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nigel.stanger / Publications

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Commits on 2017-05-30

Nigel Stanger	• Ignored main LaTeX PDF output.	994a899
Nigel Stanger	• Moved .gitignore file into subdirectory.	f652cb0
Nigel Stanger	• Moved files in preparation for repository merge.	06e74f6
Nigel Stanger	• Fixed blanks in some file and directory names.	10ae7b6

Commits on 2013-05-06

Nigel Stanger	- Fixed file permissions.	511ef08
Nigel Stanger	- Added IwC directory. - Added .gitignore.	8f1dfc6

Commits on 2005-08-09

nstanger

- Started conversion to B&IT format. - Changed file and directory names.

8967377

Commits on 2005-06-01

nstanger

- Changed title of conclusions. - Added [reviewcopy] option to get double spacing.

eefaed3

Commits on 2005-05-31

nstanger	- Added a \newpage after the title.	84dcf4b
nstanger	- Added "(degrees)" to x-axis caption.	86ef8e1
nstanger	- Tweaked things to fit IwC submission guidelines.	420a4b3

Commits on 2005-05-30

nstanger

- Added missing Ferguson reference.

dfd746b

Commits on 2005-05-26

nstanger

- Added new screen shot of test environment. - Removed Apple reference from caption of target sizes table.

55d1947

Commits on 2005-05-05

nstanger

- Added inadvertently missing diagram source.

fe2123d

Commits on 2005-05-03

nstanger

- Added reference for touch screen overlay. - Split bar charts by device. - De-colourised all graphics. - Revamped definition of target sizes. - Added more cross references. - Fixed incorrect p value and non-adjusted error rates, etc. - Moved combo box selection discussion from "Procedure" into "Design". - Revamped percentage comparisons. - Added combo box vs. Fitts' Law discussion. - Tweaked a bunch of little things.

0e2a614

Commits on 2005-04-26

nstanger

- Removed "clever" BibTeX processing that didn't work from scratch.

263869a

Commits on 2005-04-25

nstanger	- Added combo box selection diagrams. - Removed obsolete graphics files.	d8a5819
nstanger	- Cleaned up various bits of text and ensured consistent terminology use. - Reformatted equations. - Added Fitts reference. - Added note about questionnaire's general feedback section. - Added discussion of combo box complexities (one- vs. two-step, etc.), and moved combo box figure into same section. - Expanded discussion of general experiment setup, and moved test environment figure into same section. - Revamped Apparatus section; added notes about parallax effects. - Swapped order of Design and Procedure sections. - Expanded discussion of trials and target angles & distances. - Added note about adjustment of combo box distance. - Revamped Procedure section; revisited combo box complexities. - Reorganised paragraphs in Adjusting for learning section. - Expanded discussion of learning adjustments. - Adjusted captions of most graphs. - Added note about "two-click" selection assumption to Error rate section. - Reorganised Comfort section. - Added Other findings section. - Revamped and updated conclusions. - Spell-checked!	194358c
nstanger	- Added selection coordinate variation data and ploticus script file.	e5535be
nstanger	- Added suffixes list. - Removed .sxd rule. - Added new variation images. - Added -dNOCACHE to ps2pdf to fix font rendering problem.	3771b09
nstanger	- Trimmed abbreviation list. - Added Fitts 1954 reference.	01f3004

Commits on 2005-04-18

nstanger

- Revamped the evaluation section. - Added \ISOnine macro to make sure that I say "ISO 0241-9" consistently :) - Added some more references. - Removed unnecessary URLs from references.

164b4cf

Commits on 2005-02-10

nstanger

- Added screenshot graphics. - Changed title slightly. - Shortened abstract. - Revamped GUI targets section. - Added note about check box sizes to Table 1.

170fb2d

Commits on 2005-02-04

nstanger	- Tweaked layout slightly.	f3d62ae
nstanger	- Added learning spreadsheet and linechart script to generate learning graphs. - Cleaned up appearance of bar charts. - Centred all figures	9744493
nstanger	- Changed order of building graphics so that they are built before the first LaTeX run.	6f15657

Patch

Showing 26 changed files

Ignore Space Show notes View Gleeson_2005/.gitignore 0 → 100644
Gleeson_paper.pdf

Ignore Space Show notes View Gleeson_2005/Gleeson_paper.bib 0 → 100644
This file was created with JabRef 1.6. Encoding: ISO8859_1 @STRING{IJMMS = {International Journal of Man-Machine Studies}} @STRING{LNCS = {Lecture Notes in Computer Science}} @STRING{Reg = {{\scriptsize\textsuperscript{\textregistered}}}} @PHDTHESIS{Bend-G-1999-PhD, author = {Gregory T. Bender}, title = {Touch Screen Performance as a Function of the Duration of Auditory Feedback and Target Size}, school = {Wichita State University}, year = {1999}, type = {PhD thesis}, address = {Wichita, Kansas}, pdf = {B/Bend-G-1999-PhD.pdf}, } @BOOK{Appl-2004-HIG, title = {Apple Human Interface Guidelines}, publisher = {Apple Computer, Inc.}, year = {2004}, author = {{Apple Computer}}, month = may, pdf = {A/Appl-2004-HIG.pdf}, } @INPROCEEDINGS{Doug-SA-1999-CHI, author = {Sarah A. Douglas and Arthur E. Kirkpatrick and I. Scott MacKenzie}, title = {Testing pointing device performance and user assessment with the {ISO} 9241, {P}art 9 standard.}, booktitle = {The CHI is the Limit: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '99)}, year = {1999}, pages = {215--222}, address = {Pittsburgh, Pennsylvania}, month = may # {~15--20}, publisher = {ACM Press}, doi = {doi:10.1145/302979.303042}, pdf = {D/Doug-SA-1999-CHI.pdf}, } @INPROCEEDINGS{Doug-SA-1994-SIGCHI, author = {Sarah A. Douglas and Anant Kartik Mithal}, title = {The effect of reducing homing time on the speed of a finger-controlled isometric pointing device}, booktitle = {Celebrating Interdependence: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '94)}, year = {1994}, pages = {411--416}, address = {Boston, Massachusetts}, month = apr # {~24--28}, publisher = {ACM Press}, doi = {doi:10.1145/191666.191805}, pdf = {D/Doug-SA-1994-SIGCHI.pdf}, isbn = {0-89791-650-6}, } @ARTICLE{Ferg-EL-2004-Nutrition, author = {Elaine L. Ferguson and N. Darmon and A. Briend and I. Premachandra}, title = {Food-based dietary guidelines can be developed and tested using Linear Programming}, journal = {Journal of Nutrition}, year = {2004}, volume = {134}, pages = {951--957}, } @ARTICLE{Fitt-PM-1954-Law, author = {Paul M.\ Fitts}, title = {The information capacity of the human motor system in controlling the amplitude of movement}, journal = {Journal of Experimental Psychology}, year = {1954}, volume = {47}, pages = {381--391}, number = {6}, month = jun, } @ARTICLE{Hara-H-1996, author = {Harada, H. and Katsuura, T. and Kikuchi, Y.}, title = {Fundamental study on the size and inter-key spacing of numeric keys for touch screen}, journal = {Journal of Human Ergology}, year = {1996}, volume = {25}, pages = {167--174}, number = {2}, month = dec, } @TECHREPORT{ISO-2000-9241-9, author = {ISO}, title = {Ergonomic {R}equirements for {O}ffice {W}ork with {V}isual {D}isplay {T}erminals ({VDT}s)---{P}art 9: {R}equirements for {N}on-keyboard {I}nput {D}evices}, institution = {International Organisation for Standardisation (ISO)}, year = {2000}, type = {International standard}, number = {ISO 9241-9:2000}, address = {Geneva, Switzerland}, } @MISC{Keyt-2005-Touch, author = {{KEYTEC}}, title = {{KEYTEC} add-on magic touch screen for 16--17'' {LCD} and {CRT} monitors}, howpublished = {Web document, KEYTEC, Inc., Richardson, Texas}, year = {2005}, note = {Accessed 3 May 2005.}, url = {http://www.magictouch.com/KTMT-1700.html}, } @INPROCEEDINGS{Mack-IS-2001-EHCI, author = {I. Scott MacKenzie and Shaidah Jusoh}, title = {An evaluation of two input devices for remote pointing}, booktitle = {Proceedings of the 8th IFIP International Conference on Engineering for Human-Computer Interaction (EHCI 2001, revised papers)}, year = {2001}, editor = {Murray Reed Little and Laurence Nigay}, volume = {2254}, series = LNCS, pages = {235--250}, address = {Toronto, Canada}, month = may # {~11--13}, publisher = {Springer}, isbn = {3-540-43044-X}, pdf = {M/Mack-IS-2001-EHCI.pdf}, citeseerurl = {http://citeseer.ist.psu.edu/609516.html}, } @INPROCEEDINGS{Mack-IS-1991, author = {I. Scott MacKenzie and Abigail Sellen and William A. S. Buxton}, title = {A comparison of input devices in element pointing and dragging tasks}, booktitle = {Reaching Through Technology: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '91)}, year = {1991}, pages = {161--166}, address = {New Orleans, Louisiana}, month = apr # {~27--} # may # {~2}, doi = {doi:10.1145/108844.108868}, pdf = {M/Mack-IS-1991.pdf}, } @BOOK{MS-1999-UI, title = {Microsoft} # Reg # { Windows} # Reg # { User Experience: Official Guidelines for User Interface Developers and Designers}, publisher = {Microsoft Press}, year = {1999}, author = {{Microsoft Corporation}}, series = {Microsoft} # Reg # { Professional Editions}, isbn = {0735605661}, } @INPROCEEDINGS{Po-BA-2004-CHI, author = {Barry A. Po and Brian D. Fisher and Kellogg S. Booth}, title = {Mouse and touchscreen selection in the upper and lower visual fields}, booktitle = {Proceedings of the 2004 Conference on Human Factors in Computing Systems (CHI 2004)}, year = {2004}, editor = {Elizabeth Dykstra-Erickson and Manfred Tscheligi}, pages = {359--366}, address = {Vienna, Austria}, month = apr # {~24--29}, doi = {doi:10.1145/985692.985738}, pdf = {P/Po-BA-2004-CHI.pdf}, } @ARTICLE{Sear-A-1993-BIT, author = {Andrew Sears and D. Revis and J. Swatski and R. Crittenden and Ben Shneiderman}, title = {Investigating touchscreen typing: {T}he effect of keyboard size on typing speed}, journal = {Behavior {\&} Information Technology}, year = {1993}, volume = {12}, pages = {17--22}, number = {1}, month = jan # {--} # feb, } @ARTICLE{Sear-A-1991-IJMMS, author = {Andrew Sears and Ben Shneiderman}, title = {High precision touchscreens: {D}esign strategies and comparisons with a mouse}, journal = IJMMS, year = {1991}, volume = {34}, number = {4}, pages = {593--613}, }

Ignore Space Show notes View

Gleeson_2005/Gleeson_paper.bib 0 → 100644

This file was created with JabRef 1.6.
Encoding: ISO8859_1

@STRING{IJMMS = {International Journal of Man-Machine Studies}}

@STRING{LNCS = {Lecture Notes in Computer Science}}

@STRING{Reg = {{\scriptsize\textsuperscript{\textregistered}}}}

@PHDTHESIS{Bend-G-1999-PhD,
  author = {Gregory T. Bender},
  title = {Touch Screen Performance as a Function of the Duration of Auditory Feedback and Target Size},
  school = {Wichita State University},
  year = {1999},
  type = {PhD thesis},
  address = {Wichita, Kansas},
  pdf = {B/Bend-G-1999-PhD.pdf},
}

@INPROCEEDINGS{Doug-SA-1999-CHI,
  author = {Sarah A. Douglas and Arthur E. Kirkpatrick and I. Scott MacKenzie},
  title = {Testing pointing device performance and user assessment with the {ISO} 9241, {P}art 9 standard.},
  booktitle = {The CHI is the Limit: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '99)},
  year = {1999},
  pages = {215--222},
  address = {Pittsburgh, Pennsylvania},
  month = may # {~15--20},
  publisher = {ACM Press},
  doi = {doi:10.1145/302979.303042},
  pdf = {D/Doug-SA-1999-CHI.pdf},
}

@INPROCEEDINGS{Doug-SA-1994-SIGCHI,
  author = {Sarah A. Douglas and Anant Kartik Mithal},
  title = {The effect of reducing homing time on the speed of a finger-controlled isometric pointing device},
  booktitle = {Celebrating Interdependence: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '94)},
  year = {1994},
  pages = {411--416},
  address = {Boston, Massachusetts},
  month = apr # {~24--28},
  publisher = {ACM Press},
  doi = {doi:10.1145/191666.191805},
  pdf = {D/Doug-SA-1994-SIGCHI.pdf},
  isbn = {0-89791-650-6},
}

@ARTICLE{Ferg-EL-2004-Nutrition,
  author = {Elaine L. Ferguson and N. Darmon and A. Briend and I. Premachandra},
  title = {Food-based dietary guidelines can be developed and tested using Linear Programming},
  journal = {Journal of Nutrition},
  year = {2004},
  volume = {134},
  pages = {951--957},
}

@ARTICLE{Fitt-PM-1954-Law,
  author = {Paul M.\ Fitts},
  title = {The information capacity of the human motor system in controlling the amplitude of movement},
  journal = {Journal of Experimental Psychology},
  year = {1954},
  volume = {47},
  pages = {381--391},
  number = {6},
  month = jun,
}

@ARTICLE{Hara-H-1996,
  author = {Harada, H. and Katsuura, T. and Kikuchi, Y.},
  title = {Fundamental study on the size and inter-key spacing of numeric keys for touch screen},
  journal = {Journal of Human Ergology},
  year = {1996},
  volume = {25},
  pages = {167--174},
  number = {2},
  month = dec,
}

@TECHREPORT{ISO-2000-9241-9,
  author = {ISO},
  title = {Ergonomic {R}equirements for {O}ffice {W}ork with {V}isual {D}isplay {T}erminals ({VDT}s)---{P}art 9: {R}equirements for {N}on-keyboard {I}nput {D}evices},
  institution = {International Organisation for Standardisation (ISO)},
  year = {2000},
  type = {International standard},
  number = {ISO 9241-9:2000},
  address = {Geneva, Switzerland},
}

@MISC{Keyt-2005-Touch,
  author = {{KEYTEC}},
  title = {{KEYTEC} add-on magic touch screen for 16--17'' {LCD} and {CRT} monitors},
  howpublished = {Web document, KEYTEC, Inc., Richardson, Texas},
  year = {2005},
  note = {Accessed 3 May 2005.},
  url = {http://www.magictouch.com/KTMT-1700.html},
}

@INPROCEEDINGS{Mack-IS-2001-EHCI,
  author = {I. Scott MacKenzie and Shaidah Jusoh},
  title = {An evaluation of two input devices for remote pointing},
  booktitle = {Proceedings of the 8th IFIP International Conference on Engineering for Human-Computer Interaction (EHCI 2001, revised papers)},
  year = {2001},
  editor = {Murray Reed Little and Laurence Nigay},
  volume = {2254},
  series = LNCS,
  pages = {235--250},
  address = {Toronto, Canada},
  month = may # {~11--13},
  publisher = {Springer},
  isbn = {3-540-43044-X},
  pdf = {M/Mack-IS-2001-EHCI.pdf},
  citeseerurl = {http://citeseer.ist.psu.edu/609516.html},
}

@INPROCEEDINGS{Mack-IS-1991,
  author = {I. Scott MacKenzie and Abigail Sellen and William A. S. Buxton},
  title = {A comparison of input devices in element pointing and dragging tasks},
  booktitle = {Reaching Through Technology: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '91)},
  year = {1991},
  pages = {161--166},
  address = {New Orleans, Louisiana},
  month = apr # {~27--} # may # {~2},
  doi = {doi:10.1145/108844.108868},
  pdf = {M/Mack-IS-1991.pdf},
}

@BOOK{MS-1999-UI,
  title = {Microsoft} # Reg # { Windows} # Reg # { User Experience: Official Guidelines for User Interface Developers and Designers},
  publisher = {Microsoft Press},
  year = {1999},
  author = {{Microsoft Corporation}},
  series = {Microsoft} # Reg # { Professional Editions},
  isbn = {0735605661},
}

@INPROCEEDINGS{Po-BA-2004-CHI,
  author = {Barry A. Po and Brian D. Fisher and Kellogg S. Booth},
  title = {Mouse and touchscreen selection in the upper and lower visual fields},
  booktitle = {Proceedings of the 2004 Conference on Human Factors in Computing Systems (CHI 2004)},
  year = {2004},
  editor = {Elizabeth Dykstra-Erickson and Manfred Tscheligi},
  pages = {359--366},
  address = {Vienna, Austria},
  month = apr # {~24--29},
  doi = {doi:10.1145/985692.985738},
  pdf = {P/Po-BA-2004-CHI.pdf},
}

@ARTICLE{Sear-A-1993-BIT,
  author = {Andrew Sears and D. Revis and J. Swatski and R. Crittenden and Ben Shneiderman},
  title = {Investigating touchscreen typing: {T}he effect of keyboard size on typing speed},
  journal = {Behavior {\&} Information Technology},
  year = {1993},
  volume = {12},
  pages = {17--22},
  number = {1},
  month = jan # {--} # feb,
}

@ARTICLE{Sear-A-1991-IJMMS,
  author = {Andrew Sears and Ben Shneiderman},
  title = {High precision touchscreens: {D}esign strategies and comparisons with a mouse},
  journal = IJMMS,
  year = {1991},
  volume = {34},
  number = {4},
  pages = {593--613},
}

Ignore Space Show notes View Gleeson_2005/Gleeson_paper.tex 0 → 100644
\documentclass[a4paper]{article} \usepackage{natbib} \usepackage[dvips,margin=3cm]{geometry} \usepackage{graphicx} \usepackage{amssymb} \usepackage{units} \usepackage{url} \usepackage{flafter} \title{\textbf{Assessing the efficacy of a touch screen overlay as a selection device for typical GUI targets}} \author{M.\ GLEESON\dag, N.\ STANGER\thanks{Corresponding author. Email nstanger@infoscience.otago.ac.nz.} \dag\ and E.\ FERGUSON\ddag} \date{\dag Department of Information Science, \\ \ddag Department of Human Nutrition, \\ University of Otago, Dunedin, New Zealand} \begin{document} \renewcommand{\baselinestretch}{2} \maketitle \begin{quotation} \noindent In this paper we investigate the efficacy of a touch screen overlay compared to a mouse, when selecting typical graphical user interface (GUI) items in a desktop information system. A series of tests were completed involving multi-directional point and select tasks, and the results for both devices compared. The results showed that the touch screen overlay was not suitable for selecting GUI targets smaller than \unit[4]{mm}. The touch screen overlay was slower and had a higher error rate than the mouse, but there was no significant difference in throughput. Testers rated the mouse easier to use and to make accurate selections, while the touch screen overlay resulted in greater arm, wrist and finger fatigue. These results suggest that a touch screen overlay is not a practical selection device for desktop interfaces with small GUI targets. \end{quotation} \begin{quotation} \noindent \emph{Keywords:} Touch screen overlay; Mouse; Selection device; Fitts' Law; Performance evaluation; GUI item \end{quotation} % main text \newcommand{\ISOnine}{ISO 9241-9} \section{Introduction} \label{sec-introduction} Most modern information systems that run on desktop personal computers are designed to be used with a keyboard and mouse. While the combination of keyboard and mouse is the accepted method of interaction with such systems it does not necessarily suit all information systems. Information systems with limited data entry may be more usable through the use of a keyboard and touch screen. Touch screens require less physical space and thus the workstation environment in an office setting could be improved, allocating more space to the user and less to the computer. The purpose of this paper is to investigate how effective a touch screen overlay is compared to a mouse, when selecting typical graphical user interface (GUI) items. The target types tested were buttons, check boxes, combo boxes and text boxes, which are typical of those found in an interface for an information system. Each target type was tested at three different sizes (see Section~\ref{sec-GUI}). A typical touch screen device comprises a monitor enhanced with hardware for detecting touches on the screen surface. An alternative approach is to attach a discrete touch-sensitive surface to an existing conventional monitor. \citet{Sear-A-1991-IJMMS} have previously assessed the efficacy of specialised touch screen hardware, but there appears to have been little research into the efficacy of touch screen overlays. We therefore chose to compare the performance of a touch screen overlay with that of a mouse. The testing occurred in the context of a research project undertaken by the Department of Human Nutrition at the University of Otago. This project aims to improve complementary feeding diets for toddlers in New Zealand, by designing a computer program to help formulate population-specific food-based dietary guidelines for this high risk group. The program, which is based on a previously published linear programming approach \citep{Ferg-EL-2004-Nutrition}, is a decision-making tool, designed specifically for nutrition programme planners to assist them in selecting appropriate and improved home-based complementary foods. % do we need this? The remainder of the paper discusses our experiment and the results obtained. Section~\ref{sec-GUI} briefly describes the types of targets used in the experiment, while Section~\ref{sec-evaluation} describes the measures used to evaluate the selection devices. The experimental design is described in Section~\ref{sec-method}. Section~\ref{sec-analysis} describes how the data were analysed, and Section~\ref{sec-results} presents the results of the experiment. Our conclusions are presented in Section~\ref{sec-conclusions}. \section{GUI targets} \label{sec-GUI} Since the 1980's much work has gone into developing human computer interface guidelines. Today's interfaces are made up of a combination of different targets that include text boxes, check boxes, combo boxes, list boxes, buttons, labels, tool bars, etc. \citet{Sear-A-1991-IJMMS} showed that touch screens can be successfully used as a selection device and can have advantages over a mouse, even for small targets. These results were, however, based on selecting arbitrary shapes and not the typical targets found in modern GUIs. To accurately test the performance of each selection device within the experiment, three different sizes of GUI target were used, corresponding to small, medium and large GUI items. As our experiment took place in a Windows environment, we would have preferred to base these sizes on Microsoft's user interface guidelines. However, Microsoft's guidelines specify only a single standard size for most GUI items \citep[pp.\ 448--450]{MS-1999-UI}. \citeauthor{Appl-2004-HIG}'s \citeyearpar{Appl-2004-HIG} human interface guidelines specify three standard sizes (mini, small and large), but these proved to be rather small in our Windows-based testing environment. We therefore adjusted Apple's three sizes such that the ``small'' size was consistent with Microsoft's guidelines. The resultant target sizes are listed in Table~\ref{tab-target-sizes}. A screen resolution of \unit[81]{DPI} was assumed. \begin{table}[ht] \caption{Target sizes (width \(\times\) height) used in the experiment.} \label{tab-target-sizes} \begin{tabular}{llll} \hline \textbf{Target type} & \textbf{Large} & \textbf{Medium} & \textbf{Small} \\ \hline Text box & \(\unit[63]{mm} \times \unit[11]{mm}\) & \(\unit[55]{mm} \times \unit[8]{mm}\) & \(\unit[47]{mm} \times \unit[6]{mm}\) \\ Combo box & \(\unit[63]{mm} \times \unit[11]{mm}\) & \(\unit[55]{mm} \times \unit[8]{mm}\) & \(\unit[47]{mm} \times \unit[6]{mm}\) \\ Button & \(\unit[28]{mm} \times \unit[13]{mm}\) & \(\unit[24]{mm} \times \unit[9]{mm}\) & \(\unit[17]{mm} \times \unit[6]{mm}\) \\ Check box\(^{a}\) & \(\unit[9]{mm} \times \unit[9]{mm}\) & \(\unit[6]{mm} \times \unit[6]{mm}\) & \(\unit[4]{mm} \times \unit[4]{mm}\) \\ \hline \end{tabular} {\footnotesize \(^{a}\)This refers to the size of the check box itself, not the associated text label.} \end{table} \section{Evaluation methods} \label{sec-evaluation} Each selection device was assessed using a combination of performance and comfort measures. The performance measures were primarily taken from the \ISOnine\ standard \citep{ISO-2000-9241-9}, while the comfort measures were derived from a questionnaire administered to test participants. \subsection{Performance} \label{sec-evaluation-performance} ISO 9241 specifies standards for the ergonomic design of office computing environments. Part 9 of this standard describes different tests that can be used to evaluate one or more pointing devices \citep{ISO-2000-9241-9}. The standard describes a serial point and select task and recognises a dependent measure used with this test, known as \emph{throughput}. The serial test comprises moving the cursor back and forth between two targets using the pointing device and selecting each target by pressing and releasing a button on the pointing device. One disadvantage of this approach is that only two targets are used in the test and therefore interactions between more than two targets---which often occur in a typical information system interface---are not studied. \citet{Mack-IS-2001-EHCI} note that throughput is a very important measure, as it reflects the efficiency of the user completing the task and is a measure of both speed and accuracy. Throughput is calculated by the formula \(\mathit{throughput} = \mathit{ID}_{e} / \mathit{MT}\), where \(\mathit{MT}\) is the movement time in seconds (defined as the time taken to successfully select a target) and \(\mathit{ID}_{e}\) is Fitts' \citeyearpar{Fitt-PM-1954-Law} \emph{index of difficulty} measured in bits. Throughput is thus measured in bits per second (bps). The index of difficulty is calculated by the formula \(\mathit{ID}_{e} = \log_{2}((D / W_{e}) + 1)\), where \(D\) is the distance to the target and \(W_{e}\) is the \emph{effective width} of the target. The effective width reflects spatial variability in a sequence of trials, and thus differs from the actual width of the target. The effective width of a target is calculated by the formula \(W_{e} = 4.133 \times \mathit{SD}_{x}\), where \(\mathit{SD}_{x}\) is the standard deviation in the selection coordinates measured along the path to target \(x\). \ISOnine\ does not provide any guidance on the range of index of difficulty values to use in testing. \citet{Doug-SA-1999-CHI} recommend using a range from 2 to 6 bits. They also recommend calculating the \emph{error rate} as a separate dependent measure of accuracy. The error rate is defined as the ratio of incorrect to correct selections made on a target, so an error rate of 100\% implies that there were as many errors made as correct selections. Error rate is not included in \ISOnine, but has been used in several other studies \citep{Sear-A-1991-IJMMS,Sear-A-1993-BIT,Hara-H-1996,Bend-G-1999-PhD, Doug-SA-1999-CHI,Mack-IS-2001-EHCI,Po-BA-2004-CHI}. Computing both throughput and error rate gives a more detailed performance analysis for the selection device in question. \subsection{Comfort} \label{sec-evaluation-comfort} ISO 9241-9 argues that to fully evaluate a selection device requires assessment of user effort and comfort in addition to performance measurements. Comfort is subjective and can be assessed by means of questionnaires, while effort can be evaluated objectively by measuring the biomechanical load on users as they use a device. Unfortunately, such measurements require reasonably sophisticated equipment \citep{Doug-SA-1999-CHI} that was not available to us. We therefore omitted effort measurements from our experiment. A questionnaire was used to assess comfort and user satisfaction for each selection device in our experiment. The selection device assessment questionnaire comprised sixteen questions, eight of which were taken from the ISO ``Independent Questionnaire for Assessment of Comfort'' \citep{Doug-SA-1999-CHI}. The remaining eight questions related specifically to the target types and target sizes that were tested. In particular, the questionnaire aimed to assess the participants' comfort in using the selection device, the difficulty in accurately selecting each of the target types and the preferred size of each target type using the selection device. The responses to twelve of the questions were based on a five point ordinal scale. The remaining four questions referred to the participant's preferred size for each target type and were based on a three point response corresponding to the target sizes tested---small, medium and large (see Table~\ref{tab-target-sizes}). There was also a space for participants to provide additional general feedback about the testing process. \subsection{Other considerations} \label{sec-evaluation-other} \citet{Doug-SA-1999-CHI} also note that \ISOnine\ does not take into account any possible effects of learning, which can affect movement time and accuracy. For example, \citet{Mack-IS-1991} found that the movement times from the first of five testing sessions were significantly higher than in later sessions. This can be explained as a result of learning and shows that input device studies should take learning into account and test for it; indeed, \citet{Doug-SA-1999-CHI} recommend applying a repeated measures paradigm and testing for learning effects. One interesting aspect of using typical GUI items as targets is the variation in selection behaviour for different target types, compared to earlier studies that used simple rectangular targets. The button, check box and text box target types can be said to exhibit a ``one-step'' selection behaviour, because they require only single action (i.e., the user clicks on them) in order to be selected. A combo box is different, however, because it exhibits a ``two-step'' selection behaviour: first the combo box must be selected in order to show the list of items, and then an item must be selected from the displayed list, as illustrated in Figure~\ref{fig-combo-box}. To complicate matters further, users may execute this two-step behaviour using either a ``one-click'' or a ``two-click'' approach. In the former approach, the user clicks on the combo box, drags down to the desired list item, then releases. In the latter approach, the user clicks once on the combo box, then clicks again on the desired list item. If the drop-down list were longer than what could be displayed on screen, this could even lead to a ``multiple-click'' approach, where the user clicks multiple times on the downward scroll arrow in the list. We have, however, not considered this possibility in our experiment. \begin{figure}[ht] \centering \includegraphics[scale=0.8]{combobox-step1}\quad\quad\quad \includegraphics[scale=0.8]{combobox-step2} \caption{The ``two-step'' action required to select a combo box.} \label{fig-combo-box} \end{figure} \section{Method} \label{sec-method} An experiment was carried out to test the effect of size for different GUI target types with different selection devices. The experiment involved participants completing a series of simple point and select tasks. Small, medium and large sizes (see Table~\ref{tab-target-sizes}) were tested for combo boxes, text boxes, check boxes and buttons, using either a touch screen overlay or a mouse. The test was multi-directional, meaning the targets appeared in multiple directions from the initial starting point. A variety of different sizes, angles and distances were used for each target position. The test itself comprised a screen containing a button in the centre and a target for the participant to select as illustrated in Figure~\ref{fig-test-environment}. When a participant clicked on the centre ``Go'' button, a trial was started and a target appeared on the screen. The trial ended when the participant successfully clicked the target, which then disappeared. The time taken between clicking the ``Go'' button and successfully clicking on the target was recorded as well as the number of errors made during the trial. The final coordinates of the successful click on the target were recorded in order to calculate the effective width of the target. \begin{figure} \centering \includegraphics[scale=0.5]{test-environment} \caption{Screenshot of the test environment with a target in the top left of the screen and the ``Go'' button in the centre.} \label{fig-test-environment} \end{figure} \subsection{Participants} \label{sec-method-participants} A participant sample size of twenty-four was used for the experiment. Each participant was allocated to one of two groups with each group using one selection device in testing. The allocation of groups was based on the results of a questionnaire completed by each participant prior to testing. The purpose of the pre-test questionnaire was to establish the level of computer, mouse and touch screen experience of each participant. Participants were then allocated to a selection device group based on which device they had the least experience with. Due to the testing being done within the nutrition program environment mentioned in Section~\ref{sec-introduction}, the participants were all nutritionists (i.e., typical users of the program). There were twenty-one female and three male participants, all with a university level of education. All participants were unpaid volunteers. \subsection{Apparatus} \label{sec-method-apparatus} The test environment was implemented in Visual Basic.NET using Microsoft Studio 2003, and is illustrated in Figure~\ref{fig-test-environment}. During each test, data corresponding to the relevant measures (movement time, number of errors and selection coordinates) were captured by the software and automatically written to a Microsoft Excel worksheet. The touch screen used in testing was a 17'' Magic Touch USB overlay Model KTMT-1700-USB-M \citep{Keyt-2005-Touch}. This device uses a take-off touch strategy, that is, a selection is not confirmed until the user's finger is removed from the screen. An important property of touch screen overlays is that they are placed over a conventional monitor and the touch surface is thus not coincident with the display surface. This can cause a slight discrepancy or parallax effect between where the user touches the overlay and where the cursor is positioned on the screen. The touch screen overlay was fitted to a Dell 15'' Flat Panel Model E151FPb monitor. A flat panel monitor was chosen because it was noticed during pre-testing that typical CRT monitors with curved screens produced a variable gap between the overlay and the display surface, thus potentially leading to a greater parallax effect than with a flat display surface. The mouse used in testing was a standard Dell PS/2 Optical Mouse Model M071KC. Both devices were connected to a Dell Inspiron 7500 laptop computer that ran the testing software. \subsection{Design} \label{sec-method-design} A mixed design experiment was used with the selection device as a between-subjects factor. The independent (between-subject) variables were: \begin{itemize} \item Target type (text box, combo box, button and check box) \item Target size (large, medium and small---see Table~\ref{tab-target-sizes}) \item Target distance (\unit[40]{mm}, \unit[80]{mm} and \unit[160]{mm}---see below) \item Target angle (\(45^{\circ}\), \(135^{\circ}\), \(225^{\circ}\) and \(315^{\circ}\)---see below) \item Trial (1 to 144) \item Block (1 to 6) \end{itemize} The dependent variables within the experiment were throughput, movement time and error rate. The entire test was divided into six blocks. Each block contained every possible combination of target type (four combinations), size (three combinations), angle from initial starting point (four combinations) and distance from initial starting point (three combinations). Consequently there were 144 trials in each block and the entire experiment per participant comprised a total of 864 trials (six blocks of 144 trials each). Combinations of target type, distance and angle were presented to the participant in random sequence with no repetition. Target size was deliberately set to large for the first forty-eight trials in each block, followed by medium for the next forty-eight trials, and finally small for the remaining trials, in order to compensate for learning effects. The combination of distance and angle from the initial starting point yielded twelve possible target positions for each trial, as illustrated in Figure~\ref{fig-target-positions}. Three distances were used that represented target positions ranging from close to the initial starting point to very far away from the initial starting point. Four angles were chosen so that targets could be tested in ninety degree blocks and to provide a good range of screen positions for the target. The first angle was set to \(45^{\circ}\) with \(90^{\circ}\) increments thereafter, in order to mimic real life user interface target selection, where targets are situated in different areas of the screen and therefore selections are made in multiple directions that are neither simply horizontal nor vertical. \begin{figure} \centering \includegraphics{target-positions} \caption{Positions of targets tested. The black box represents the initial starting point and the rounded rectangles represent the target positions.} \label{fig-target-positions} \end{figure} The index of difficulty (\(\mathit{ID}_{e}\)) was ascertained for each possible task using the combination of distance and non-adjusted target width. This showed that the test had a range of \(\mathit{ID}_{e}\) values from \unit[0.7]{bits} (\unit[63]{mm} width and \unit[160]{mm} distance) to \unit[5.4]{bits} (\unit[4]{mm} width and \unit[40]{mm} distance). It is important to note that the combo box distance values were adjusted in these calculations to reflect the two-step selection behaviour of this target type (as discussed in Section~\ref{sec-evaluation-other}). That is, we need to consider not just the distance from the initial starting point to the target, but also the extra distance from the main combo box to the selected list item. In our experiment, participants were told to always select the third list item in combo boxes (as illustrated in Figure~\ref{fig-combo-box}), so the adjusted distance for a combo box was equal to the normal distance from the initial starting point to the target, \emph{plus} the additional distance to the third list item. Additional data about the selections made on combo boxes were recorded in order to account for the selection approach of the participant, whether it be a ``one-click'' or ``two-click'' approach. \subsection{Procedure} \label{sec-method-procedure} The participant was given an introduction to the test by the research observer, which included a brief summary of the aims of the study and what the test involved. The participant was also given an instruction sheet that they had access to throughout the duration of the test. After reading the instruction sheet the participant had the opportunity to ask questions or raise any issues. Participants were instructed to complete each block of trials as quickly as possible without losing accuracy. Participants were given the opportunity to rest for as long as they wished between blocks. It was made clear to participants that a task was only complete once the target was successfully selected. Before the test began, participants were instructed to complete a practice session involving fifteen random trials of the same point and select tasks used in the test. This brought all participants up to a minimal level of experience with their selection device. This also meant that each participant knew how to correctly select each target type including the combo box. At the conclusion of the test the participant was asked to fill out a questionnaire regarding comfort and user satisfaction with the selection device used. \section{Analysis} \label{sec-analysis} The data collected from the software included movement time, error rate and throughput and was used to evaluate selection device performance. A mixed design repeated measures analysis of variance model (MANOVA) was used for movement time and throughput to examine within subject differences in target type and size, as well as between subject differences in selection device. A Greenhouse and Geisser correction of the F-ratio was used whenever the Mauchly's test results showed that assumptions of sphericity were violated. Post hoc tests, for multiple comparisons, were made using the Bonferroni method. Due to the skew observed in the error rate data (see Section~\ref{sec-results-learning}), inter-device differences in error rates were assessed using the Mann-Whitney U Test. The comfort questionnaire was based on a five point ordinal scale, where five generally indicated a poor rating. Because of the small data size, a Mann-Whitney (non-parametric) test was used. All statistical analyses were performed using SPSS version 11.0. A \emph{p}-value of \(< 0.05\) was considered statistically significant. \section{Results and discussion} \label{sec-results} \subsection{Adjusting for learning} \label{sec-results-learning} \citet{Doug-SA-1999-CHI} have shown that the effects of learning can affect movement time and accuracy. They therefore recommend that input device studies should apply a repeated measures paradigm and test for learning effects. From analysing the results of movement time and throughput over each test block, it was clear for the combo box and check box target types that learning occurred from the first to the second block with the touch screen overlay, as seen in Figure~\ref{fig-movement-time-learning}. Due to prior participant experience, no learning was observed with the mouse. No learning occurred with the text box or button, most likely due to their relatively large size and simple selection behaviour. \begin{figure} \centering \includegraphics{combobox-learning} \includegraphics{checkbox-learning} \caption{Learning is displayed for movement time by selection device and test block for the combo box and check box.} \label{fig-movement-time-learning} \end{figure} Statistical analysis using a simple repeated measure ANOVA was carried out on movement time for both the check box and combo box. For movement time of the combo box, the effect of block \(\times\) device was significant \((F(1.549, 1335.219) = 4.373, p < 0.05)\). Helmhert contrasts showed that the differences between blocks became non-significant after block 1 \((p > 0.05)\), which implies that learning occurred during block 1. For movement time of the check box, the effect of block \(\times\) device was significant \((F(1.608, 1385.960) = 4.763, p < 0.05)\). Helmhert contrasts again showed that the differences between blocks became non-significant after block 1 \((p > 0.05)\), implying that learning occurred during block 1. To account for learning with the combo and check box, results from block 6 only were used to calculate the movement time and throughput measures, as the results from block 6 alone gave a good measure of performance. However, the error rate results were highly skewed for both target types, with two participants accounting for almost 90\% of the errors. Error rates for the check box and combo box were therefore calculated using results from all six test blocks. \subsection{Movement time} \label{sec-results-movement} The results showed that the mouse had an overall movement time of \unit[1.32]{s} across all target types compared to \unit[1.57]{s} for the touch screen overlay. We can thus conclude that the touch screen overlay was on average 1.2 times slower than the mouse. This is interesting because \citet{Sear-A-1991-IJMMS} found that the movement times for mouse and touch screen monitor were similar for rectangular targets larger than \unit[2]{mm}. Therefore the nature of the two types of touch screen (overlay versus monitor) may affect the movement time associated with the type of touch screen. It is also likely that due to the loss of accuracy found with the overlay during testing, the touch screen monitor will have faster movement times compared to the touch screen overlay. The movement times for each target type showed that the text box had the fastest movement time, followed by the button, the check box and the combo box. These results are illustrated in Figure~\ref{fig-movement-time} and are consistent with Fitts' Law \citep{Fitt-PM-1954-Law}, in that the largest target (the text box) had the fastest movement time. It may appear that the combo box results violate Fitts' Law, as the combo box is the same size as the text box, yet is over twice as slow. In this case however, the slow movement times are not a function of the target size, but rather a result of the more complex two-step behaviour required to successfully select a combo box (which is not considered by Fitts' Law). The extra movement of selecting an item from the drop-down list clearly dramatically increases the movement time for the combo box. As the additional distance from the main combo box area to the list item is relatively short, the significant increase in movement time is therefore most likely due to users making more errors. \begin{figure} \centering \includegraphics{movement-time} \caption{Movement time by target type and device, averaged across all target sizes.} \label{fig-movement-time} \end{figure} The touch screen overlay was found to have similar movement time to the mouse for the medium and large targets, but for the small targets, the touch screen overlay was on average 1.5 times slower than the mouse. The only time that the touch screen overlay was found to be faster than the mouse was with the largest target type (the large text box), but the difference was less than one percent. The movement time for the small check box on the touch screen overlay was about 2.7 times slower than that for the mouse. The small check box was the smallest item tested, with dimensions of \unit[4]{mm} \(\times\) \unit[4]{mm}. We can conclude that the touch screen overlay was not efficient for selecting targets as small as \unit[4]{mm}. Compare this with \citet{Sear-A-1991-IJMMS}, who showed that a touch screen monitor has similar movement time to a mouse for targets as small as \unit[2]{mm}. While a touch screen monitor can be used with targets as small as \unit[2]{mm}, a touch screen overlay should only be used for targets with a size of greater than \unit[4]{mm}. The results from the error rate analysis also support this conclusion (see Section~\ref{sec-results-error-rate}). \subsection{Throughput} \label{sec-results-throughput} The average throughput for the mouse was \unit[1.242]{bps}, slightly higher than the \unit[1.214]{bps} average throughput for the touch screen overlay. The selection device by itself was shown not to have a significant effect on throughput \((F(1, 22) = 0.02, p > 0.05)\). Throughput did not vary for size but throughput did vary depending on target type \((F(2.07, 45.55) = 4.77, p < 0.001)\), as shown in Figure~\ref{fig-throughput}. Check boxes had the highest throughput rate of \unit[1.967]{bps} (sd = 0.720). This is interesting as the check box had the second worst movement time and the worst error rate. Upon further investigation it was seen that the movement time for the check box was in fact in the middle range of all targets, and due to its small size it had a high index of difficulty. These two factors are the most likely reason for the check box having such a high throughput rate. \begin{figure}[ht] \centering \includegraphics{throughput} \caption{Throughput by target type and device, averaged across all target sizes.} \label{fig-throughput} \end{figure} The combo box had the worst average throughput of \unit[0.501]{bps} (sd = 0.213). The index of difficulty was not very high for the combo box, so its low throughput rate could be attributed to its high movement time. The average throughput rate of \unit[1.242]{bps} for the mouse is much lower than that found by previous research. A study by \citet{Doug-SA-1994-SIGCHI} showed that a mouse had a throughput rate of \unit[4.15]{bps}. \citet{Mack-IS-1991} compared three devices (mouse, tablet and trackball) using four target sizes (8, 16, 32 and 64 pixels) over two different types of tasks (pointing and dragging), and found that the throughput for the mouse was \unit[4.5]{bps}. This may indicate that the level of selection difficulty in our experiment is higher than in previous research. This could be due to the selection of GUI targets instead of arbitrary rectangular targets. \subsection{Error rate} \label{sec-results-error-rate} The average error rate for the mouse was only 2.7\% which is consistent with previous studies. The touch screen overlay, on the other hand, had an average error rate of 60.8\%. \citet{Sear-A-1991-IJMMS} found that a touch screen monitor had an average error rate of 49\% but this was across much smaller targets. This suggests that there is a loss of accuracy when using a touch screen overlay as opposed to a touch screen monitor. The check box had a significantly high average error rate of 78.5\% across all sizes and both devices; in particular, the small check box on the touch screen overlay had an error rate of 393\%. The touch screen overlay incurred the majority of the errors. For all sizes of the check box the mouse produced an average error rate of 6.7\%, while the touch screen overlay produced an average error rate of 178.5\%. The distinguishing factor of the check box compared to the other target types is its small size, so we can conclude from this that a touch screen overlay is more inaccurate for selecting small targets (\unit[4]{mm} or less). The button and text box had much lower error rates than the check box and combo box (as seen in Figure~\ref{fig-error-rate}). As the button and text box also exhibited low movement times, we can conclude that these two target types have very good overall performance. \begin{figure} \centering \includegraphics{error-rate} \caption{Error rate by target type and device, averaged across all target sizes.} \label{fig-error-rate} \end{figure} Note that the error rate calculation for combo boxes assumes a ``two-click'' selection approach, as only two of the twenty-four participants used the ``one-click'' approach. Both of these participants used the mouse. \subsection{Comfort} \label{sec-results-comfort} In terms of accurate pointing the mouse (2.083) was rated easier than the touch screen overlay (3.000). These differences were statistically significant \((p < 0.01)\). The responses regarding the question on neck, wrist and arm fatigue showed that the touch screen overlay had a high rating (4.083), whereas the mouse was rated in the midpoint range (3.167). These differences were statistically significant \((p < 0.05)\). The final question rated the overall difficulty in using the selection device. The mouse (4.250) was rated easier to use than the touch screen overlay (3.333). These differences were statistically significant \((p < 0.05)\). Participants using the touch screen overlay rated both the text box and button as easy to accurately select, with the large and medium sizes being most preferred. This feedback is consistent with the data collected in that the text box and button have low movement times and low error rates (i.e., they are easy to accurately select). The combo box was rated in the middle of the range, and the check box was rated as very hard to select. Three quarters of the touch screen overlay participants preferred to select large combo boxes and check boxes, which is consistent with the high error rates and movement times associated with these two target types on the touch screen overlay. Participants using the mouse also rated the text box and button as easy to accurately select, with the large and medium sizes being most preferred. Both the combo box and check box were rated harder to select than the button and text box with the check box having the worst rating. As with the touch screen overlay, participants preferred large combo boxes and check boxes. In the general feedback, one participant noted the lack of arm support when selecting targets at the top of the screen. This is an interesting comment, because the nature of using a touch screen means the user's arm might be raised off the desk, and thus be self-supporting when selecting items towards the top of the screen. Another suggestion was making the target change colour when the cursor is located above it. This is a similar concept to that of interactive rollover items commonly used in web pages. Auditory feedback has been shown to affect speed and accuracy when making a selection \citep{Bend-G-1999-PhD}, so it is likely that the visual feedback received from GUI targets will affect the selection performance. All of the target types tested provide some form of immediate visual feedback, from the button being visually depressed to a tick appearing in the check box. Further study is needed to assess how visual feedback affects selection performance of GUI items and what is the most effective method of providing feedback. \subsection{Other findings} \label{sec-results-other} Two interesting patterns emerged when we calculated the standard deviation of the final selection coordinates on the screen. First, when selecting text boxes with the mouse, there was greater variation in final selection coordinates on the right side of the screen (\(45^{\circ}\) and \(315^{\circ}\) target angles) than on the left side of the screen (\(90^{\circ}\) and \(225^{\circ}\) target angles). This behaviour was not apparent when selecting text boxes with the touch screen overlay, as illustrated in Figure~\ref{fig-variation-textbox}. This would mean that participants using the mouse were more careful when making selections with text boxes on the left side of the screen than on the right. \begin{figure} \centering \includegraphics{variation-text-mouse} \includegraphics{variation-text-touch} \caption{Standard deviation of final selection coordinates for the text box, averaged across all target sizes.} \label{fig-variation-textbox} \end{figure} Second, and even more interesting, was the observation that while selections made on the combo box with the mouse exhibited similar behaviour to the text box, the behaviour on the touch screen overlay was the opposite (although less pronounced), as shown in Figure~\ref{fig-variation-combobox}. That is, selections of combo boxes on the left side of the touch screen overlay had greater variation than selections made on the right. \begin{figure} \centering \includegraphics{variation-combo-mouse} \includegraphics{variation-combo-touch} \caption{Standard deviation of final selection coordinates for the combo box, averaged across all target sizes.} \label{fig-variation-combobox} \end{figure} These effects were most pronounced for the large size of both the text box and the combo box. The variation of selection coordinates for the smaller targets (the button and check box) was consistent across both the mouse and touch screen overlay and for all target sizes. We can only speculate as to the reasons for this variation. In the case of the combo box, one possibility is its asymmetrical appearance compared to the other target types, which may encourage participants to try to click specifically on the drop-down arrow of the combo box, rather than treating the entire combo box as a target (this could also be another factor in the slow movement times for this target type). However, this does not explain the variation between left and right sides of the screen, nor why the same behaviour was observed with the completely symmetrical text box. Another possibility is the handedness of the participants, which in the case of a touch screen might affect how difficult it is to select targets on different sides of the screen. Unfortunately we did not ask participants whether they were right- or left-handed, and thus can draw no conclusions on this point. \section{Conclusion} \label{sec-conclusions} The goal of our study was to assess the efficacy of a touch screen overlay compared to a mouse, when selecting the typical GUI targets commonly presented to users in desktop information systems. This was achieved by an experiment measuring movement time, throughput and error rate for various combinations of target type, size, angle and distance. Comfort and user satisfaction were assessed by means of a questionnaire. The results showed that the touch screen overlay was both slower and less accurate than the mouse. The touch screen overlay was found to have reasonable performance with large GUI items but poor performance with smaller GUI items. The touch screen overlay did have comparable movement times to the mouse for medium and large sized targets. Throughput did not vary across device or target size but did vary across target type. Both selection devices had the same user preference except with respect to the smallest target type (check boxes), in which the mouse had a higher preference. The mouse was rated easier to make accurate selections with than the touch screen overlay. The touch screen overlay also had worse arm, wrist and finger fatigue compared to the mouse. From these results we can conclude that the mouse had higher user satisfaction than a touch screen. An unusual variation in final selection coordinates was noted for both text boxes and combo boxes. Further studies are required to establish why this variation occurs. In general we can conclude that a touch screen overlay with no external device (e.g., a pen) is not an effective selection device for targets with dimensions of \unit[4]{mm} or smaller. When designing interfaces that will be used with a touch screen overlay, selection within the interface will be more efficient if the GUI items are larger than \unit[4]{mm}. Although the results showed that the touch screen overlay was not efficient and usable for selecting GUI items with a size of \unit[4]{mm} or less, this may not be the case when a pen or some external device is used in conjunction with the touch screen overlay. In general there seems to be a lack of research in device assessment of touch screen overlays with pens or other external devices. Further testing on touch screen overlays used with an external device such as a pen may well show that a touch screen overlay is adequate and efficient for selecting small GUI items. % The Appendices part is started with the command \appendix; % appendix sections are then done as normal sections % \appendix % \section{} % \label{} % Bibliographic references with the natbib package: % Parenthetical: \citep{Bai92} produces (Bailyn 1992). % Textual: \citet{Bai95} produces Bailyn et al. (1995). % An affix and part of a reference: % \citep[e.g.][Ch. 2]{Bar76} % produces (e.g. Barnes et al. 1976, Ch. 2). \bibliographystyle{elsart-harv} \bibliography{Gleeson_paper} % \begin{thebibliography}{} % \bibitem[Names(Year)]{label} or \bibitem[Names(Year)Long names]{label}. % (\harvarditem{Name}{Year}{label} is also supported.) % Text of bibliographic item % \bibitem[]{} % % \end{thebibliography} \end{document}

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\documentclass[a4paper]{article}

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\title{\textbf{Assessing the efficacy of a touch screen overlay as a selection
device for typical GUI targets}}
\author{M.\ GLEESON\dag, N.\ STANGER\thanks{Corresponding author. Email nstanger@infoscience.otago.ac.nz.} \dag\ and E.\ FERGUSON\ddag}
\date{\dag Department of Information Science, \\
	\ddag Department of Human Nutrition, \\
	University of Otago, Dunedin, New Zealand}

\begin{document}

\renewcommand{\baselinestretch}{2}

\maketitle

\begin{quotation}
	\noindent In this paper we investigate the efficacy of a touch
	screen overlay compared to a mouse, when selecting typical graphical
	user interface (GUI) items in a desktop information system. A series
	of tests were completed involving multi-directional point and select
	tasks, and the results for both devices compared. The results showed
	that the touch screen overlay was not suitable for selecting GUI
	targets smaller than \unit[4]{mm}. The touch screen overlay was
	slower and had a higher error rate than the mouse, but there was no
	significant difference in throughput. Testers rated the mouse easier
	to use and to make accurate selections, while the touch screen
	overlay resulted in greater arm, wrist and finger fatigue. These
	results suggest that a touch screen overlay is not a practical
	selection device for desktop interfaces with small GUI targets.
\end{quotation}

\begin{quotation}
	\noindent \emph{Keywords:} Touch screen overlay; Mouse; Selection
	device; Fitts' Law; Performance evaluation; GUI item
\end{quotation}

% main text
\newcommand{\ISOnine}{ISO 9241-9}

\section{Introduction}
\label{sec-introduction}

Most modern information systems that run on desktop personal computers
are designed to be used with a keyboard and mouse. While the combination
of keyboard and mouse is the accepted method of interaction with such
systems it does not necessarily suit all information systems.
Information systems with limited data entry may be more usable through
the use of a keyboard and touch screen. Touch screens require less
physical space and thus the workstation environment in an office setting
could be improved, allocating more space to the user and less to the
computer.

The purpose of this paper is to investigate how effective a touch screen
overlay is compared to a mouse, when selecting typical graphical user
interface (GUI) items. The target types tested were buttons, check
boxes, combo boxes and text boxes, which are typical of those found in
an interface for an information system. Each target type was tested at
three different sizes (see Section~\ref{sec-GUI}).

A typical touch screen device comprises a monitor enhanced with hardware
for detecting touches on the screen surface. An alternative approach is
to attach a discrete touch-sensitive surface to an existing conventional
monitor. \citet{Sear-A-1991-IJMMS} have previously assessed the efficacy
of specialised touch screen hardware, but there appears to have been
little research into the efficacy of touch screen overlays. We therefore
chose to compare the performance of a touch screen overlay with that of
a mouse.

The testing occurred in the context of a research project undertaken by
the Department of Human Nutrition at the University of Otago. This
project aims to improve complementary feeding diets for toddlers in New
Zealand, by designing a computer program to help formulate
population-specific food-based dietary guidelines for this high risk
group. The program, which is based on a previously published linear
programming approach \citep{Ferg-EL-2004-Nutrition}, is a
decision-making tool, designed specifically for nutrition programme
planners to assist them in selecting appropriate and improved home-based
complementary foods.

% do we need this?
The remainder of the paper discusses our experiment and the results
obtained. Section~\ref{sec-GUI} briefly describes the types of targets
used in the experiment, while Section~\ref{sec-evaluation} describes the
measures used to evaluate the selection devices. The experimental design
is described in Section~\ref{sec-method}. Section~\ref{sec-analysis}
describes how the data were analysed, and Section~\ref{sec-results}
presents the results of the experiment. Our conclusions are presented in
Section~\ref{sec-conclusions}.

\section{GUI targets}
\label{sec-GUI}

Since the 1980's much work has gone into developing human computer
interface guidelines. Today's interfaces are made up of a combination of
different targets that include text boxes, check boxes, combo boxes,
list boxes, buttons, labels, tool bars, etc. \citet{Sear-A-1991-IJMMS}
showed that touch screens can be successfully used as a selection device
and can have advantages over a mouse, even for small targets. These
results were, however, based on selecting arbitrary shapes and not the
typical targets found in modern GUIs.

To accurately test the performance of each selection device within the
experiment, three different sizes of GUI target were used, corresponding
to small, medium and large GUI items. As our experiment took place in a
Windows environment, we would have preferred to base these sizes on
Microsoft's user interface guidelines. However, Microsoft's guidelines
specify only a single standard size for most GUI items \citep[pp.\
448--450]{MS-1999-UI}. \citeauthor{Appl-2004-HIG}'s
\citeyearpar{Appl-2004-HIG} human interface guidelines specify three
standard sizes (mini, small and large), but these proved to be rather
small in our Windows-based testing environment. We therefore adjusted
Apple's three sizes such that the ``small'' size was consistent with
Microsoft's guidelines. The resultant target sizes are listed in
Table~\ref{tab-target-sizes}. A screen resolution of \unit[81]{DPI} was
assumed.

\begin{table}[ht]
	\caption{Target sizes (width $\times$ height) used in the experiment.}
	\label{tab-target-sizes}
	\begin{tabular}{llll}
		\hline
		\textbf{Target type}	&	\textbf{Large}							&	\textbf{Medium}							&	\textbf{Small}	\\
		\hline
		Text box				&	$\unit[63]{mm} \times \unit[11]{mm}$	&	$\unit[55]{mm} \times \unit[8]{mm}$	&	$\unit[47]{mm} \times \unit[6]{mm}$	\\
		Combo box				&	$\unit[63]{mm} \times \unit[11]{mm}$	&	$\unit[55]{mm} \times \unit[8]{mm}$	&	$\unit[47]{mm} \times \unit[6]{mm}$	\\
		Button					&	$\unit[28]{mm} \times \unit[13]{mm}$	&	$\unit[24]{mm} \times \unit[9]{mm}$	&	$\unit[17]{mm} \times \unit[6]{mm}$	\\
		Check box$^{a}$		&	$\unit[9]{mm} \times \unit[9]{mm}$	&	$\unit[6]{mm} \times \unit[6]{mm}$	&	$\unit[4]{mm} \times \unit[4]{mm}$	\\
		\hline
	\end{tabular}
	
	{\footnotesize $^{a}$This refers to the size of the check box itself, not the associated text label.}
\end{table}

\section{Evaluation methods}
\label{sec-evaluation}

Each selection device was assessed using a combination of performance
and comfort measures. The performance measures were primarily taken from
the \ISOnine\ standard \citep{ISO-2000-9241-9}, while the comfort
measures were derived from a questionnaire administered to test
participants.

\subsection{Performance}
\label{sec-evaluation-performance}

ISO 9241 specifies standards for the ergonomic design of office
computing environments. Part 9 of this standard describes different
tests that can be used to evaluate one or more pointing devices
\citep{ISO-2000-9241-9}. The standard describes a serial point and
select task and recognises a dependent measure used with this test,
known as \emph{throughput}. The serial test comprises moving the cursor
back and forth between two targets using the pointing device and
selecting each target by pressing and releasing a button on the pointing
device. One disadvantage of this approach is that only two targets are
used in the test and therefore interactions between more than two
targets---which often occur in a typical information system
interface---are not studied.

\citet{Mack-IS-2001-EHCI} note that throughput is a very important
measure, as it reflects the efficiency of the user completing the task
and is a measure of both speed and accuracy. Throughput is calculated by
the formula $\mathit{throughput} = \mathit{ID}_{e} / \mathit{MT}$,
where $\mathit{MT}$ is the movement time in seconds (defined as the
time taken to successfully select a target) and $\mathit{ID}_{e}$ is
Fitts' \citeyearpar{Fitt-PM-1954-Law} \emph{index of difficulty}
measured in bits. Throughput is thus measured in bits per second (bps).

The index of difficulty is calculated by the formula $\mathit{ID}_{e} =
\log_{2}((D / W_{e}) + 1)$, where $D$ is the distance to the target
and $W_{e}$ is the \emph{effective width} of the target. The effective
width reflects spatial variability in a sequence of trials, and thus
differs from the actual width of the target. The effective width of a
target is calculated by the formula $W_{e} = 4.133 \times
\mathit{SD}_{x}$, where $\mathit{SD}_{x}$ is the standard deviation
in the selection coordinates measured along the path to target $x$.

\ISOnine\ does not provide any guidance on the range of index of
difficulty values to use in testing. \citet{Doug-SA-1999-CHI} recommend
using a range from 2 to 6 bits. They also recommend calculating the
\emph{error rate} as a separate dependent measure of accuracy. The
error rate is defined as the ratio of incorrect to correct selections
made on a target, so an error rate of 100\% implies that there were as
many errors made as correct selections. Error rate is not included in
\ISOnine, but has been used in several other studies
\citep{Sear-A-1991-IJMMS,Sear-A-1993-BIT,Hara-H-1996,Bend-G-1999-PhD,
Doug-SA-1999-CHI,Mack-IS-2001-EHCI,Po-BA-2004-CHI}. Computing both
throughput and error rate gives a more detailed performance analysis for
the selection device in question.

\subsection{Comfort}
\label{sec-evaluation-comfort}

ISO 9241-9 argues that to fully evaluate a selection device requires
assessment of user effort and comfort in addition to performance
measurements. Comfort is subjective and can be assessed by means of
questionnaires, while effort can be evaluated objectively by measuring
the biomechanical load on users as they use a device. Unfortunately,
such measurements require reasonably sophisticated equipment
\citep{Doug-SA-1999-CHI} that was not available to us. We therefore
omitted effort measurements from our experiment.

A questionnaire was used to assess comfort and user satisfaction for
each selection device in our experiment. The selection device assessment
questionnaire comprised sixteen questions, eight of which were taken
from the ISO ``Independent Questionnaire for Assessment of Comfort''
\citep{Doug-SA-1999-CHI}. The remaining eight questions related
specifically to the target types and target sizes that were tested. In
particular, the questionnaire aimed to assess the participants' comfort
in using the selection device, the difficulty in accurately selecting each
of the target types and the preferred size of each target type using the
selection device.

The responses to twelve of the questions were based on a five point
ordinal scale. The remaining four questions referred to the
participant's preferred size for each target type and were based on a
three point response corresponding to the target sizes tested---small,
medium and large (see Table~\ref{tab-target-sizes}). There was also a
space for participants to provide additional general feedback about the
testing process.

\subsection{Other considerations}
\label{sec-evaluation-other}

\citet{Doug-SA-1999-CHI} also note that \ISOnine\ does not take into
account any possible effects of learning, which can affect movement time
and accuracy. For example, \citet{Mack-IS-1991} found that the movement
times from the first of five testing sessions were significantly higher
than in later sessions. This can be explained as a result of learning
and shows that input device studies should take learning into account
and test for it; indeed, \citet{Doug-SA-1999-CHI} recommend applying a
repeated measures paradigm and testing for learning effects.

One interesting aspect of using typical GUI items as targets is the
variation in selection behaviour for different target types, compared to
earlier studies that used simple rectangular targets. The button, check
box and text box target types can be said to exhibit a ``one-step''
selection behaviour, because they require only single action (i.e., the
user clicks on them) in order to be selected. A combo box is different,
however, because it exhibits a ``two-step'' selection behaviour: first
the combo box must be selected in order to show the list of items, and
then an item must be selected from the displayed list, as illustrated in
Figure~\ref{fig-combo-box}. To complicate matters further, users may
execute this two-step behaviour using either a ``one-click'' or a
``two-click'' approach. In the former approach, the user clicks on the
combo box, drags down to the desired list item, then releases. In the
latter approach, the user clicks once on the combo box, then clicks
again on the desired list item. If the drop-down list were longer than
what could be displayed on screen, this could even lead to a
``multiple-click'' approach, where the user clicks multiple times on the
downward scroll arrow in the list. We have, however, not considered this
possibility in our experiment.

\begin{figure}[ht]
	\centering
	\includegraphics[scale=0.8]{combobox-step1}\quad\quad\quad
	\includegraphics[scale=0.8]{combobox-step2}
	\caption{The ``two-step'' action required to select a combo box.}
	\label{fig-combo-box}
\end{figure}

\section{Method}
\label{sec-method}

An experiment was carried out to test the effect of size for different
GUI target types with different selection devices. The experiment
involved participants completing a series of simple point and select
tasks. Small, medium and large sizes (see Table~\ref{tab-target-sizes})
were tested for combo boxes, text boxes, check boxes and buttons, using
either a touch screen overlay or a mouse. The test was
multi-directional, meaning the targets appeared in multiple directions
from the initial starting point. A variety of different sizes, angles
and distances were used for each target position.

The test itself comprised a screen containing a button in the centre and
a target for the participant to select as illustrated in
Figure~\ref{fig-test-environment}. When a participant clicked on the
centre ``Go'' button, a trial was started and a target appeared on the
screen. The trial ended when the participant successfully clicked the
target, which then disappeared. The time taken between clicking the
``Go'' button and successfully clicking on the target was recorded as
well as the number of errors made during the trial. The final
coordinates of the successful click on the target were recorded in order
to calculate the effective width of the target.

\begin{figure}
	\centering
 	\includegraphics[scale=0.5]{test-environment}
	\caption{Screenshot of the test environment with a target in the
	top left of the screen and the ``Go'' button in the centre.}
	\label{fig-test-environment}
\end{figure}

\subsection{Participants}
\label{sec-method-participants}

A participant sample size of twenty-four was used for the experiment.
Each participant was allocated to one of two groups with each group
using one selection device in testing. The allocation of groups was
based on the results of a questionnaire completed by each participant
prior to testing. The purpose of the pre-test questionnaire was to
establish the level of computer, mouse and touch screen experience of
each participant. Participants were then allocated to a selection device
group based on which device they had the least experience with.

Due to the testing being done within the nutrition program environment
mentioned in Section~\ref{sec-introduction}, the participants were all
nutritionists (i.e., typical users of the program). There were
twenty-one female and three male participants, all with a university
level of education. All participants were unpaid volunteers.

\subsection{Apparatus}
\label{sec-method-apparatus}

The test environment was implemented in Visual Basic.NET using Microsoft
Studio 2003, and is illustrated in Figure~\ref{fig-test-environment}.
During each test, data corresponding to the relevant measures (movement
time, number of errors and selection coordinates) were captured by the
software and automatically written to a Microsoft Excel worksheet.

The touch screen used in testing was a 17'' Magic Touch USB overlay
Model KTMT-1700-USB-M \citep{Keyt-2005-Touch}. This device uses a
take-off touch strategy, that is, a selection is not confirmed until the
user's finger is removed from the screen. An important property of touch
screen overlays is that they are placed over a conventional monitor and
the touch surface is thus not coincident with the display surface. This
can cause a slight discrepancy or parallax effect between where the user
touches the overlay and where the cursor is positioned on the screen.

The touch screen overlay was fitted to a Dell 15'' Flat Panel Model
E151FPb monitor. A flat panel monitor was chosen because it was noticed
during pre-testing that typical CRT monitors with curved screens
produced a variable gap between the overlay and the display surface,
thus potentially leading to a greater parallax effect than with a flat
display surface.

The mouse used in testing was a standard Dell PS/2 Optical Mouse Model
M071KC. Both devices were connected to a Dell Inspiron 7500 laptop
computer that ran the testing software.

\subsection{Design}
\label{sec-method-design}

A mixed design experiment was used with the selection device as a
between-subjects factor. The independent (between-subject) variables
were:
\begin{itemize}

\item Target type (text box, combo box, button and check box)

\item Target size (large, medium and small---see
	Table~\ref{tab-target-sizes})

\item Target distance (\unit[40]{mm}, \unit[80]{mm} and
	\unit[160]{mm}---see below)

\item Target angle ($45^{\circ}$, $135^{\circ}$, $225^{\circ}$
	and $315^{\circ}$---see below)

\item Trial (1 to 144)

\item Block (1 to 6)

\end{itemize}
The dependent variables within the experiment were throughput, movement
time and error rate.

The entire test was divided into six blocks. Each block contained every
possible combination of target type (four combinations), size (three
combinations), angle from initial starting point (four combinations) and
distance from initial starting point (three combinations). Consequently
there were 144 trials in each block and the entire experiment per
participant comprised a total of 864 trials (six blocks of 144 trials
each). Combinations of target type, distance and angle were presented to
the participant in random sequence with no repetition. Target size was
deliberately set to large for the first forty-eight trials in each block,
followed by medium for the next forty-eight trials, and finally small for
the remaining trials, in order to compensate for learning effects.

The combination of distance and angle from the initial starting point
yielded twelve possible target positions for each trial, as illustrated
in Figure~\ref{fig-target-positions}. Three distances were used that
represented target positions ranging from close to the initial starting
point to very far away from the initial starting point. Four angles were
chosen so that targets could be tested in ninety degree blocks and to
provide a good range of screen positions for the target. The first angle
was set to $45^{\circ}$ with $90^{\circ}$ increments thereafter, in
order to mimic real life user interface target selection, where targets
are situated in different areas of the screen and therefore selections
are made in multiple directions that are neither simply horizontal nor
vertical.

\begin{figure}
	\centering
	\includegraphics{target-positions}
	\caption{Positions of targets tested. The black box represents the
	initial starting point and the rounded rectangles represent the
	target positions.}
	\label{fig-target-positions}
\end{figure}

The index of difficulty ($\mathit{ID}_{e}$) was ascertained for each
possible task using the combination of distance and non-adjusted target
width. This showed that the test had a range of $\mathit{ID}_{e}$
values from \unit[0.7]{bits} (\unit[63]{mm} width and \unit[160]{mm}
distance) to \unit[5.4]{bits} (\unit[4]{mm} width and \unit[40]{mm}
distance). It is important to note that the combo box distance values
were adjusted in these calculations to reflect the two-step selection
behaviour of this target type (as discussed in
Section~\ref{sec-evaluation-other}). That is, we need to consider not
just the distance from the initial starting point to the target, but
also the extra distance from the main combo box to the selected list
item. In our experiment, participants were told to always select the
third list item in combo boxes (as illustrated in
Figure~\ref{fig-combo-box}), so the adjusted distance for a combo box
was equal to the normal distance from the initial starting point to the
target, \emph{plus} the additional distance to the third list item.
Additional data about the selections made on combo boxes were recorded
in order to account for the selection approach of the participant,
whether it be a ``one-click'' or ``two-click'' approach.

\subsection{Procedure}
\label{sec-method-procedure}

The participant was given an introduction to the test by the research
observer, which included a brief summary of the aims of the study and
what the test involved. The participant was also given an instruction
sheet that they had access to throughout the duration of the test. After
reading the instruction sheet the participant had the opportunity to ask
questions or raise any issues.

Participants were instructed to complete each block of trials as quickly
as possible without losing accuracy. Participants were given the
opportunity to rest for as long as they wished between blocks. It was
made clear to participants that a task was only complete once the target
was successfully selected.

Before the test began, participants were instructed to complete a
practice session involving fifteen random trials of the same point and
select tasks used in the test. This brought all participants up to a
minimal level of experience with their selection device. This also meant
that each participant knew how to correctly select each target type
including the combo box.

At the conclusion of the test the participant was asked to fill out a
questionnaire regarding comfort and user satisfaction with the selection
device used.

\section{Analysis}
\label{sec-analysis}

The data collected from the software included movement time, error rate
and throughput and was used to evaluate selection device performance. A
mixed design repeated measures analysis of variance model (MANOVA) was
used for movement time and throughput to examine within subject
differences in target type and size, as well as between subject
differences in selection device. A Greenhouse and Geisser correction of
the F-ratio was used whenever the Mauchly's test results showed that
assumptions of sphericity were violated.

Post hoc tests, for multiple comparisons, were made using the Bonferroni
method. Due to the skew observed in the error rate data (see
Section~\ref{sec-results-learning}), inter-device differences in error
rates were assessed using the Mann-Whitney U Test.

The comfort questionnaire was based on a five point ordinal scale, where
five generally indicated a poor rating. Because of the small data size, a
Mann-Whitney (non-parametric) test was used.

All statistical analyses were performed using SPSS version 11.0. A
\emph{p}-value of $< 0.05$ was considered statistically significant.

\section{Results and discussion}
\label{sec-results}

\subsection{Adjusting for learning}
\label{sec-results-learning}

\citet{Doug-SA-1999-CHI} have shown that the effects of learning can
affect movement time and accuracy. They therefore recommend that input
device studies should apply a repeated measures paradigm and test for
learning effects.

From analysing the results of movement time and throughput over each
test block, it was clear for the combo box and check box target types
that learning occurred from the first to the second block with the touch
screen overlay, as seen in Figure~\ref{fig-movement-time-learning}. Due
to prior participant experience, no learning was observed with the
mouse. No learning occurred with the text box or button, most likely due
to their relatively large size and simple selection behaviour.

\begin{figure}
	\centering
	\includegraphics{combobox-learning}
	\includegraphics{checkbox-learning}
	\caption{Learning is displayed for movement time by selection device
	and test block for the combo box and check box.}
	\label{fig-movement-time-learning}
\end{figure}

Statistical analysis using a simple repeated measure ANOVA was carried
out on movement time for both the check box and combo box. For movement
time of the combo box, the effect of block $\times$ device was
significant $(F(1.549, 1335.219) = 4.373, p < 0.05)$. Helmhert
contrasts showed that the differences between blocks became
non-significant after block 1 $(p > 0.05)$, which implies that
learning occurred during block 1.

For movement time of the check box, the effect of block $\times$
device was significant $(F(1.608, 1385.960) = 4.763, p < 0.05)$.
Helmhert contrasts again showed that the differences between blocks
became non-significant after block 1 $(p > 0.05)$, implying that
learning occurred during block 1.

To account for learning with the combo and check box, results from block
6 only were used to calculate the movement time and throughput measures,
as the results from block 6 alone gave a good measure of performance.
However, the error rate results were highly skewed for both target
types, with two participants accounting for almost 90\% of the errors.
Error rates for the check box and combo box were therefore calculated
using results from all six test blocks.

\subsection{Movement time}
\label{sec-results-movement}

The results showed that the mouse had an overall movement time of
\unit[1.32]{s} across all target types compared to \unit[1.57]{s} for
the touch screen overlay. We can thus conclude that the touch screen
overlay was on average 1.2 times slower than the mouse. This is
interesting because \citet{Sear-A-1991-IJMMS} found that the movement
times for mouse and touch screen monitor were similar for rectangular
targets larger than \unit[2]{mm}. Therefore the nature of the two types
of touch screen (overlay versus monitor) may affect the movement time
associated with the type of touch screen. It is also likely that due to
the loss of accuracy found with the overlay during testing, the touch
screen monitor will have faster movement times compared to the touch
screen overlay.

The movement times for each target type showed that the text box had the
fastest movement time, followed by the button, the check box and the
combo box. These results are illustrated in
Figure~\ref{fig-movement-time} and are consistent with Fitts' Law
\citep{Fitt-PM-1954-Law}, in that the largest target (the text box) had
the fastest movement time. It may appear that the combo box results
violate Fitts' Law, as the combo box is the same size as the text box,
yet is over twice as slow. In this case however, the slow movement times
are not a function of the target size, but rather a result of the more
complex two-step behaviour required to successfully select a combo box
(which is not considered by Fitts' Law). The extra movement of selecting
an item from the drop-down list clearly dramatically increases the
movement time for the combo box. As the additional distance from the
main combo box area to the list item is relatively short, the
significant increase in movement time is therefore most likely due to
users making more errors.

\begin{figure}
	\centering
	\includegraphics{movement-time}
	\caption{Movement time by target type and device, averaged across
	all target sizes.}
	\label{fig-movement-time}
\end{figure}

The touch screen overlay was found to have similar movement time to the
mouse for the medium and large targets, but for the small targets, the
touch screen overlay was on average 1.5 times slower than the mouse. The
only time that the touch screen overlay was found to be faster than the
mouse was with the largest target type (the large text box), but the
difference was less than one percent.

The movement time for the small check box on the touch screen overlay
was about 2.7 times slower than that for the mouse. The small check box
was the smallest item tested, with dimensions of \unit[4]{mm} $\times$
\unit[4]{mm}. We can conclude that the touch screen overlay was not
efficient for selecting targets as small as \unit[4]{mm}. Compare this
with \citet{Sear-A-1991-IJMMS}, who showed that a touch screen monitor
has similar movement time to a mouse for targets as small as
\unit[2]{mm}. While a touch screen monitor can be used with targets as
small as \unit[2]{mm}, a touch screen overlay should only be used for
targets with a size of greater than \unit[4]{mm}. The results from the
error rate analysis also support this conclusion (see
Section~\ref{sec-results-error-rate}).

\subsection{Throughput}
\label{sec-results-throughput}

The average throughput for the mouse was \unit[1.242]{bps}, slightly
higher than the \unit[1.214]{bps} average throughput for the touch
screen overlay. The selection device by itself was shown not to have a
significant effect on throughput $(F(1, 22) = 0.02, p > 0.05)$.
Throughput did not vary for size but throughput did vary depending on
target type $(F(2.07, 45.55) = 4.77, p < 0.001)$, as shown in
Figure~\ref{fig-throughput}. Check boxes had the highest throughput rate
of \unit[1.967]{bps} (sd = 0.720). This is interesting as the check box
had the second worst movement time and the worst error rate. Upon
further investigation it was seen that the movement time for the check
box was in fact in the middle range of all targets, and due to its small
size it had a high index of difficulty. These two factors are the most
likely reason for the check box having such a high throughput rate.

\begin{figure}[ht]
	\centering
	\includegraphics{throughput}
	\caption{Throughput by target type and device, averaged across all
	target sizes.}
	\label{fig-throughput}
\end{figure}

The combo box had the worst average throughput of \unit[0.501]{bps} (sd
= 0.213). The index of difficulty was not very high for the combo box,
so its low throughput rate could be attributed to its high movement
time.

The average throughput rate of \unit[1.242]{bps} for the mouse is much
lower than that found by previous research. A study by
\citet{Doug-SA-1994-SIGCHI} showed that a mouse had a throughput rate of
\unit[4.15]{bps}. \citet{Mack-IS-1991} compared three devices (mouse,
tablet and trackball) using four target sizes (8, 16, 32 and 64 pixels)
over two different types of tasks (pointing and dragging), and found
that the throughput for the mouse was \unit[4.5]{bps}. This may indicate
that the level of selection difficulty in our experiment is higher than
in previous research. This could be due to the selection of GUI targets
instead of arbitrary rectangular targets.

\subsection{Error rate}
\label{sec-results-error-rate}

The average error rate for the mouse was only 2.7\% which is consistent
with previous studies. The touch screen overlay, on the other hand, had
an average error rate of 60.8\%. \citet{Sear-A-1991-IJMMS} found that a
touch screen monitor had an average error rate of 49\% but this was
across much smaller targets. This suggests that there is a loss of
accuracy when using a touch screen overlay as opposed to a touch screen
monitor.

The check box had a significantly high average error rate of 78.5\%
across all sizes and both devices; in particular, the small check box on
the touch screen overlay had an error rate of 393\%. The touch screen
overlay incurred the majority of the errors. For all sizes of the check
box the mouse produced an average error rate of 6.7\%, while the touch
screen overlay produced an average error rate of 178.5\%. The
distinguishing factor of the check box compared to the other target
types is its small size, so we can conclude from this that a touch
screen overlay is more inaccurate for selecting small targets
(\unit[4]{mm} or less).

The button and text box had much lower error rates than the check box
and combo box (as seen in Figure~\ref{fig-error-rate}). As the button
and text box also exhibited low movement times, we can conclude that
these two target types have very good overall performance.

\begin{figure}
	\centering
	\includegraphics{error-rate}
	\caption{Error rate by target type and device, averaged across all
	target sizes.}
	\label{fig-error-rate}
\end{figure}

Note that the error rate calculation for combo boxes assumes a
``two-click'' selection approach, as only two of the twenty-four
participants used the ``one-click'' approach. Both of these participants
used the mouse.

\subsection{Comfort}
\label{sec-results-comfort}

In terms of accurate pointing the mouse (2.083) was rated easier than
the touch screen overlay (3.000). These differences were statistically
significant $(p < 0.01)$. The responses regarding the question on
neck, wrist and arm fatigue showed that the touch screen overlay had a
high rating (4.083), whereas the mouse was rated in the midpoint range
(3.167). These differences were statistically significant $(p < 0.05)$.
The final question rated the overall difficulty in using the selection
device. The mouse (4.250) was rated easier to use than the touch screen
overlay (3.333). These differences were statistically significant $(p <
0.05)$.

Participants using the touch screen overlay rated both the text box and
button as easy to accurately select, with the large and medium sizes
being most preferred. This feedback is consistent with the data
collected in that the text box and button have low movement times and
low error rates (i.e., they are easy to accurately select). The combo
box was rated in the middle of the range, and the check box was rated as
very hard to select. Three quarters of the touch screen overlay
participants preferred to select large combo boxes and check boxes,
which is consistent with the high error rates and movement times
associated with these two target types on the touch screen overlay.

Participants using the mouse also rated the text box and button as easy
to accurately select, with the large and medium sizes being most
preferred. Both the combo box and check box were rated harder to select
than the button and text box with the check box having the worst rating.
As with the touch screen overlay, participants preferred large combo
boxes and check boxes.

In the general feedback, one participant noted the lack of arm support
when selecting targets at the top of the screen. This is an interesting
comment, because the nature of using a touch screen means the user's arm
might be raised off the desk, and thus be self-supporting when selecting
items towards the top of the screen.

Another suggestion was making the target change colour when the cursor
is located above it. This is a similar concept to that of interactive
rollover items commonly used in web pages. Auditory feedback has been
shown to affect speed and accuracy when making a selection
\citep{Bend-G-1999-PhD}, so it is likely that the visual feedback
received from GUI targets will affect the selection performance. All of
the target types tested provide some form of immediate visual feedback,
from the button being visually depressed to a tick appearing in the
check box. Further study is needed to assess how visual feedback affects
selection performance of GUI items and what is the most effective method of
providing feedback.

\subsection{Other findings}
\label{sec-results-other}

Two interesting patterns emerged when we calculated the standard
deviation of the final selection coordinates on the screen. First, when
selecting text boxes with the mouse, there was greater variation in
final selection coordinates on the right side of the screen
($45^{\circ}$ and $315^{\circ}$ target angles) than on the left side
of the screen ($90^{\circ}$ and $225^{\circ}$ target angles). This
behaviour was not apparent when selecting text boxes with the touch
screen overlay, as illustrated in Figure~\ref{fig-variation-textbox}.
This would mean that participants using the mouse were more careful when
making selections with text boxes on the left side of the screen than on
the right.

\begin{figure}
	\centering
	\includegraphics{variation-text-mouse}
	\includegraphics{variation-text-touch}
	\caption{Standard deviation of final selection coordinates for the
	text box, averaged across all target sizes.}
	\label{fig-variation-textbox}
\end{figure}

Second, and even more interesting, was the observation that while
selections made on the combo box with the mouse exhibited similar
behaviour to the text box, the behaviour on the touch screen overlay was
the opposite (although less pronounced), as shown in
Figure~\ref{fig-variation-combobox}. That is, selections of combo boxes
on the left side of the touch screen overlay had greater variation than
selections made on the right.

\begin{figure}
	\centering
	\includegraphics{variation-combo-mouse}
	\includegraphics{variation-combo-touch}
	\caption{Standard deviation of final selection coordinates for the
	combo box, averaged across all target sizes.}
	\label{fig-variation-combobox}
\end{figure}

These effects were most pronounced for the large size of both the text
box and the combo box. The variation of selection coordinates for the
smaller targets (the button and check box) was consistent across both
the mouse and touch screen overlay and for all target sizes.

We can only speculate as to the reasons for this variation. In the case
of the combo box, one possibility is its asymmetrical appearance
compared to the other target types, which may encourage participants to
try to click specifically on the drop-down arrow of the combo box,
rather than treating the entire combo box as a target (this could also
be another factor in the slow movement times for this target type).
However, this does not explain the variation between left and right
sides of the screen, nor why the same behaviour was observed with the
completely symmetrical text box.

Another possibility is the handedness of the participants, which in the
case of a touch screen might affect how difficult it is to select
targets on different sides of the screen. Unfortunately we did not ask
participants whether they were right- or left-handed, and thus can draw
no conclusions on this point.

\section{Conclusion}
\label{sec-conclusions}

The goal of our study was to assess the efficacy of a touch screen
overlay compared to a mouse, when selecting the typical GUI targets
commonly presented to users in desktop information systems. This was
achieved by an experiment measuring movement time, throughput and error
rate for various combinations of target type, size, angle and distance.
Comfort and user satisfaction were assessed by means of a questionnaire.

The results showed that the touch screen overlay was both slower and
less accurate than the mouse. The touch screen overlay was found to have
reasonable performance with large GUI items but poor performance with
smaller GUI items. The touch screen overlay did have comparable movement
times to the mouse for medium and large sized targets. Throughput did
not vary across device or target size but did vary across target type.
Both selection devices had the same user preference except with respect
to the smallest target type (check boxes), in which the mouse had a
higher preference. The mouse was rated easier to make accurate
selections with than the touch screen overlay. The touch screen overlay
also had worse arm, wrist and finger fatigue compared to the mouse. From
these results we can conclude that the mouse had higher user
satisfaction than a touch screen.

An unusual variation in final selection coordinates was noted for both
text boxes and combo boxes. Further studies are required to establish
why this variation occurs.

In general we can conclude that a touch screen overlay with no external
device (e.g., a pen) is not an effective selection device for targets
with dimensions of \unit[4]{mm} or smaller. When designing interfaces
that will be used with a touch screen overlay, selection within the
interface will be more efficient if the GUI items are larger than
\unit[4]{mm}.

Although the results showed that the touch screen overlay was not
efficient and usable for selecting GUI items with a size of \unit[4]{mm}
or less, this may not be the case when a pen or some external device is
used in conjunction with the touch screen overlay. In general there
seems to be a lack of research in device assessment of touch screen
overlays with pens or other external devices. Further testing on touch
screen overlays used with an external device such as a pen may well show
that a touch screen overlay is adequate and efficient for selecting
small GUI items.

% The Appendices part is started with the command \appendix;
% appendix sections are then done as normal sections
% \appendix

% \section{}
% \label{}

% Bibliographic references with the natbib package:
% Parenthetical: \citep{Bai92} produces (Bailyn 1992).
% Textual: \citet{Bai95} produces Bailyn et al. (1995).
% An affix and part of a reference:
%   \citep[e.g.][Ch. 2]{Bar76}
%   produces (e.g. Barnes et al. 1976, Ch. 2).

\bibliographystyle{elsart-harv}
\bibliography{Gleeson_paper}
% \begin{thebibliography}{}

% \bibitem[Names(Year)]{label} or \bibitem[Names(Year)Long names]{label}.
% (\harvarditem{Name}{Year}{label} is also supported.)
% Text of bibliographic item

% \bibitem[]{}
% 
% \end{thebibliography}

\end{document}

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.SUFFIXES: .eps .dvi .ps .bbl .bib .tex .plo .tif .pdf SHELL=/bin/sh GRAPHICS:=test-environment.eps target-positions.eps \ throughput.eps movement-time.eps error-rate.eps \ combobox-learning.eps checkbox-learning.eps \ combobox-step1.eps combobox-step2.eps \ variation-text-mouse.eps variation-text-touch.eps \ variation-combo-mouse.eps variation-combo-touch.eps Gleeson_paper.pdf: Gleeson_paper.ps Gleeson_paper.ps: Gleeson_paper.dvi Gleeson_paper.dvi: Gleeson_paper.tex Gleeson_paper.bib $(GRAPHICS) latex $< bibtex $* latex $< latex $< test-screenshot.eps: test-screenshot.tif throughput.eps: barchart.plo ploticus -eps -tightcrop -o $@ $< yrange="0 2.25" ystubfmt="%2.1f" ylabel="Throughput (bps)" field=throughput movement-time.eps: barchart.plo ploticus -eps -tightcrop -o $@ $< yrange="0 2.25" ystubfmt="%2.1f" ylabel="Movement time (s)" field=movement_time error-rate.eps: barchart.plo ploticus -eps -tightcrop -o $@ $< yrange="0 155" ystubfmt="%g" ylabel="Error rate (%)" field=error_rate combobox-learning.eps: linechart.plo ploticus -eps -tightcrop -o $@ $< field1=combo_mouse_move field2=combo_touch_move label1=Mouse label2=Touch checkbox-learning.eps: linechart.plo ploticus -eps -tightcrop -o $@ $< field1=check_mouse_move field2=check_touch_move label1=Mouse label2=Touch variation-text-mouse.eps: variation.plo ploticus -eps -tightcrop -o $@ $< device=mouse target=text variation-text-touch.eps: variation.plo ploticus -eps -tightcrop -o $@ $< device=touch target=text variation-combo-mouse.eps: variation.plo ploticus -eps -tightcrop -o $@ $< device=mouse target=combo variation-combo-touch.eps: variation.plo ploticus -eps -tightcrop -o $@ $< device=touch target=combo clean: rm -f .aux .bbl .blg .log .dvi .ps %.pdf: %.ps ps2pdf -dNOCACHE $< $@ %.ps: %.dvi dvips -o $@ $< %.dvi: %.tex latex $< latex $< %.eps: %.tif convert $< $@

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Gleeson_2005/Makefile 0 → 100644

.SUFFIXES: .eps .dvi .ps .bbl .bib .tex .plo .tif .pdf

SHELL=/bin/sh

GRAPHICS:=test-environment.eps target-positions.eps \
	throughput.eps movement-time.eps error-rate.eps \
	combobox-learning.eps checkbox-learning.eps \
	combobox-step1.eps combobox-step2.eps \
	variation-text-mouse.eps variation-text-touch.eps \
	variation-combo-mouse.eps variation-combo-touch.eps

Gleeson_paper.pdf: Gleeson_paper.ps

Gleeson_paper.ps: Gleeson_paper.dvi

Gleeson_paper.dvi: Gleeson_paper.tex Gleeson_paper.bib $(GRAPHICS)
	latex $<
	bibtex $*
	latex $<
	latex $<

test-screenshot.eps: test-screenshot.tif

throughput.eps: barchart.plo
	ploticus -eps -tightcrop -o $@ $< yrange="0 2.25" ystubfmt="%2.1f" ylabel="Throughput (bps)" field=throughput

movement-time.eps: barchart.plo
	ploticus -eps -tightcrop -o $@ $< yrange="0 2.25" ystubfmt="%2.1f" ylabel="Movement time (s)" field=movement_time

error-rate.eps: barchart.plo
	ploticus -eps -tightcrop -o $@ $< yrange="0 155" ystubfmt="%g" ylabel="Error rate (%)" field=error_rate

combobox-learning.eps: linechart.plo
	ploticus -eps -tightcrop -o $@ $< field1=combo_mouse_move field2=combo_touch_move label1=Mouse label2=Touch

checkbox-learning.eps: linechart.plo
	ploticus -eps -tightcrop -o $@ $< field1=check_mouse_move field2=check_touch_move label1=Mouse label2=Touch

variation-text-mouse.eps: variation.plo
	ploticus -eps -tightcrop -o $@ $< device=mouse target=text

variation-text-touch.eps: variation.plo
	ploticus -eps -tightcrop -o $@ $< device=touch target=text

variation-combo-mouse.eps: variation.plo
	ploticus -eps -tightcrop -o $@ $< device=mouse target=combo

variation-combo-touch.eps: variation.plo
	ploticus -eps -tightcrop -o $@ $< device=touch target=combo

clean:
	rm -f *.aux *.bbl *.blg *.log *.dvi *.ps

%.pdf: %.ps
	ps2pdf -dNOCACHE $< $@

%.ps: %.dvi
	dvips -o $@ $<

%.dvi: %.tex
	latex $<
	latex $<

%.eps: %.tif
	convert $< $@

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#musthave yrange #musthave ylabel #musthave field #musthave ystubfmt #proc settings units: cm #endproc #set field_mouse = @field "_mouse" #set field_touch = @field "_touch" #proc getdata delim: comma fieldnameheader: yes data: target_type, throughput_mouse, throughput_touch, movement_time_mouse, movement_time_touch, error_rate_mouse, error_rate_touch Text box, 0.86, 1.016, 0.98, 0.97, 0.233, 15.3 Button, 1.461, 1.551, 1.02, 1.05, 1.633, 13.03 Check box, 2.155, 1.779, 1.22, 2.06, 4.4, 152.5 Combo box, 0.492, 0.51, 2.07, 2.19, 4.667, 62.27 #proc areadef areaname: slide autowidth: 0.9 yrange: @yrange xrange: 0.25 4.75 #proc yaxis: stubs: inc stubformat: @ystubfmt stubdetails: size=10 label: @ylabel labeldetails: style=B size=10 adjust=-0.1,0 grid: color=gray(0.7) #proc xaxis: stubs: datafields=target_type stubdetails: style=B size=10 tics: none #proc bars lenfield: @field_mouse color: gray(0.3) showvalues: yes labeldetails: size=8 adjust=-0.15,0.1 cluster: 1 / 2 barwidth: 0.5 legendlabel: Mouse #proc bars lenfield: @field_touch color: white showvalues: yes labeldetails: size=8 adjust=0.15,0.1 cluster: 2 / 2 barwidth: 0.5 legendlabel: Touch #proc legend format: multiline location: min+1 max-0.9 textdetails: size=9 outlinecolors: yes

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Gleeson_2005/barchart.plo 0 → 100644

#musthave yrange
#musthave ylabel
#musthave field
#musthave ystubfmt

#proc settings
	units: cm
#endproc

#set field_mouse = @field "_mouse"
#set field_touch = @field "_touch"

#proc getdata
	delim: comma
	fieldnameheader: yes
	data:
		target_type, throughput_mouse, throughput_touch, movement_time_mouse, movement_time_touch, error_rate_mouse, error_rate_touch
		Text box, 0.86, 1.016, 0.98, 0.97, 0.233, 15.3
		Button, 1.461, 1.551, 1.02, 1.05, 1.633, 13.03
		Check box, 2.155, 1.779, 1.22, 2.06, 4.4, 152.5
		Combo box, 0.492, 0.51, 2.07, 2.19, 4.667, 62.27

#proc areadef
	areaname: slide
	autowidth: 0.9
	yrange: @yrange
	xrange: 0.25 4.75

#proc yaxis:
	stubs: inc
	stubformat: @ystubfmt
	stubdetails: size=10
	label: @ylabel
	labeldetails: style=B size=10 adjust=-0.1,0
	grid: color=gray(0.7)

#proc xaxis:
	stubs: datafields=target_type
	stubdetails: style=B size=10
	tics: none

#proc bars
	lenfield: @field_mouse
	color: gray(0.3)
	showvalues: yes
	labeldetails: size=8 adjust=-0.15,0.1
	cluster: 1 / 2
	barwidth: 0.5
	legendlabel: Mouse

#proc bars
	lenfield: @field_touch
	color: white
	showvalues: yes
	labeldetails: size=8 adjust=0.15,0.1
	cluster: 2 / 2
	barwidth: 0.5
	legendlabel: Touch

#proc legend
	format: multiline
	location: min+1 max-0.9
	textdetails: size=9
	outlinecolors: yes

Ignore Space Show notes View Gleeson_2005/combobox-selection.graffle 0 → 100644
<?xml version="1.0" encoding="UTF-8"?> <!DOCTYPE plist PUBLIC "-//Apple Computer//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd"> <plist version="1.0"> <dict> <key>CanvasColor</key> <dict> <key>w</key> <string>1</string> </dict> <key>ColumnAlign</key> <integer>1</integer> <key>ColumnSpacing</key> <real>36</real> <key>GraphDocumentVersion</key> <integer>3</integer> <key>GraphicsList</key> <array> <dict> <key>Class</key> <string>Group</string> <key>Graphics</key> <array> <dict> <key>Class</key> <string>Group</string> <key>Graphics</key> <array> <dict> <key>Bounds</key> <string>{{468.041, 128.751}, {9.85782, 6.468}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>ID</key> <integer>41</integer> <key>Shape</key> <string>VerticalTriangle</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Color</key> <dict> <key>b</key> <string>0</string> <key>g</key> <string>0</string> <key>r</key> <string>0</string> </dict> <key>GradientColor</key> <dict> <key>w</key> <string>1</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> </dict> </dict> <dict> <key>Bounds</key> <string>{{464.067, 123.751}, {17.8827, 18}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>ID</key> <integer>42</integer> <key>Shape</key> <string>Rectangle</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Color</key> <dict> <key>b</key> <string>0.85098</string> <key>g</key> <string>0.466667</string> <key>r</key> <string>0.0862745</string> </dict> <key>Draws</key> <string>NO</string> <key>FillType</key> <integer>2</integer> <key>GradientAngle</key> <real>90</real> <key>GradientColor</key> <dict> <key>b</key> <string>1</string> <key>g</key> <string>0.952941</string> <key>r</key> <string>0.694118</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>stroke</key> <dict> <key>Cap</key> <integer>0</integer> <key>Join</key> <integer>0</integer> </dict> </dict> <key>Text</key> <dict> <key>Align</key> <integer>0</integer> </dict> </dict> </array> <key>ID</key> <integer>40</integer> </dict> <dict> <key>Bounds</key> <string>{{340.2, 123.751}, {123.867, 18}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>ID</key> <integer>43</integer> <key>Shape</key> <string>Rectangle</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Draws</key> <string>NO</string> <key>GradientColor</key> <dict> <key>w</key> <string>0.666667</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> </dict> <key>Text</key> <dict> <key>Align</key> <integer>0</integer> </dict> </dict> <dict> <key>Bounds</key> <string>{{340.2, 125.432}, {43.75, 14.5671}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>ID</key> <integer>44</integer> <key>Shape</key> <string>Rectangle</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> 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<integer>0</integer> <key>Join</key> <integer>0</integer> </dict> </dict> <key>Text</key> <dict> <key>Align</key> <integer>0</integer> </dict> </dict> </array> <key>ID</key> <integer>32</integer> </dict> <dict> <key>Bounds</key> <string>{{141.75, 123.751}, {123.867, 18}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>ID</key> <integer>35</integer> <key>Shape</key> <string>Rectangle</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Draws</key> <string>NO</string> <key>GradientColor</key> <dict> <key>w</key> <string>0.666667</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> </dict> <key>Text</key> <dict> <key>Align</key> <integer>0</integer> </dict> </dict> <dict> <key>Bounds</key> <string>{{141.75, 125.432}, {43.75, 14.5671}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>ID</key> <integer>36</integer> <key>Shape</key> <string>Rectangle</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>stroke</key> <dict> <key>Color</key> <dict> <key>w</key> <string>1</string> </dict> <key>Draws</key> <string>NO</string> </dict> </dict> <key>Text</key> <dict> <key>Align</key> <integer>0</integer> <key>Text</key> <string>{\rtf1\mac\ansicpg10000\cocoartf102 {\fonttbl\f0\fswiss\fcharset77 Helvetica;} {\colortbl;\red255\green255\blue255;} \pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720 \f0\fs24 \cf1 Select}</string> </dict> </dict> </array> <key>ID</key> <integer>31</integer> </dict> <dict> <key>Bounds</key> <string>{{340.2, 169.75}, {141.75, 14}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>FitText</key> <string>Vertical</string> <key>ID</key> <integer>30</integer> <key>Shape</key> <string>Rectangle</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>stroke</key> <dict> <key>Draws</key> <string>NO</string> </dict> </dict> <key>Text</key> <dict> <key>Align</key> <integer>0</integer> <key>Text</key> <string>{\rtf1\mac\ansicpg10000\cocoartf102 {\fonttbl\f0\fswiss\fcharset77 Helvetica;} {\colortbl;\red255\green255\blue255;\red128\green128\blue128;} \pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\ql\qnatural \f0\fs24 \cf2 Item 3}</string> </dict> <key>TextPlacement</key> <integer>0</integer> </dict> <dict> <key>Bounds</key> <string>{{141.75, 141.75}, {141.75, 14}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>FitText</key> <string>Vertical</string> <key>ID</key> <integer>29</integer> <key>Shape</key> <string>Rectangle</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>stroke</key> <dict> <key>Draws</key> <string>NO</string> </dict> </dict> <key>Text</key> <dict> <key>Align</key> <integer>0</integer> <key>Text</key> <string>{\rtf1\mac\ansicpg10000\cocoartf102 {\fonttbl\f0\fswiss\fcharset77 Helvetica;} {\colortbl;\red255\green255\blue255;\red128\green128\blue128;} \pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\ql\qnatural \f0\fs24 \cf2 Select}</string> </dict> <key>TextPlacement</key> <integer>0</integer> </dict> </array> <key>GridInfo</key> <dict> <key>GridSpacing</key> <real>14.175000190734863</real> <key>MajorGridSpacing</key> <integer>10</integer> <key>ShowsGrid</key> <string>YES</string> <key>SnapsToGrid</key> <string>YES</string> </dict> <key>GuidesVisible</key> <string>YES</string> <key>HPages</key> <integer>1</integer> <key>ImageCounter</key> <integer>1</integer> <key>IsPalette</key> <string>NO</string> <key>Layers</key> <array> 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Ignore Space Show notes View

Gleeson_2005/combobox-selection.graffle 0 → 100644

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<!DOCTYPE plist PUBLIC "-//Apple Computer//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
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<dict>
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								<dict>
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									<key>Color</key>
									<dict>
										<key>b</key>
										<string>0.85098</string>
										<key>g</key>
										<string>0.466667</string>
										<key>r</key>
										<string>0.0862745</string>
									</dict>
									<key>Draws</key>
									<string>NO</string>
									<key>FillType</key>
									<integer>2</integer>
									<key>GradientAngle</key>
									<real>90</real>
									<key>GradientColor</key>
									<dict>
										<key>b</key>
										<string>1</string>
										<key>g</key>
										<string>0.952941</string>
										<key>r</key>
										<string>0.694118</string>
									</dict>
								</dict>
								<key>shadow</key>
								<dict>
									<key>Draws</key>
									<string>NO</string>
								</dict>
								<key>stroke</key>
								<dict>
									<key>Cap</key>
									<integer>0</integer>
									<key>Join</key>
									<integer>0</integer>
								</dict>
							</dict>
							<key>Text</key>
							<dict>
								<key>Align</key>
								<integer>0</integer>
							</dict>
						</dict>
					</array>
					<key>ID</key>
					<integer>32</integer>
				</dict>
				<dict>
					<key>Bounds</key>
					<string>{{141.75, 123.751}, {123.867, 18}}</string>
					<key>Class</key>
					<string>ShapedGraphic</string>
					<key>ID</key>
					<integer>35</integer>
					<key>Shape</key>
					<string>Rectangle</string>
					<key>Style</key>
					<dict>
						<key>fill</key>
						<dict>
							<key>Draws</key>
							<string>NO</string>
							<key>GradientColor</key>
							<dict>
								<key>w</key>
								<string>0.666667</string>
							</dict>
						</dict>
						<key>shadow</key>
						<dict>
							<key>Draws</key>
							<string>NO</string>
						</dict>
					</dict>
					<key>Text</key>
					<dict>
						<key>Align</key>
						<integer>0</integer>
					</dict>
				</dict>
				<dict>
					<key>Bounds</key>
					<string>{{141.75, 125.432}, {43.75, 14.5671}}</string>
					<key>Class</key>
					<string>ShapedGraphic</string>
					<key>ID</key>
					<integer>36</integer>
					<key>Shape</key>
					<string>Rectangle</string>
					<key>Style</key>
					<dict>
						<key>fill</key>
						<dict>
							<key>Color</key>
							<dict>
								<key>w</key>
								<string>0.5</string>
							</dict>
						</dict>
						<key>shadow</key>
						<dict>
							<key>Draws</key>
							<string>NO</string>
						</dict>
						<key>stroke</key>
						<dict>
							<key>Color</key>
							<dict>
								<key>w</key>
								<string>1</string>
							</dict>
							<key>Draws</key>
							<string>NO</string>
						</dict>
					</dict>
					<key>Text</key>
					<dict>
						<key>Align</key>
						<integer>0</integer>
						<key>Text</key>
						<string>{\rtf1\mac\ansicpg10000\cocoartf102
{\fonttbl\f0\fswiss\fcharset77 Helvetica;}
{\colortbl;\red255\green255\blue255;}
\pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720

\f0\fs24 \cf1 Select}</string>
					</dict>
				</dict>
			</array>
			<key>ID</key>
			<integer>31</integer>
		</dict>
		<dict>
			<key>Bounds</key>
			<string>{{340.2, 169.75}, {141.75, 14}}</string>
			<key>Class</key>
			<string>ShapedGraphic</string>
			<key>FitText</key>
			<string>Vertical</string>
			<key>ID</key>
			<integer>30</integer>
			<key>Shape</key>
			<string>Rectangle</string>
			<key>Style</key>
			<dict>
				<key>fill</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
				<key>shadow</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
				<key>stroke</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
			</dict>
			<key>Text</key>
			<dict>
				<key>Align</key>
				<integer>0</integer>
				<key>Text</key>
				<string>{\rtf1\mac\ansicpg10000\cocoartf102
{\fonttbl\f0\fswiss\fcharset77 Helvetica;}
{\colortbl;\red255\green255\blue255;\red128\green128\blue128;}
\pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\ql\qnatural

\f0\fs24 \cf2 Item 3}</string>
			</dict>
			<key>TextPlacement</key>
			<integer>0</integer>
		</dict>
		<dict>
			<key>Bounds</key>
			<string>{{141.75, 141.75}, {141.75, 14}}</string>
			<key>Class</key>
			<string>ShapedGraphic</string>
			<key>FitText</key>
			<string>Vertical</string>
			<key>ID</key>
			<integer>29</integer>
			<key>Shape</key>
			<string>Rectangle</string>
			<key>Style</key>
			<dict>
				<key>fill</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
				<key>shadow</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
				<key>stroke</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
			</dict>
			<key>Text</key>
			<dict>
				<key>Align</key>
				<integer>0</integer>
				<key>Text</key>
				<string>{\rtf1\mac\ansicpg10000\cocoartf102
{\fonttbl\f0\fswiss\fcharset77 Helvetica;}
{\colortbl;\red255\green255\blue255;\red128\green128\blue128;}
\pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\ql\qnatural

\f0\fs24 \cf2 Select}</string>
			</dict>
			<key>TextPlacement</key>
			<integer>0</integer>
		</dict>
	</array>
	<key>GridInfo</key>
	<dict>
		<key>GridSpacing</key>
		<real>14.175000190734863</real>
		<key>MajorGridSpacing</key>
		<integer>10</integer>
		<key>ShowsGrid</key>
		<string>YES</string>
		<key>SnapsToGrid</key>
		<string>YES</string>
	</dict>
	<key>GuidesVisible</key>
	<string>YES</string>
	<key>HPages</key>
	<integer>1</integer>
	<key>ImageCounter</key>
	<integer>1</integer>
	<key>IsPalette</key>
	<string>NO</string>
	<key>Layers</key>
	<array>
		<dict>
			<key>Lock</key>
			<string>NO</string>
			<key>Name</key>
			<string>Layer 1</string>
			<key>Print</key>
			<string>YES</string>
			<key>View</key>
			<string>YES</string>
		</dict>
	</array>
	<key>LayoutInfo</key>
	<dict>
		<key>AutoAdjust</key>
		<string>YES</string>
		<key>ChildOrdering</key>
		<integer>2</integer>
		<key>MagneticFieldCenter</key>
		<string>{0, 0}</string>
	</dict>
	<key>LinksVisible</key>
	<string>NO</string>
	<key>MagnetsVisible</key>
	<string>NO</string>
	<key>Orientation</key>
	<integer>2</integer>
	<key>PageBreaks</key>
	<string>YES</string>
	<key>PageSetup</key>
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	</data>
	<key>ReadOnly</key>
	<string>NO</string>
	<key>RowAlign</key>
	<integer>1</integer>
	<key>RowSpacing</key>
	<real>36</real>
	<key>SheetTitle</key>
	<string>Canvas 1</string>
	<key>SmartAlignmentGuidesActive</key>
	<string>YES</string>
	<key>SmartDistanceGuidesActive</key>
	<string>YES</string>
	<key>UseEntirePage</key>
	<true/>
	<key>VPages</key>
	<integer>1</integer>
	<key>WindowInfo</key>
	<dict>
		<key>CurrentSheet</key>
		<string>0</string>
		<key>Frame</key>
		<string>{{156, 0}, {574, 746}}</string>
		<key>ShowRuler</key>
		<true/>
		<key>ShowStatusBar</key>
		<true/>
		<key>VisibleRegion</key>
		<string>{{0, 0}, {543, 602}}</string>
		<key>Zoom</key>
		<string>1</string>
	</dict>
</dict>
</plist>

Ignore Space Show notes View Gleeson_2005/dissertation.doc 0 → 100644
Not supported

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Not supported

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Not supported

Ignore Space Show notes View Gleeson_2005/linechart.plo 0 → 100644
#musthave field1 #musthave field2 #musthave label1 #musthave label2 #proc settings units: cm #endproc #proc getdata delim: comma fieldnameheader: yes data: block, combo_mouse_move, combo_touch_move, check_mouse_move, check_touch_move 1, 2.194583333, 3.220412037, 1.31625463, 4.07544213 2, 2.149467593, 2.544164352, 1.301625, 2.293645833 3, 2.167368056, 2.374134259, 1.277354167, 2.002578704 4, 2.107435185, 2.729488426, 1.260993056, 3.019840278 5, 2.108939815, 2.52312037, 1.232050926, 1.88675463 6, 2.068502315, 2.191631944, 1.216634259, 2.059671296 #proc areadef #if @field1 = "combo_mouse_move" title: Combo box #else title: Check box #endif titledetails: size=10 style=B align=C areaname: standard yrange: 1 4.25 xrange: 0.5 6.5 autowidth: 0.33 autoheight: 0.66 #proc yaxis: stubs: inc stubformat: %2.1f stubdetails: size=10 label: Movement time (s) labeldetails: style=B size=10 adjust=-0.1,0 grid: color=gray(0.7) #proc xaxis: stubs: datafields=block stubdetails: size=10 label: Test block labeldetails: style=B size=10 adjust=0,-0.1 //adjust=-0.1,0 #proc lineplot xfield: block yfield: @field1 linedetails: color=black pointsymbol: shape=diamond linecolor=black fillcolor=black legendlabel: @label1 legendsampletype: line+symbol #proc lineplot xfield: block yfield: @field2 linedetails: color=gray(0.25) pointsymbol: shape=square linecolor=gray(0.25) fillcolor=gray(0.25) legendlabel: @label2 legendsampletype: line+symbol #proc legend format: multiline location: max-1.2 max-0.3 textdetails: size=10 seglen: 0.25 reverseorder: yes

Ignore Space Show notes View

Gleeson_2005/linechart.plo 0 → 100644

#musthave field1
#musthave field2
#musthave label1
#musthave label2

#proc settings
	units: cm
#endproc

#proc getdata
	delim: comma
	fieldnameheader: yes
	data:
		block, combo_mouse_move, combo_touch_move, check_mouse_move, check_touch_move
		1, 2.194583333, 3.220412037, 1.31625463, 4.07544213
		2, 2.149467593, 2.544164352, 1.301625, 2.293645833
		3, 2.167368056, 2.374134259, 1.277354167, 2.002578704
		4, 2.107435185, 2.729488426, 1.260993056, 3.019840278
		5, 2.108939815, 2.52312037, 1.232050926, 1.88675463
		6, 2.068502315, 2.191631944, 1.216634259, 2.059671296

#proc areadef
	#if @field1 = "combo_mouse_move"
		title: Combo box
	#else
		title: Check box
	#endif
	titledetails: size=10 style=B align=C
	areaname: standard
	yrange: 1 4.25
	xrange: 0.5 6.5
	autowidth: 0.33
	autoheight: 0.66

#proc yaxis:
	stubs: inc
	stubformat: %2.1f
	stubdetails: size=10
	label: Movement time (s)
	labeldetails: style=B size=10 adjust=-0.1,0
	grid: color=gray(0.7)

#proc xaxis:
	stubs: datafields=block
	stubdetails: size=10
	label: Test block
	labeldetails: style=B size=10 adjust=0,-0.1
	//adjust=-0.1,0

#proc lineplot
	xfield: block
	yfield: @field1
	linedetails: color=black
	pointsymbol: shape=diamond linecolor=black fillcolor=black
	legendlabel: @label1
	legendsampletype: line+symbol

#proc lineplot
	xfield: block
	yfield: @field2
	linedetails: color=gray(0.25)
	pointsymbol: shape=square linecolor=gray(0.25) fillcolor=gray(0.25)
	legendlabel: @label2
	legendsampletype: line+symbol

#proc legend
	format: multiline
	location: max-1.2 max-0.3
	textdetails: size=10
	seglen: 0.25
	reverseorder: yes

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<?xml version="1.0" encoding="UTF-8"?> <!DOCTYPE plist PUBLIC "-//Apple Computer//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd"> <plist version="1.0"> <dict> <key>CanvasColor</key> <dict> <key>w</key> <string>1</string> </dict> <key>ColumnAlign</key> <integer>1</integer> <key>ColumnSpacing</key> <real>36</real> <key>GraphDocumentVersion</key> <integer>3</integer> <key>GraphicsList</key> <array> <dict> <key>Bounds</key> <string>{{181, 164.125}, {48, 12}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>FitText</key> <string>YES</string> <key>ID</key> <integer>20</integer> <key>Shape</key> <string>Rectangle</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>stroke</key> <dict> <key>Draws</key> <string>NO</string> </dict> </dict> <key>Text</key> <dict> <key>Text</key> <string>{\rtf1\mac\ansicpg10000\cocoartf102 {\fonttbl\f0\fswiss\fcharset77 Helvetica;} {\colortbl;\red255\green255\blue255;} \pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\qc \f0\fs20 \cf0 160 mm}</string> </dict> </dict> <dict> <key>Bounds</key> <string>{{262.213, 249.025}, {42, 12}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>FitText</key> <string>YES</string> <key>ID</key> <integer>19</integer> <key>Shape</key> <string>Rectangle</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>stroke</key> <dict> <key>Draws</key> <string>NO</string> </dict> </dict> <key>Text</key> <dict> <key>Text</key> <string>{\rtf1\mac\ansicpg10000\cocoartf102 {\fonttbl\f0\fswiss\fcharset77 Helvetica;} {\colortbl;\red255\green255\blue255;} \pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\qc \f0\fs20 \cf0 \kerning1\expnd0\expndtw-5 40 mm}</string> </dict> </dict> <dict> <key>Bounds</key> <string>{{237.738, 220.75}, {42, 12}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>FitText</key> <string>YES</string> <key>ID</key> <integer>18</integer> <key>Shape</key> <string>Rectangle</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>stroke</key> <dict> <key>Draws</key> <string>NO</string> </dict> </dict> <key>Text</key> <dict> <key>Text</key> <string>{\rtf1\mac\ansicpg10000\cocoartf102 {\fonttbl\f0\fswiss\fcharset77 Helvetica;} {\colortbl;\red255\green255\blue255;} \pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\qc \f0\fs20 \cf0 80 mm}</string> </dict> </dict> <dict> <key>Class</key> <string>LineGraphic</string> <key>ID</key> <integer>17</integer> <key>Labels</key> <array> <dict> <key>Filled</key> <string>NO</string> <key>Label</key> <dict> <key>Align</key> <integer>0</integer> <key>Text</key> <string>{\rtf1\mac\ansicpg10000\cocoartf102 {\fonttbl\f0\fswiss\fcharset77 Helvetica;} {\colortbl;\red255\green255\blue255;} \pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\ql\qnatural \f0\fs20 \cf0 315\'bc}</string> </dict> <key>LabelVisible</key> <string>YES</string> <key>Offset</key> <real>6.875</real> <key>Orientation</key> <integer>2</integer> <key>Position</key> <real>0.7421875</real> </dict> </array> <key>Points</key> <array> <string>{290.5, 290.5}</string> <string>{396.9, 396.9}</string> </array> <key>Style</key> <dict> <key>stroke</key> <dict> <key>HeadArrow</key> <string>FilledArrow</string> <key>TailArrow</key> <string>0</string> </dict> </dict> <key>Tail</key> <dict> <key>ID</key> <integer>14</integer> </dict> </dict> <dict> <key>Class</key> <string>LineGraphic</string> <key>ID</key> <integer>16</integer> <key>Labels</key> <array> <dict> <key>Filled</key> <string>NO</string> <key>Label</key> <dict> <key>Align</key> <integer>0</integer> <key>Text</key> <string>{\rtf1\mac\ansicpg10000\cocoartf102 {\fonttbl\f0\fswiss\fcharset77 Helvetica;} {\colortbl;\red255\green255\blue255;} \pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\ql\qnatural \f0\fs20 \cf0 45\'bc}</string> </dict> <key>LabelVisible</key> <string>YES</string> <key>Offset</key> <real>-5.625</real> <key>Orientation</key> <integer>2</integer> <key>Position</key> <real>0.7421875</real> </dict> </array> <key>Points</key> <array> <string>{290.5, 276.325}</string> <string>{396.725, 170.1}</string> </array> <key>Style</key> <dict> <key>stroke</key> <dict> <key>HeadArrow</key> <string>FilledArrow</string> <key>TailArrow</key> <string>0</string> </dict> </dict> <key>Tail</key> <dict> <key>ID</key> <integer>14</integer> </dict> </dict> <dict> <key>Class</key> <string>LineGraphic</string> <key>ID</key> <integer>15</integer> <key>Labels</key> <array> <dict> <key>Filled</key> <string>NO</string> <key>Label</key> <dict> <key>Align</key> <integer>0</integer> <key>Text</key> <string>{\rtf1\mac\ansicpg10000\cocoartf102 {\fonttbl\f0\fswiss\fcharset77 Helvetica;} {\colortbl;\red255\green255\blue255;} \pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\ql\qnatural \f0\fs20 \cf0 225\'bc}</string> </dict> <key>LabelVisible</key> <string>YES</string> <key>Offset</key> <real>6.875</real> <key>Orientation</key> <integer>2</integer> <key>Position</key> <real>0.7421875</real> </dict> </array> <key>Points</key> <array> <string>{276.325, 290.5}</string> <string>{169.925, 396.9}</string> </array> <key>Style</key> <dict> <key>stroke</key> <dict> <key>HeadArrow</key> <string>FilledArrow</string> <key>TailArrow</key> <string>0</string> </dict> </dict> <key>Tail</key> <dict> <key>ID</key> <integer>14</integer> </dict> </dict> <dict> <key>Bounds</key> <string>{{276.325, 276.325}, {14.175, 14.175}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>ID</key> <integer>14</integer> <key>Shape</key> <string>Rectangle</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> </dict> </dict> <dict> <key>Class</key> <string>LineGraphic</string> <key>ID</key> <integer>13</integer> <key>Labels</key> <array> <dict> <key>Filled</key> <string>NO</string> <key>Label</key> <dict> <key>Align</key> <integer>0</integer> <key>Text</key> <string>{\rtf1\mac\ansicpg10000\cocoartf102 {\fonttbl\f0\fswiss\fcharset77 Helvetica;} {\colortbl;\red255\green255\blue255;} \pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\ql\qnatural \f0\fs20 \cf0 135\'bc}</string> </dict> <key>LabelVisible</key> <string>YES</string> <key>Offset</key> <real>-5.625</real> <key>Orientation</key> <integer>2</integer> <key>Position</key> <real>0.7421875</real> </dict> </array> <key>Points</key> <array> <string>{276.325, 276.325}</string> <string>{170.1, 170.1}</string> </array> <key>Style</key> <dict> <key>stroke</key> <dict> <key>HeadArrow</key> <string>FilledArrow</string> <key>TailArrow</key> <string>0</string> </dict> </dict> <key>Tail</key> <dict> <key>ID</key> <integer>14</integer> </dict> </dict> <dict> <key>Bounds</key> <string>{{297.1, 304.85}, {28.35, 14.175}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>HFlip</key> <string>YES</string> <key>ID</key> <integer>12</integer> <key>Shape</key> <string>RoundRect</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>stroke</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> </dict> <key>VFlip</key> <string>YES</string> </dict> <dict> <key>Bounds</key> <string>{{325.45, 333.2}, {28.35, 14.175}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>HFlip</key> <string>YES</string> <key>ID</key> <integer>11</integer> <key>Shape</key> <string>RoundRect</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>stroke</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> </dict> <key>VFlip</key> <string>YES</string> </dict> <dict> <key>Bounds</key> <string>{{382.15, 389.9}, {28.35, 14.175}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>HFlip</key> <string>YES</string> <key>ID</key> <integer>10</integer> <key>Shape</key> <string>RoundRect</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>stroke</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> </dict> <key>VFlip</key> <string>YES</string> </dict> <dict> <key>Bounds</key> <string>{{297.1, 248.15}, {28.35, 14.175}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>HFlip</key> <string>YES</string> <key>ID</key> <integer>9</integer> <key>Shape</key> <string>RoundRect</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>stroke</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> </dict> </dict> <dict> <key>Bounds</key> <string>{{325.45, 219.8}, {28.35, 14.175}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>HFlip</key> <string>YES</string> <key>ID</key> <integer>8</integer> <key>Shape</key> <string>RoundRect</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>stroke</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> </dict> </dict> <dict> <key>Bounds</key> <string>{{382.15, 163.1}, {28.35, 14.175}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>HFlip</key> <string>YES</string> <key>ID</key> <integer>7</integer> <key>Shape</key> <string>RoundRect</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>stroke</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> </dict> </dict> <dict> <key>Bounds</key> <string>{{240.4, 304.85}, {28.35, 14.175}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>ID</key> <integer>6</integer> <key>Shape</key> <string>RoundRect</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>stroke</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> </dict> <key>VFlip</key> <string>YES</string> </dict> <dict> <key>Bounds</key> <string>{{212.05, 333.2}, {28.35, 14.175}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>ID</key> <integer>5</integer> <key>Shape</key> <string>RoundRect</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>stroke</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> </dict> <key>VFlip</key> <string>YES</string> </dict> <dict> <key>Bounds</key> <string>{{155.35, 389.9}, {28.35, 14.175}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>ID</key> <integer>4</integer> <key>Shape</key> <string>RoundRect</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>stroke</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> </dict> <key>VFlip</key> <string>YES</string> </dict> <dict> <key>Bounds</key> <string>{{240.4, 248.15}, {28.35, 14.175}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>ID</key> <integer>3</integer> <key>Shape</key> <string>RoundRect</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>stroke</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> </dict> </dict> <dict> <key>Bounds</key> <string>{{212.05, 219.8}, {28.35, 14.175}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>ID</key> <integer>2</integer> <key>Shape</key> <string>RoundRect</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>stroke</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> </dict> </dict> <dict> <key>Bounds</key> <string>{{155.35, 163.1}, {28.35, 14.175}}</string> <key>Class</key> <string>ShapedGraphic</string> <key>ID</key> <integer>1</integer> <key>Shape</key> <string>RoundRect</string> <key>Style</key> <dict> <key>fill</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> <key>shadow</key> <dict> <key>Draws</key> <string>NO</string> </dict> <key>stroke</key> <dict> <key>Color</key> <dict> <key>w</key> <string>0.5</string> </dict> </dict> </dict> </dict> </array> <key>GridInfo</key> <dict> <key>GridSpacing</key> <real>7.0875000953674316</real> <key>MajorGridSpacing</key> <integer>20</integer> <key>ShowsGrid</key> <string>YES</string> <key>SnapsToGrid</key> <string>YES</string> </dict> <key>GuidesVisible</key> <string>YES</string> <key>HPages</key> <integer>1</integer> <key>ImageCounter</key> <integer>1</integer> <key>IsPalette</key> <string>NO</string> <key>Layers</key> <array> <dict> <key>Lock</key> <string>NO</string> <key>Name</key> <string>Layer 1</string> <key>Print</key> <string>YES</string> <key>View</key> <string>YES</string> </dict> </array> <key>LayoutInfo</key> <dict> <key>AutoAdjust</key> <string>YES</string> <key>ChildOrdering</key> <integer>2</integer> <key>MagneticFieldCenter</key> <string>{0, 0}</string> </dict> <key>LinksVisible</key> <string>NO</string> <key>MagnetsVisible</key> <string>NO</string> <key>Orientation</key> <integer>2</integer> <key>PageBreaks</key> <string>YES</string> <key>PageSetup</key> <data> 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<key>SmartAlignmentGuidesActive</key> <string>YES</string> <key>SmartDistanceGuidesActive</key> <string>YES</string> <key>UseEntirePage</key> <true/> <key>VPages</key> <integer>1</integer> <key>WindowInfo</key> <dict> <key>CurrentSheet</key> <string>0</string> <key>Frame</key> <string>{{294, 75}, {590, 927}}</string> <key>ShowRuler</key> <true/> <key>ShowStatusBar</key> <true/> <key>VisibleRegion</key> <string>{{143.5, 74.5}, {279.5, 391.5}}</string> <key>Zoom</key> <string>2</string> </dict> </dict> </plist>

Ignore Space Show notes View

Gleeson_2005/target-positions.graffle 0 → 100644

\f0\fs20 \cf0 160 mm}</string>
			</dict>
		</dict>
		<dict>
			<key>Bounds</key>
			<string>{{262.213, 249.025}, {42, 12}}</string>
			<key>Class</key>
			<string>ShapedGraphic</string>
			<key>FitText</key>
			<string>YES</string>
			<key>ID</key>
			<integer>19</integer>
			<key>Shape</key>
			<string>Rectangle</string>
			<key>Style</key>
			<dict>
				<key>fill</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
				<key>shadow</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
				<key>stroke</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
			</dict>
			<key>Text</key>
			<dict>
				<key>Text</key>
				<string>{\rtf1\mac\ansicpg10000\cocoartf102
{\fonttbl\f0\fswiss\fcharset77 Helvetica;}
{\colortbl;\red255\green255\blue255;}
\pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\qc

\f0\fs20 \cf0 \kerning1\expnd0\expndtw-5
40 mm}</string>
			</dict>
		</dict>
		<dict>
			<key>Bounds</key>
			<string>{{237.738, 220.75}, {42, 12}}</string>
			<key>Class</key>
			<string>ShapedGraphic</string>
			<key>FitText</key>
			<string>YES</string>
			<key>ID</key>
			<integer>18</integer>
			<key>Shape</key>
			<string>Rectangle</string>
			<key>Style</key>
			<dict>
				<key>fill</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
				<key>shadow</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
				<key>stroke</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
			</dict>
			<key>Text</key>
			<dict>
				<key>Text</key>
				<string>{\rtf1\mac\ansicpg10000\cocoartf102
{\fonttbl\f0\fswiss\fcharset77 Helvetica;}
{\colortbl;\red255\green255\blue255;}
\pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\qc

\f0\fs20 \cf0 80 mm}</string>
			</dict>
		</dict>
		<dict>
			<key>Class</key>
			<string>LineGraphic</string>
			<key>ID</key>
			<integer>17</integer>
			<key>Labels</key>
			<array>
				<dict>
					<key>Filled</key>
					<string>NO</string>
					<key>Label</key>
					<dict>
						<key>Align</key>
						<integer>0</integer>
						<key>Text</key>
						<string>{\rtf1\mac\ansicpg10000\cocoartf102
{\fonttbl\f0\fswiss\fcharset77 Helvetica;}
{\colortbl;\red255\green255\blue255;}
\pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\ql\qnatural

\f0\fs20 \cf0 315\'bc}</string>
					</dict>
					<key>LabelVisible</key>
					<string>YES</string>
					<key>Offset</key>
					<real>6.875</real>
					<key>Orientation</key>
					<integer>2</integer>
					<key>Position</key>
					<real>0.7421875</real>
				</dict>
			</array>
			<key>Points</key>
			<array>
				<string>{290.5, 290.5}</string>
				<string>{396.9, 396.9}</string>
			</array>
			<key>Style</key>
			<dict>
				<key>stroke</key>
				<dict>
					<key>HeadArrow</key>
					<string>FilledArrow</string>
					<key>TailArrow</key>
					<string>0</string>
				</dict>
			</dict>
			<key>Tail</key>
			<dict>
				<key>ID</key>
				<integer>14</integer>
			</dict>
		</dict>
		<dict>
			<key>Class</key>
			<string>LineGraphic</string>
			<key>ID</key>
			<integer>16</integer>
			<key>Labels</key>
			<array>
				<dict>
					<key>Filled</key>
					<string>NO</string>
					<key>Label</key>
					<dict>
						<key>Align</key>
						<integer>0</integer>
						<key>Text</key>
						<string>{\rtf1\mac\ansicpg10000\cocoartf102
{\fonttbl\f0\fswiss\fcharset77 Helvetica;}
{\colortbl;\red255\green255\blue255;}
\pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\ql\qnatural

\f0\fs20 \cf0 45\'bc}</string>
					</dict>
					<key>LabelVisible</key>
					<string>YES</string>
					<key>Offset</key>
					<real>-5.625</real>
					<key>Orientation</key>
					<integer>2</integer>
					<key>Position</key>
					<real>0.7421875</real>
				</dict>
			</array>
			<key>Points</key>
			<array>
				<string>{290.5, 276.325}</string>
				<string>{396.725, 170.1}</string>
			</array>
			<key>Style</key>
			<dict>
				<key>stroke</key>
				<dict>
					<key>HeadArrow</key>
					<string>FilledArrow</string>
					<key>TailArrow</key>
					<string>0</string>
				</dict>
			</dict>
			<key>Tail</key>
			<dict>
				<key>ID</key>
				<integer>14</integer>
			</dict>
		</dict>
		<dict>
			<key>Class</key>
			<string>LineGraphic</string>
			<key>ID</key>
			<integer>15</integer>
			<key>Labels</key>
			<array>
				<dict>
					<key>Filled</key>
					<string>NO</string>
					<key>Label</key>
					<dict>
						<key>Align</key>
						<integer>0</integer>
						<key>Text</key>
						<string>{\rtf1\mac\ansicpg10000\cocoartf102
{\fonttbl\f0\fswiss\fcharset77 Helvetica;}
{\colortbl;\red255\green255\blue255;}
\pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\ql\qnatural

\f0\fs20 \cf0 225\'bc}</string>
					</dict>
					<key>LabelVisible</key>
					<string>YES</string>
					<key>Offset</key>
					<real>6.875</real>
					<key>Orientation</key>
					<integer>2</integer>
					<key>Position</key>
					<real>0.7421875</real>
				</dict>
			</array>
			<key>Points</key>
			<array>
				<string>{276.325, 290.5}</string>
				<string>{169.925, 396.9}</string>
			</array>
			<key>Style</key>
			<dict>
				<key>stroke</key>
				<dict>
					<key>HeadArrow</key>
					<string>FilledArrow</string>
					<key>TailArrow</key>
					<string>0</string>
				</dict>
			</dict>
			<key>Tail</key>
			<dict>
				<key>ID</key>
				<integer>14</integer>
			</dict>
		</dict>
		<dict>
			<key>Bounds</key>
			<string>{{276.325, 276.325}, {14.175, 14.175}}</string>
			<key>Class</key>
			<string>ShapedGraphic</string>
			<key>ID</key>
			<integer>14</integer>
			<key>Shape</key>
			<string>Rectangle</string>
			<key>Style</key>
			<dict>
				<key>fill</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0</string>
					</dict>
				</dict>
				<key>shadow</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
			</dict>
		</dict>
		<dict>
			<key>Class</key>
			<string>LineGraphic</string>
			<key>ID</key>
			<integer>13</integer>
			<key>Labels</key>
			<array>
				<dict>
					<key>Filled</key>
					<string>NO</string>
					<key>Label</key>
					<dict>
						<key>Align</key>
						<integer>0</integer>
						<key>Text</key>
						<string>{\rtf1\mac\ansicpg10000\cocoartf102
{\fonttbl\f0\fswiss\fcharset77 Helvetica;}
{\colortbl;\red255\green255\blue255;}
\pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\ql\qnatural

\f0\fs20 \cf0 135\'bc}</string>
					</dict>
					<key>LabelVisible</key>
					<string>YES</string>
					<key>Offset</key>
					<real>-5.625</real>
					<key>Orientation</key>
					<integer>2</integer>
					<key>Position</key>
					<real>0.7421875</real>
				</dict>
			</array>
			<key>Points</key>
			<array>
				<string>{276.325, 276.325}</string>
				<string>{170.1, 170.1}</string>
			</array>
			<key>Style</key>
			<dict>
				<key>stroke</key>
				<dict>
					<key>HeadArrow</key>
					<string>FilledArrow</string>
					<key>TailArrow</key>
					<string>0</string>
				</dict>
			</dict>
			<key>Tail</key>
			<dict>
				<key>ID</key>
				<integer>14</integer>
			</dict>
		</dict>
		<dict>
			<key>Bounds</key>
			<string>{{297.1, 304.85}, {28.35, 14.175}}</string>
			<key>Class</key>
			<string>ShapedGraphic</string>
			<key>HFlip</key>
			<string>YES</string>
			<key>ID</key>
			<integer>12</integer>
			<key>Shape</key>
			<string>RoundRect</string>
			<key>Style</key>
			<dict>
				<key>fill</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
				<key>shadow</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
				<key>stroke</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
			</dict>
			<key>VFlip</key>
			<string>YES</string>
		</dict>
		<dict>
			<key>Bounds</key>
			<string>{{325.45, 333.2}, {28.35, 14.175}}</string>
			<key>Class</key>
			<string>ShapedGraphic</string>
			<key>HFlip</key>
			<string>YES</string>
			<key>ID</key>
			<integer>11</integer>
			<key>Shape</key>
			<string>RoundRect</string>
			<key>Style</key>
			<dict>
				<key>fill</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
				<key>shadow</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
				<key>stroke</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
			</dict>
			<key>VFlip</key>
			<string>YES</string>
		</dict>
		<dict>
			<key>Bounds</key>
			<string>{{382.15, 389.9}, {28.35, 14.175}}</string>
			<key>Class</key>
			<string>ShapedGraphic</string>
			<key>HFlip</key>
			<string>YES</string>
			<key>ID</key>
			<integer>10</integer>
			<key>Shape</key>
			<string>RoundRect</string>
			<key>Style</key>
			<dict>
				<key>fill</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
				<key>shadow</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
				<key>stroke</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
			</dict>
			<key>VFlip</key>
			<string>YES</string>
		</dict>
		<dict>
			<key>Bounds</key>
			<string>{{297.1, 248.15}, {28.35, 14.175}}</string>
			<key>Class</key>
			<string>ShapedGraphic</string>
			<key>HFlip</key>
			<string>YES</string>
			<key>ID</key>
			<integer>9</integer>
			<key>Shape</key>
			<string>RoundRect</string>
			<key>Style</key>
			<dict>
				<key>fill</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
				<key>shadow</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
				<key>stroke</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
			</dict>
		</dict>
		<dict>
			<key>Bounds</key>
			<string>{{325.45, 219.8}, {28.35, 14.175}}</string>
			<key>Class</key>
			<string>ShapedGraphic</string>
			<key>HFlip</key>
			<string>YES</string>
			<key>ID</key>
			<integer>8</integer>
			<key>Shape</key>
			<string>RoundRect</string>
			<key>Style</key>
			<dict>
				<key>fill</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
				<key>shadow</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
				<key>stroke</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
			</dict>
		</dict>
		<dict>
			<key>Bounds</key>
			<string>{{382.15, 163.1}, {28.35, 14.175}}</string>
			<key>Class</key>
			<string>ShapedGraphic</string>
			<key>HFlip</key>
			<string>YES</string>
			<key>ID</key>
			<integer>7</integer>
			<key>Shape</key>
			<string>RoundRect</string>
			<key>Style</key>
			<dict>
				<key>fill</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
				<key>shadow</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
				<key>stroke</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
			</dict>
		</dict>
		<dict>
			<key>Bounds</key>
			<string>{{240.4, 304.85}, {28.35, 14.175}}</string>
			<key>Class</key>
			<string>ShapedGraphic</string>
			<key>ID</key>
			<integer>6</integer>
			<key>Shape</key>
			<string>RoundRect</string>
			<key>Style</key>
			<dict>
				<key>fill</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
				<key>shadow</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
				<key>stroke</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
			</dict>
			<key>VFlip</key>
			<string>YES</string>
		</dict>
		<dict>
			<key>Bounds</key>
			<string>{{212.05, 333.2}, {28.35, 14.175}}</string>
			<key>Class</key>
			<string>ShapedGraphic</string>
			<key>ID</key>
			<integer>5</integer>
			<key>Shape</key>
			<string>RoundRect</string>
			<key>Style</key>
			<dict>
				<key>fill</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
				<key>shadow</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
				<key>stroke</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
			</dict>
			<key>VFlip</key>
			<string>YES</string>
		</dict>
		<dict>
			<key>Bounds</key>
			<string>{{155.35, 389.9}, {28.35, 14.175}}</string>
			<key>Class</key>
			<string>ShapedGraphic</string>
			<key>ID</key>
			<integer>4</integer>
			<key>Shape</key>
			<string>RoundRect</string>
			<key>Style</key>
			<dict>
				<key>fill</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
				<key>shadow</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
				<key>stroke</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
			</dict>
			<key>VFlip</key>
			<string>YES</string>
		</dict>
		<dict>
			<key>Bounds</key>
			<string>{{240.4, 248.15}, {28.35, 14.175}}</string>
			<key>Class</key>
			<string>ShapedGraphic</string>
			<key>ID</key>
			<integer>3</integer>
			<key>Shape</key>
			<string>RoundRect</string>
			<key>Style</key>
			<dict>
				<key>fill</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
				<key>shadow</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
				<key>stroke</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
			</dict>
		</dict>
		<dict>
			<key>Bounds</key>
			<string>{{212.05, 219.8}, {28.35, 14.175}}</string>
			<key>Class</key>
			<string>ShapedGraphic</string>
			<key>ID</key>
			<integer>2</integer>
			<key>Shape</key>
			<string>RoundRect</string>
			<key>Style</key>
			<dict>
				<key>fill</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
				<key>shadow</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
				<key>stroke</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
			</dict>
		</dict>
		<dict>
			<key>Bounds</key>
			<string>{{155.35, 163.1}, {28.35, 14.175}}</string>
			<key>Class</key>
			<string>ShapedGraphic</string>
			<key>ID</key>
			<integer>1</integer>
			<key>Shape</key>
			<string>RoundRect</string>
			<key>Style</key>
			<dict>
				<key>fill</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
				<key>shadow</key>
				<dict>
					<key>Draws</key>
					<string>NO</string>
				</dict>
				<key>stroke</key>
				<dict>
					<key>Color</key>
					<dict>
						<key>w</key>
						<string>0.5</string>
					</dict>
				</dict>
			</dict>
		</dict>
	</array>
	<key>GridInfo</key>
	<dict>
		<key>GridSpacing</key>
		<real>7.0875000953674316</real>
		<key>MajorGridSpacing</key>
		<integer>20</integer>
		<key>ShowsGrid</key>
		<string>YES</string>
		<key>SnapsToGrid</key>
		<string>YES</string>
	</dict>
	<key>GuidesVisible</key>
	<string>YES</string>
	<key>HPages</key>
	<integer>1</integer>
	<key>ImageCounter</key>
	<integer>1</integer>
	<key>IsPalette</key>
	<string>NO</string>
	<key>Layers</key>
	<array>
		<dict>
			<key>Lock</key>
			<string>NO</string>
			<key>Name</key>
			<string>Layer 1</string>
			<key>Print</key>
			<string>YES</string>
			<key>View</key>
			<string>YES</string>
		</dict>
	</array>
	<key>LayoutInfo</key>
	<dict>
		<key>AutoAdjust</key>
		<string>YES</string>
		<key>ChildOrdering</key>
		<integer>2</integer>
		<key>MagneticFieldCenter</key>
		<string>{0, 0}</string>
	</dict>
	<key>LinksVisible</key>
	<string>NO</string>
	<key>MagnetsVisible</key>
	<string>NO</string>
	<key>Orientation</key>
	<integer>2</integer>
	<key>PageBreaks</key>
	<string>YES</string>
	<key>PageSetup</key>
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		<true/>
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		<true/>
		<key>VisibleRegion</key>
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Ignore Space Show notes View Gleeson_2005/test-environment.tif 0 → 100644

Ignore Space Show notes View Gleeson_2005/variation.plo 0 → 100644
#musthave device #musthave target #proc settings units: cm #endproc #set field_40 = @device "_" @target "_40" #set field_80 = @device "_" @target "_80" #set field_160 = @device "_" @target "_160" #proc getdata delim: comma fieldnameheader: yes data: angle,mouse_text_40,mouse_text_80,mouse_text_160,mouse_combo_40,mouse_combo_80,mouse_combo_160,touch_text_40,touch_text_80,touch_text_160,touch_combo_40,touch_combo_80,touch_combo_160 45,36.1,40.2425,42.89,40.3325,40.3325,38.5675,26.72909752,25.38166745,25.94191397,30.32391975,26.10231481,27.06981481 135,20.7525,23.575,31.865,20.225,19.6075,19.87,23.19430419,23.81227848,24.95375293,30.40052469,32.8770679,37.77787037 225,19.52,23.31,27.28,21.195,23.31,21.105,19.58570636,21.33953,23.72853688,31.4591358,31.72521605,35.06466049 315,32.2175,39.5375,42.27,39.625,42.5375,38.8325,27.26008947,25.49955696,24.24673621,28.63228395,23.28416667,24.87274691 #proc areadef #if @device = "touch" title: Touch #else title: Mouse #endif titledetails: size=10 style=B align=C areaname: standard yrange: 0 47 xrange: 0 360 autowidth: 0.0055555556 autoheight: 0.0444444444 #proc yaxis: stubs: inc 10 stubformat: %2.0f stubdetails: size=10 label: Standard deviation labeldetails: style=B size=10 adjust=-0.1,0 grid: color=gray(0.7) #proc xaxis: selflocatingstubs: datafields=angle,angle stubdetails: size=10 label: Target angle (degrees) labeldetails: style=B size=10 adjust=0,-0.1 //adjust=-0.1,0 #proc lineplot xfield: angle yfield: @field_40 linedetails: color=black pointsymbol: shape=diamond linecolor=black fillcolor=black legendlabel: 40 mm legendsampletype: line+symbol #proc lineplot xfield: angle yfield: @field_80 linedetails: color=gray(0.2) pointsymbol: shape=square linecolor=gray(0.2) fillcolor=gray(0.2) legendlabel: 80 mm legendsampletype: line+symbol #proc lineplot xfield: angle yfield: @field_160 linedetails: color=gray(0.6) pointsymbol: shape=circle linecolor=gray(0.4) fillcolor=gray(0.4) legendlabel: 160 mm legendsampletype: line+symbol #proc legend format: multiline location: max-1.5 min+1.65 textdetails: size=10 seglen: 0.25 reverseorder: yes

Ignore Space Show notes View

Gleeson_2005/variation.plo 0 → 100644

#musthave device
#musthave target

#proc settings
	units: cm
#endproc

#set field_40 = @device "_" @target "_40"
#set field_80 = @device "_" @target "_80"
#set field_160 = @device "_" @target "_160"

#proc getdata
	delim: comma
	fieldnameheader: yes
	data:
		angle,mouse_text_40,mouse_text_80,mouse_text_160,mouse_combo_40,mouse_combo_80,mouse_combo_160,touch_text_40,touch_text_80,touch_text_160,touch_combo_40,touch_combo_80,touch_combo_160
		45,36.1,40.2425,42.89,40.3325,40.3325,38.5675,26.72909752,25.38166745,25.94191397,30.32391975,26.10231481,27.06981481
		135,20.7525,23.575,31.865,20.225,19.6075,19.87,23.19430419,23.81227848,24.95375293,30.40052469,32.8770679,37.77787037
		225,19.52,23.31,27.28,21.195,23.31,21.105,19.58570636,21.33953,23.72853688,31.4591358,31.72521605,35.06466049
		315,32.2175,39.5375,42.27,39.625,42.5375,38.8325,27.26008947,25.49955696,24.24673621,28.63228395,23.28416667,24.87274691

#proc areadef
	#if @device = "touch"
		title: Touch
	#else
		title: Mouse
	#endif
	titledetails: size=10 style=B align=C
	areaname: standard
	yrange: 0 47
	xrange: 0 360
	autowidth: 0.0055555556
	autoheight: 0.0444444444

#proc yaxis:
	stubs: inc 10
	stubformat: %2.0f
	stubdetails: size=10
	label: Standard deviation
	labeldetails: style=B size=10 adjust=-0.1,0
	grid: color=gray(0.7)

#proc xaxis:
	selflocatingstubs: datafields=angle,angle
	stubdetails: size=10
	label: Target angle (degrees)
	labeldetails: style=B size=10 adjust=0,-0.1
	//adjust=-0.1,0

#proc lineplot
	xfield: angle
	yfield: @field_40
	linedetails: color=black
	pointsymbol: shape=diamond linecolor=black fillcolor=black
	legendlabel: 40 mm
	legendsampletype: line+symbol

#proc lineplot
	xfield: angle
	yfield: @field_80
	linedetails: color=gray(0.2)
	pointsymbol: shape=square linecolor=gray(0.2) fillcolor=gray(0.2)
	legendlabel: 80 mm
	legendsampletype: line+symbol

#proc lineplot
	xfield: angle
	yfield: @field_160
	linedetails: color=gray(0.6)
	pointsymbol: shape=circle linecolor=gray(0.4) fillcolor=gray(0.4)
	legendlabel: 160 mm
	legendsampletype: line+symbol

#proc legend
	format: multiline
	location: max-1.5 min+1.65
	textdetails: size=10
	seglen: 0.25
	reverseorder: yes

Ignore Space Show notes View Gleeson_2005/variation.xls 0 → 100644
Not supported

Show notes View Gleeson_paper.bib 100755 → 0
This file was created with JabRef 1.6. Encoding: ISO8859_1 @STRING{ACJ = {Australian Computer Journal}} @STRING{ADT = {Application Development Trends}} @STRING{AI = {Artificial Intelligence}} @STRING{AJIS = {Australian Journal of Information Systems}} @STRING{CACM = {Communications of the ACM}} @STRING{CJ = {The Computer Journal}} @STRING{Database = {ACM SIGMIS Database}} @STRING{DBMS = {DBMS Magazine}} @STRING{DBPD = {Database Programming {\&} Design}} @STRING{develop = {{d}evelop, The Apple Technical Journal}} @STRING{Directions = {Apple Directions}} @STRING{DKE = {Data {\&} Knowledge Engineering}} @STRING{EJIS = {European Journal of Information Systems}} @STRING{IDT = {Internet Development Trends}} @STRING{IJAST = {International Journal of Applied Software Technology}} @STRING{IJGIS = {International Journal of Geographical Information Systems}} @STRING{IJHCS = {International Journal of Human-Computer Studies}} @STRING{IJMMS = {International Journal of Man-Machine Studies}} @STRING{IJSEKE = {International Journal of Software Engineering and Knowledge Engineering}} @STRING{IS = {Information Systems}} @STRING{ISJ = {Information Systems Journal}} @STRING{IST = {Information and Software Technology}} @STRING{JACM = {Journal of the ACM}} @STRING{JLP = {Journal of Logic Programming}} @STRING{JOT = {Journal of Object Technology}} @STRING{JSS = {Journal of Systems and Software}} @STRING{LNCS = {Lecture Notes in Computer Science}} @STRING{MISQ = {MIS Quarterly}} @STRING{NZJC = {New Zealand Journal of Computing}} @STRING{NZJIS = {New Zealand Journal of Information Systems}} @STRING{Oracle = {Oracle Magazine}} @STRING{Reg = {{\textsuperscript{\scriptsize\textregistered}}}} @STRING{SEJ = {Software Engineering Journal}} @STRING{SIGMOD = {ACM SIGMOD Record}} @STRING{SPE = {Software---Practice and Experience}} @STRING{Surveys = {ACM Computing Surveys}} @STRING{TKDE = {IEEE Transactions on Knowledge and Data Engineering}} @STRING{TM = {{\scriptsize\texttrademark}}} @STRING{TODS = {ACM Transactions on Database Systems}} @STRING{TOSE = {IEEE Transactions on Software Engineering}} @STRING{VLDB = {The VLDB Journal}} @PHDTHESIS{Bend-G-1999-PhD, author = {Gregory T. Bender}, title = {Touch Screen Performance as a Function of the Duration of Auditory Feedback and Target Size}, school = {Wichita State University}, year = {1999}, type = {PhD thesis}, address = {Wichita, Kansas}, pdf = {B/Bend-G-1999-PhD.pdf}, url = {http://www.thisoldtractor.com/gtbender/papers/dissertation.pdf}, } @BOOK{Appl-2004-HIG, title = {Apple Human Interface Guidelines}, publisher = {Apple Computer, Inc.}, year = {2004}, author = {{Apple Computer}}, month = may, pdf = {A/Appl-2004-HIG.pdf}, url = {http://developer.apple.com/documentation/UserExperience/Conceptual/OSXHIGuidelines/index.html}, } @INPROCEEDINGS{Doug-SA-1999-CHI, author = {Sarah A. Douglas and Arthur E. Kirkpatrick and I. Scott MacKenzie}, title = {Testing pointing device performance and user assessment with the {ISO} 9241, {P}art 9 standard.}, booktitle = {The CHI is the Limit: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '99)}, year = {1999}, pages = {215--222}, address = {Pittsburgh, Pennsylvania}, month = may # {~15--20}, publisher = {ACM Press}, doi = {doi:10.1145/302979.303042}, pdf = {D/Doug-SA-1999-CHI.pdf}, } @INPROCEEDINGS{Doug-SA-1994-SIGCHI, author = {Sarah A. Douglas and Anant Kartik Mithal}, title = {The effect of reducing homing time on the speed of a finger-controlled isometric pointing device}, booktitle = {Celebrating Interdependence: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '94)}, year = {1994}, pages = {411--416}, address = {Boston, Massachusetts}, month = apr # {~24--28}, publisher = {ACM Press}, doi = {doi:10.1145/191666.191805}, pdf = {D/Doug-SA-1994-SIGCHI.pdf}, isbn = {0-89791-650-6}, } @TECHREPORT{ISO-2000-9241-9, author = {ISO}, title = {Ergonomic {R}equirements for {O}ffice {W}ork with {V}isual {D}isplay {T}erminals ({VDT}s)---{P}art 9: {R}equirements for {N}on-keyboard {I}nput {D}evices}, institution = {International Organisation for Standardisation (ISO)}, year = {2000}, type = {International standard}, number = {ISO 9241-9:2000}, address = {Geneva, Switzerland}, } @INPROCEEDINGS{Mack-IS-2001-EHCI, author = {I. Scott MacKenzie and Shaidah Jusoh}, title = {An evaluation of two input devices for remote pointing}, booktitle = {Proceedings of the 8th IFIP International Conference on Engineering for Human-Computer Interaction (EHCI 2001, revised papers)}, year = {2001}, editor = {Murray Reed Little and Laurence Nigay}, volume = {2254}, series = LNCS, pages = {235--250}, address = {Toronto, Canada}, month = may # {~11--13}, publisher = {Springer}, isbn = {3-540-43044-X}, pdf = {M/Mack-IS-2001-EHCI.pdf}, url = {http://link.springer.de/link/service/series/0558/bibs/2254/22540235.htm}, citeseerurl = {http://citeseer.ist.psu.edu/609516.html}, } @INPROCEEDINGS{Mack-IS-1991, author = {I. Scott MacKenzie and Abigail Sellen and William A. S. Buxton}, title = {A comparison of input devices in element pointing and dragging tasks}, booktitle = {Reaching Through Technology: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '91)}, year = {1991}, pages = {161--166}, address = {New Orleans, Louisiana}, month = apr # {~27--} # may # {~2}, doi = {doi:10.1145/108844.108868}, pdf = {M/Mack-IS-1991.pdf}, } @ARTICLE{Sear-A-1991-IJMMS, author = {Andrew Sears and Ben Shneiderman}, title = {High precision touchscreens: {D}esign strategies and comparisons with a mouse}, journal = IJMMS, year = {1991}, volume = {34}, number = {4}, pages = {593--613}, }

Show notes View

Gleeson_paper.bib 100755 → 0

This file was created with JabRef 1.6.
Encoding: ISO8859_1

@STRING{ACJ = {Australian Computer Journal}}

@STRING{ADT = {Application Development Trends}}

@STRING{AI = {Artificial Intelligence}}

@STRING{AJIS = {Australian Journal of Information Systems}}

@STRING{CACM = {Communications of the ACM}}

@STRING{CJ = {The Computer Journal}}

@STRING{Database = {ACM SIGMIS Database}}

@STRING{DBMS = {DBMS Magazine}}

@STRING{DBPD = {Database Programming {\&} Design}}

@STRING{develop = {{d}evelop, The Apple Technical Journal}}

@STRING{Directions = {Apple Directions}}

@STRING{DKE = {Data {\&} Knowledge Engineering}}

@STRING{EJIS = {European Journal of Information Systems}}

@STRING{IDT = {Internet Development Trends}}

@STRING{IJAST = {International Journal of Applied Software Technology}}

@STRING{IJGIS = {International Journal of Geographical Information Systems}}

@STRING{IJHCS = {International Journal of Human-Computer Studies}}

@STRING{IJMMS = {International Journal of Man-Machine Studies}}

@STRING{IJSEKE = {International Journal of Software Engineering and Knowledge Engineering}}

@STRING{IS = {Information Systems}}

@STRING{ISJ = {Information Systems Journal}}

@STRING{IST = {Information and Software Technology}}

@STRING{JACM = {Journal of the ACM}}

@STRING{JLP = {Journal of Logic Programming}}

@STRING{JOT = {Journal of Object Technology}}

@STRING{JSS = {Journal of Systems and Software}}

@STRING{LNCS = {Lecture Notes in Computer Science}}

@STRING{MISQ = {MIS Quarterly}}

@STRING{NZJC = {New Zealand Journal of Computing}}

@STRING{NZJIS = {New Zealand Journal of Information Systems}}

@STRING{Oracle = {Oracle Magazine}}

@STRING{Reg = {{\textsuperscript{\scriptsize\textregistered}}}}

@STRING{SEJ = {Software Engineering Journal}}

@STRING{SIGMOD = {ACM SIGMOD Record}}

@STRING{SPE = {Software---Practice and Experience}}

@STRING{Surveys = {ACM Computing Surveys}}

@STRING{TKDE = {IEEE Transactions on Knowledge and Data Engineering}}

@STRING{TM = {{\scriptsize\texttrademark}}}

@STRING{TODS = {ACM Transactions on Database Systems}}

@STRING{TOSE = {IEEE Transactions on Software Engineering}}

@STRING{VLDB = {The VLDB Journal}}

@BOOK{Appl-2004-HIG,
  title = {Apple Human Interface Guidelines},
  publisher = {Apple Computer, Inc.},
  year = {2004},
  author = {{Apple Computer}},
  month = may,
  pdf = {A/Appl-2004-HIG.pdf},
  url = {http://developer.apple.com/documentation/UserExperience/Conceptual/OSXHIGuidelines/index.html},
}

@INPROCEEDINGS{Mack-IS-2001-EHCI,
  author = {I. Scott MacKenzie and Shaidah Jusoh},
  title = {An evaluation of two input devices for remote pointing},
  booktitle = {Proceedings of the 8th IFIP International Conference on Engineering for Human-Computer Interaction (EHCI 2001, revised papers)},
  year = {2001},
  editor = {Murray Reed Little and Laurence Nigay},
  volume = {2254},
  series = LNCS,
  pages = {235--250},
  address = {Toronto, Canada},
  month = may # {~11--13},
  publisher = {Springer},
  isbn = {3-540-43044-X},
  pdf = {M/Mack-IS-2001-EHCI.pdf},
  url = {http://link.springer.de/link/service/series/0558/bibs/2254/22540235.htm},
  citeseerurl = {http://citeseer.ist.psu.edu/609516.html},
}

Show notes View Gleeson_paper.tex 100755 → 0
% Template article for preprint document class `elsart' % with harvard style bibliographic references % SP 2001/01/05 \documentclass{elsart} % Use the option doublespacing or reviewcopy to obtain double line spacing % \documentclass[doublespacing]{elsart} % the natbib package allows both number and author-year (Harvard) % style referencing; \usepackage[authoryear,sort]{natbib} % if you use PostScript figures in your article % use the graphics package for simple commands % \usepackage{graphics} % or use the graphicx package for more complicated commands \usepackage{graphicx} % or use the epsfig package if you prefer to use the old commands % \usepackage{epsfig} % The amssymb package provides various useful mathematical symbols \usepackage{amssymb} \usepackage{units} \usepackage{url} \begin{document} \begin{frontmatter} % Title, authors and addresses % use the thanksref command within \title, \author or \address for footnotes; % use the corauthref command within \author for corresponding author footnotes; % use the ead command for the email address, % and the form \ead[url] for the home page: % \title{Title\thanksref{label1}} % \thanks[label1]{} % \author{Name\corauthref{cor1}\thanksref{label2}} % \ead{email address} % \ead[url]{home page} % \thanks[label2]{} % \corauth[cor1]{} % \address{Address\thanksref{label3}} % \thanks[label3]{} \title{Assessing the efficacy of a touch screen overlay as a selection device using typical GUI targets} % use optional labels to link authors explicitly to addresses: % \author[label1,label2]{} % \address[label1]{} % \address[label2]{} \author[info]{Matthew Gleeson}, \ead{matt\_gleeson@xtra.co.nz} \author[info]{Nigel Stanger\corauthref{cor}}, \ead{nstanger@infoscience.otago.ac.nz} \corauth[cor]{Corresponding author. Tel.: +64-3-479-8179; fax: +64-3-479-8311} \author[hunt]{Elaine Ferguson} \ead{elaine.ferguson@stonebow.otago.ac.nz} \address[info]{Department of Information Science,} \address[hunt]{Department of Human Nutrition, \\ University of Otago, PO Box 56, Dunedin, New Zealand} \begin{abstract} Touch screens are a popular method of interacting with kiosk-based information systems, whereas typical desktop information systems use a mouse as the primary selection device. In this paper we investigate the efficacy of a touch screen overlay compared to a mouse, when selecting typical graphical user interface (GUI) items in a desktop information system. A series of tests were completed involving multi-directional point and select tasks, and the results for both devices compared. The results showed that the touch screen overlay was not suitable for selecting GUI targets smaller than \unit[4]{mm}. The touch screen overlay was slower and had a higher error rate than the mouse, but there was no significant difference in throughput. Testers rated the mouse easier to use and to make accurate selections, while the touch screen overlay resulted in greater arm, wrist and finger fatigue. These results suggest that a touch screen overlay is not a practical selection device for desktop interfaces with small GUI targets. \end{abstract} \begin{keyword} Touch screen overlay \sep Mouse \sep Selection device \sep Fitts' Law \sep Performance evaluation \sep GUI items \end{keyword} \end{frontmatter} % main text \section{Introduction} \label{sec-introduction} Most modern information systems that run on desktop personal computers are designed to be used with a keyboard and mouse. While the combination of keyboard and mouse is the accepted method of interaction with such systems it does not necessarily suit all information systems. Information systems with limited data entry may be more usable through the use of a keyboard and touch screen. Touch screens require less physical space and thus the workstation environment in an office setting could be improved, allocating more space to the user and less to the computer. The purpose of this paper is to investigate how effective a touch screen overlay is compared to a mouse, when selecting typical graphical user interface (GUI) items used in information systems. The target types tested were buttons, check boxes, combo boxes and text boxes, which are typical of those found in an interface for an information system. Each target type was tested at three different sizes (see Section~\ref{sec-GUI}). A typical touch screen device comprises a monitor enhanced with hardware for detecting touches on the screen surface. An alternative approach is to attach a discrete touch-sensitive surface to an existing conventional monitor. \citet{Sear-A-1991-IJMMS} have previously assessed the efficacy of specialised touch screen hardware, but there appears to have been little research into the efficacy of touch screen overlays. We therefore chose to compare the performance of a touch screen overlay with that of a mouse. The testing occurred in the context of a research project undertaken by the Department of Human Nutrition at the University of Otago. This project aimed to improve complementary food diets for toddlers in New Zealand by designing a computer program to help formulate population-specific food-based dietary guidelines for this high risk group. The program was a rapid assessment decision-making tool, designed specifically to assist nutrition programme planners in selecting appropriate and improved home-based complementary foods \citep{Ferg-E-2004}. The testing for our study took place within this program environment. % do we need this? The remainder of the paper discusses the experimental design and the results obtained. Section~\ref{sec-GUI} briefly describes the types of targets used in the experiment, while Section~\ref{sec-evaluation} describes the measures used to evaluate the selection devices. The experimental design is described in Section~\ref{sec-method}. Section~\ref{sec-analysis} describes how the data were analysed, and Section~\ref{sec-results} presents the results of the experiment. Our conclusions are presented in Section~\ref{sec-conclusions}. \section{GUI targets} \label{sec-GUI} Since the 1980s much research has been put into developing human computer interface guidelines. Today's interfaces are made up of a combination of different targets that could include text boxes, check boxes, combo boxes, list boxes, buttons, labels, tool bars etc. Results of research undertaken by \citet{Sear-A-1991-IJMMS} showed that touch screens can be successfully used as a selection device and can have advantages over a mouse, even for small targets. But these results were based on selecting arbitrary shapes and not typical GUI items commonly found in today's GUIs. To accurately test the performance of each selection device within the experiment, varying sized targets were used. The sizes represent small, medium and large for each target. Apple has produced some guidelines for developers to follow when designing interfaces for software \citep{Appl-2004-HIG}. In particular, for each target three different sizes are given corresponding to large, small and mini. The sizes used in this experiment were based on these guidelines and are shown in Table~\ref{tab-target-sizes}. \begin{table} \caption{Target sizes (width \(\times\) height) used in the experiment.} \label{tab-target-sizes} \begin{tabular}{llll} \hline \textbf{Target type} & \textbf{Large} & \textbf{Medium} & \textbf{Small} \\ \hline Text box & \(\unit[63]{mm} \times \unit[11]{mm}\) & \(\unit[55]{mm} \times \unit[8]{mm}\) & \(\unit[47]{mm} \times \unit[6]{mm}\) \\ Combo box & \(\unit[63]{mm} \times \unit[11]{mm}\) & \(\unit[55]{mm} \times \unit[8]{mm}\) & \(\unit[47]{mm} \times \unit[6]{mm}\) \\ Button & \(\unit[28]{mm} \times \unit[13]{mm}\) & \(\unit[24]{mm} \times \unit[9]{mm}\) & \(\unit[17]{mm} \times \unit[6]{mm}\) \\ Check box & \(\unit[9]{mm} \times \unit[9]{mm}\) & \(\unit[6]{mm} \times \unit[6]{mm}\) & \(\unit[4]{mm} \times \unit[4]{mm}\) \\ \hline \end{tabular} \end{table} \section{Evaluation methods} \label{sec-evaluation} Each selection device was assessed using a combination of performance and comfort measures. \subsection{Performance} \label{sec-evaluation-performance} The dependent measure described by ISO 9241-9 is throughput \citep{ISO-2000-9241-9}. Throughput is noted by \citet{Mack-IS-2001-EHCI} as being a very important measure as it reflects the efficiency of the user completing the task and it is a measure of both speed and accuracy. The formula for calculating throughput is given in the following equation: \[ \mathit{throughput} = \mathit{ID}_{e} / \mathit{MT} \] where \[ \mathit{ID}_{e} = \log_{2}(D / W_{e} + 1) \] \(\mathit{ID}_{e}\) represents the index of difficulty and is defined in terms of bits whereas movement time is defined in terms of seconds. Therefore throughput is measured in bits per second (bps). \(D\) represents the distance to the target. Throughput is used by the ISO 9241-9 standard as the performance measurement. \(W_{e}\) is the effective width and differs from the width of the target. It reflects the spatial variability in the sequence of trials. The formula for calculating effective width is given in the following equation: \[ W_{e} = 4.133 \times \mathit{SD}_{x} \] \(\mathit{SD}_{x}\) is the standard deviation in the selection coordinates measured along the path to the target Due to the nature of making a selection within a drop-down list, the throughput for a combo box was adjusted to take into account the extra distance to the desired list item. Movement time is defined as time taken to successfully select a target. Error rate is defined as the number of selections made outside of the intended target. The error rate is the ratio of incorrect selections to correct selections made, so an error rate of 100\% means as many errors as correct selections. Both movement time and error rate were left out of the ISO standard 9241-9 in terms of performance measurements but \citet{Doug-SA-1999-CHI} recommend computing both measurements to give a more detailed performance analysis for the selection device. \subsection{Comfort} \label{sec-evaluation-comfort} A questionnaire was used to assess comfort and user satisfaction of each selection device. The selection device assessment questionnaire consisted of sixteen questions, eight of which were taken from the ISO ``Independent Questionnaire for Assessment of Comfort'' \citep{Doug-SA-1999-CHI}. The remaining eight questions related specifically to the targets tested and the size of the targets tested. In particular, the questionnaire aimed to assess the participants' comfort in using the input device, the difficulty in accurately selecting each of the targets and the preferable size of each target using the input device. The responses to twelve of the questions were based on a five point ordinal scale. The remaining four questions referred to the participant's preferred size for each target and were based on a three point response corresponding to the sizes tested---small, medium and large. \section{Method} \label{sec-method} An experiment was carried out to test the effect of size for different GUI targets with different selection devices. The experiment consisted of completing a series of simple point and select tasks. Small, medium and large sizes were tested for a combo box, text box, check box and button. The selection devices tested were a touch screen overlay and mouse. The test was multi-directional, meaning the target appeared in more than one direction to the user. A variety of different sizes, angles and distances were used for each target position. \subsection{Participants} \label{sec-method-participants} A participant sample size of twenty four was used for the experiment. Each participant was allocated to one of two groups with each group using one selection device in testing. The allocation of groups was based upon the results of a questionnaire completed by each participant prior to testing. The purpose of the questionnaire was to establish the level of computer, mouse and touch screen experience of each participant. A participant was allocated to a selection device group depending on what device they had the least amount of experience with. Due to the testing being done within a nutrition program environment, the participants were all nutritionists (typical users of the program). There were 21 female and 3 male participants with all having a university level of education. All participants were unpaid volunteers. \subsection{Apparatus} \label{sec-method-apparatus} Software written in Visual Basic.Net with Microsoft Studio 2003 was used to implement the test as illustrated in Figure~\ref{fig-test-screenshot}. Each test was connected to a Microsoft Excel worksheet and the data corresponding to the relevant measures (movement time, number of errors and selection coordinates) were captured using the software and written to the Excel worksheet. \begin{figure} \includegraphics{test-screenshot} \caption{Screenshot of the test with the target in the top left of the screen and the ``go'' button in the centre.} \label{fig-test-screenshot} \end{figure} The touch screen used in testing was a 17'' Magic Touch USB overlay Model KTMT-1700-USB-M. This touch screen uses a lift-off touch strategy. A touch screen overlay is a piece of equipment external to the monitor. It sits in front of the monitor and behaves similarly to a touch screen monitor. Using an overlay results in a gap between the overlay and the monitor itself, this causes a slight discrepancy between where the user touches the overlay and where the cursor is positioned on the screen. The touch screen overlay was fitted to a Dell 15'' Flat Panel Model E151FPb monitor. A flat panel monitor was chosen because it was noticed during pre-testing that typical CRT monitors with rounded screens caused a gap between where the users touched the screen and where the cursor gets positioned. A flat panel is less likely to suffer this problem. The device used for testing the mouse was a Dell PS/2 Optical Mouse Model M071KC. Both devices were connected to a Dell Inspiron 7500 laptop computer which ran the testing software. \subsection{Procedure} \label{sec-method-procedure} The participant was initially given an introduction to the test by the research observer. The introduction included a brief summary of the aims of the study and what the test involved. The participant was also given and told to read an instruction sheet which they had access to throughout the duration of the test. After reading the instruction sheet the participant had the opportunity to ask questions or raise any issues. Participants were instructed to complete each block of tests as quickly as possible without losing accuracy. In between blocks of tasks, participants were given the opportunity to rest for as long as they wished. It was made clear to the participant that a task was only complete once the target was successfully selected. Selecting the button, check box and text box required the participant to simply click on the target. The strategy required to select a combo box was different. A combo box is a two-step target compared to the other targets which were simple one-step targets. First the combo box must be selected in order to show the list of items and then an item from the displayed list must be selected. During the testing the participant was instructed to always select the third item in the list when selecting a combo box as illustrated in Figure~\ref{fig-combo-box}. \begin{figure} \caption{The two-step action required to select the combo box.} \label{fig-combo-box} \end{figure} The participant was then instructed to complete a practice task involving fifteen random trials of the same point and select tasks used in the test. This brought all participants to a minimal level of experience with their selection device. This also meant each participant knew how to correctly select each device including the combo box. At the conclusion of the test the participant was required to fill out a questionnaire regarding comfort and user satisfaction with the selection device used. \subsection{Design} \label{sec-method-design} A mixed design experiment was used with the selection device as a between-subjects factor. The independent (between-subject) variables were: \begin{itemize} \item Target Type (text box, combo box, button and check box) \item Target Size (large, medium and small) \item Target Distance (\unit[40]{mm}, \unit[80]{mm} and \unit[160]{mm}) \item Target Angle (\(45^{\circ}\), \(135^{\circ}\), \(225^{\circ}\) and \(315^{\circ}\)) \item Trial (1 to 144) \item Block (1 to 6) \end{itemize} The entire test was divided into six blocks. Each block contained every possible combination of target type (4), size (3), angle from starting point (4) and distance (3). There were 144 trials in each block and the entire experiment per participant consisted of a total of 864 trials (six blocks of 144 trials). The different combinations of target location on the screen are illustrated in Figure~\ref{fig-target-positions} and are a combination of distance and the angle from the starting point. \begin{figure} \includegraphics[scale=0.85]{target-positions} \caption{Positions of targets tested. The black box represents the starting point and the rounded rectangles represent the target positions.} \label{fig-target-positions} \end{figure} The dependent variables within the experiment were throughput (TH), movement time (MT) and error rate (ER). The index of difficulty was ascertained for each task using the combination of distance and width. This showed that the test had a range of Fitts' Index of Difficulty values from 0.7 bits (\unit[63]{mm} width and \unit[160]{mm} distance) to 5.4 bits (\unit[4]{mm} width and \unit[40]{mm} distance). The ordering of the target size presented to the participant within each block in the experiment was deliberately set to large, medium and lastly small to compensate for learning. \section{Analysis} \label{sec-analysis} The data collected from the software included movement time, error rate and throughput and was used to evaluate selection device performance. A mixed design repeated measures analysis of variance model (MANOVA) was used for movement time and throughput to examine within subject differences in target and size, as well as between subject differences in device. A Greenhouse and Geisser correction of the F-ratio was used whenever the Mauchly's test results showed that assumptions of sphericity were violated. Post hoc tests, for multiple comparisons, were made using the Bonferroni method. Due to the skew observed in the error rate data inter-device difference in error rates were assessed using the Mann-Whitney U Test. The comfort questionnaire was based on a five point ordinal scale. In general five indicated a bad rating. Because of the small data size, a Mann-Whitney (non-parametric) test was used. All statistical analyses were performed using SPSS version 11.0. \section{Results and discussion} \label{sec-results} \subsection{Adjusting for learning} \label{sec-results-learning} \citet{Doug-SA-1999-CHI} recommend that input device studies should apply a repeated measures paradigm and test for learning effects. The effects of learning have been shown to affect movement time and accuracy \citep{Doug-SA-1999-CHI}. From analysing the results of movement time and throughput over each test block, it is clear for the combo box and check box that learning occurs from the first to second block with the touch screen (as seen in Figure~\ref{fig-movement-time-learning}). Due to prior experience, no learning is observed with the mouse. No learning occurs with the text box or button most likely due to their large size and simple selection behaviour. \begin{figure} \caption{Learning is displayed for movement time by device and block for the combo box and check box.} \label{fig-movement-time-learning} \end{figure} Statistical analysis using a simple repeated measure ANOVA was carried out on movement time for both the check box and combo box. For movement time of the combo box, the effect of block * device was significant \((F(1.549, 1335.219) = 4.373, p < 0.05)\). Helmhert contrasts show that the differences between blocks become non-significant after block 1 \((p > 0.05)\). For movement time of the check box, the effect of block * device was significant \((F(1.608, 1385.960) = 4.763, p < 0.05)\). Using Helmhert contrasts, the differences between blocks become non-significant after block 1 \((p > 0.05)\). This again shows that there was learning involved in block 1. To account for learning with the combo and check box, results from block 6 only will be used to calculate the performance measures of measurement time, throughput and error rate. The results from block 6 alone would give a good measure of performance. \subsection{Movement time} \label{sec-results-movement} The results showed that the mouse had an overall movement time of \unit[1.3]{s} for all targets compared to \unit[1.6]{s} for the touch screen. Therefore we can conclude that a mouse is on average 15.2\% faster than a touch screen overlay. This is interesting as \citet{Sear-A-1991-IJMMS} found that the movement time between a mouse and touch screen (monitor) was similar for rectangle targets larger than \unit[2]{mm}. Therefore the nature of the two types of touch screen (overlay and monitor) may affect the movement time associated with the type of touch screen. It is also likely that due to the loss of accuracy found with the overlay during testing, the touch screen monitor will have a lower movement time compared to the touch screen overlay. The movement times for each target showed that the text box has the fastest movement time, followed by the button, the check box and then the combo box. These results are illustrated in Figure~\ref{fig-movement-time} and follow Fitts' Law in that the largest target (the text box) had the fastest movement time. \begin{figure} \includegraphics{movement-time} \caption{Movement time for each target type across both devices and all sizes.} \label{fig-movement-time} \end{figure} As expected, the combo box had the slowest movement time due to the two-click behaviour involved in making a selection. The sizes of the combo box were exactly the same as the text box but movement time was 119\% slower. Thus the extra movement of selecting an item from the drop down list increases the movement time involved with the combo box dramatically. As the distance to the list item is relatively short from the main combo box area, the significant increase in movement time is therefore most likely due to users making more errors. A touch screen has similar movement time to a mouse for medium and large sized targets. But for the small targets, the touch screen was 67\% slower than the mouse. The only time where the touch screen was found to be faster than the mouse was with the largest target type - the large text box. The movement time for the small check box with the touch screen was 69\% slower than that of the mouse. The small check box was the smallest item tested having a width of \unit[4]{mm} and height of \unit[4]{mm}. We can conclude that the touch screen was not efficient for selecting targets as small as \unit[4]{mm}. \citet{Sear-A-1991-IJMMS} showed a touch screen has similar movement time to the mouse for targets as small as \unit[2]{mm}. Although a touch screen monitor can be used with targets as small as \unit[2]{mm}, a touch screen overlay should only be used for targets with a size of greater than \unit[4]{mm}. The results from the error rate analysis also support this \subsection{Throughput} \label{sec-results-throughput} Throughput for the mouse was \unit[1.238]{bps}, slightly higher than the 1.215 bps throughput for the touch screen. The device by itself was shown not to have a significant effect on throughput \((F(1, 22) = 0.02, p > 0.05)\). Throughput did not vary for size but throughput did vary depending on target type \((F(2.07, 45.55) = 4.77, p < 0.001)\). Check boxes had the highest throughput rate of \unit[1.967]{bps} (sd = 0.720). This is interesting as the check box was shown to have the second worst movement time and the worst error rate (see Figure~\ref{fig-throughput}). \begin{figure} \includegraphics{throughput} \caption{Throughput for each target type across both devices and all sizes.} \label{fig-throughput} \end{figure} Upon further investigation it was seen that the movement time for the check box was in fact in the middle range of all targets and due to its small size it had a high index of difficulty. Therefore these two factors are the reason for the check box having such a high throughput rate. The combo box had the worst throughput of \unit[0.501]{bps} (sd = 0.213). The index of difficulty was not very high for the combo box and so it was due to its high movement time that the combo box had such a low throughput rate. The overall throughput rate of \unit[1.2]{bps} for the mouse is much lower compared with previous research. A study by \citet{Doug-SA-1994-SIGCHI} showed a mouse had a throughput rate of \unit[4.15]{bps}. \citet{Mack-IS-1991} compared three devices (mouse, tablet and trackball) using four target sizes (8, 16, 32 and 64 pixels) over two different types of tasks: pointing and dragging. The throughput for the mouse in this case was 4.5 bps. This may indicate the level of difficulty with selection within this experiment is a lot higher than within previous research. This could be due to the selection of GUI targets instead of arbitrary rectangle targets. \subsection{Error rate} \label{sec-results-errorrate} The error rate for the mouse was only 2.7\% which is consistent with previous studies. The touch screen on the other hand had an error rate of 60.7\%. \citet{Sear-A-1991-IJMMS} found that the touch screen had an average error rate of 49\% but this was across much smaller targets. This suggests there is a loss in accuracy from using a touch screen overlay compared to a touch screen monitor. The check box had a significantly high amount of errors; 78.5\% for all sizes and both devices and in particular, 312.5\% for the small check box with the touch screen. A 100\% error rate indicates one wrong selection made for every correct selection. The touch screen incurred the majority of the errors. With the check box the mouse had an error rate of 4.4\% and the touch screen had an error rate 152.5\%. The distinguishing factor of the check box compared to the other targets was its small size. We can conclude from this that the touch screen overlay has inaccuracy in selecting small targets (\unit[4]{mm} or less). Buttons and text boxes had much lower error rates compared to that of the check box and combo box (as seen in Figure~\ref{fig-error-rate}). As buttons and text boxes also had low movement times, we can conclude that these two targets have very good overall performance. \begin{figure} \includegraphics{error-rate} \caption{Error rate for each target type across both devices and all sizes.} \label{fig-error-rate} \end{figure} \subsection{Comfort} \label{sec-results-comfort} In terms of accurate pointing the mouse (2.083) was rated easier than the touch screen (3.000). These differences were statistically significant \((p < 0.01)\). The responses regarding the question on neck, wrist and arm fatigue showed that the touch screen had a high rating (4.083), whereas the mouse was rated in the midpoint range (3.167). These differences were statistically significant \((p < 0.5)\). The final question rated the overall difficulty in using the selection device. The mouse (4.250) was rated easier to use than the touch screen (3.333). These differences were statistically significant \((p < 0.05)\). For user satisfaction with the touch screen, both the text box and button were rated easy to accurately select and the preferred size was both the large size and the medium size. This feedback is consistent with the data collected in that text boxes and buttons have short movement time and low error rates (easy to accurately select). The combo box was rated in the midpoint range in terms of ease in accurately selecting with the touch screen and the check box was rated very hard to select. Three quarters of the touch screen users preferred to select the large size combo boxes and check boxes and this reflects the poor error rates and movement times associated with these two targets with the touch screen overlay. The participants using the mouse rated the text box and button easy to accurately select with the medium and large sizes being the most preferred. Both the combo box and check box were rated harder to select than the button and text box with the check box having the worst rating. Like the touch screen overlay, the preferred size for the combo box and check box was large. One participant noted the lack of arm support for targets at the top of the screen. This is an interesting comment because the nature of using a touch screen means the users arm might be raised off the desk and be self supporting when selecting items towards the top of the desktop screen. Another suggestion was making the target change colour when the cursor is located above it. This is a similar concept to that of interactive rollover items commonly used in web pages. Auditory feedback has been shown to affect the speed and accuracy when making a selection \citep{Bend-G-1999-PhD}, and so it likely the visual feedback received from GUI targets will affect the selection performance. All the targets being tested provide some form of immediate visual feedback from the button being visually depressed it to a tick appearing in the check box. Future study is needed to assess how visual feedback affects selection performance and what the most effective method of providing feedback is. \section{Conclusions} \label{sec-conclusions} The goal of the study was to assess the ability of a touch screen overlay in selecting different targets commonly presented to users in an information system. The touch screen overlay sits over a normal monitor and results in a gap between the overlay and monitor itself. This gap was shown to decrease the accuracy of the touch screen. The results showed that the touch screen overlay was both slower and less accurate than the mouse. The touch screen was found to have reasonable performance with large GUI items but poor performance with a smaller GUI items. The touch screen overlay did have comparable movement times to the mouse for medium and large sized targets. Throughput did not vary across device or size but did vary across target. Both selection devices had the same user preference except with the smallest target, check boxes, in which the mouse had a higher preference. The mouse was rated easier to make accurate selections with than the touch screen. The touch screen overlay also has worse arm, wrist and finger fatigue compared to the mouse. From these results we can conclude that the mouse had higher user satisfaction than a touch screen. In general we can conclude that a touch screen overlay with no external device (i.e. pen) is not an effective selection device for targets having a size of \unit[4]{mm} or smaller. When designing interfaces that will be used with a touch screen overlay, selection within the interface will be more efficient if the GUI items are larger than \unit[4]{mm}. Although the results showed that the touch screen overlay was not efficient and usable for selecting items with a size of \unit[4]{mm} or less, this may not be the case when a pen or some external device is used in conjunction with the touch screen overlay. In general there seems to a lack of research done in device assessment with touch screens and pens or other external devices. Further testing on touch screens used with an external device such as a pen may well show that a touch screen overlay is adequate and efficient for selecting small items (\unit[4]{mm} or less). % The Appendices part is started with the command \appendix; % appendix sections are then done as normal sections % \appendix % \section{} % \label{} % Bibliographic references with the natbib package: % Parenthetical: \citep{Bai92} produces (Bailyn 1992). % Textual: \citet{Bai95} produces Bailyn et al. (1995). % An affix and part of a reference: % \citep[e.g.][Ch. 2]{Bar76} % produces (e.g. Barnes et al. 1976, Ch. 2). \bibliographystyle{elsart-harv} \bibliography{IwC_paper} % \begin{thebibliography}{} % \bibitem[Names(Year)]{label} or \bibitem[Names(Year)Long names]{label}. % (\harvarditem{Name}{Year}{label} is also supported.) % Text of bibliographic item % \bibitem[]{} % % \end{thebibliography} \end{document}

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Gleeson_paper.tex 100755 → 0

% Template article for preprint document class `elsart'
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\begin{document}

\begin{frontmatter}

% Title, authors and addresses

% use the thanksref command within \title, \author or \address for footnotes;
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\title{Assessing the efficacy of a touch screen overlay as a selection
device using typical GUI targets}

% use optional labels to link authors explicitly to addresses:
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\author[info]{Matthew Gleeson},
\ead{matt\_gleeson@xtra.co.nz}
\author[info]{Nigel Stanger\corauthref{cor}},
\ead{nstanger@infoscience.otago.ac.nz}
\corauth[cor]{Corresponding author. Tel.: +64-3-479-8179; fax: +64-3-479-8311}
\author[hunt]{Elaine Ferguson}
\ead{elaine.ferguson@stonebow.otago.ac.nz}

\address[info]{Department of Information Science,}
\address[hunt]{Department of Human Nutrition, \\ University of Otago, PO Box 56, Dunedin, New Zealand}

\begin{abstract}

Touch screens are a popular method of interacting with kiosk-based
information systems, whereas typical desktop information systems use a
mouse as the primary selection device. In this paper we investigate the
efficacy of a touch screen overlay compared to a mouse, when selecting
typical graphical user interface (GUI) items in a desktop information
system. A series of tests were completed involving multi-directional
point and select tasks, and the results for both devices compared. The
results showed that the touch screen overlay was not suitable for
selecting GUI targets smaller than \unit[4]{mm}. The touch screen
overlay was slower and had a higher error rate than the mouse, but there
was no significant difference in throughput. Testers rated the mouse
easier to use and to make accurate selections, while the touch screen
overlay resulted in greater arm, wrist and finger fatigue. These results
suggest that a touch screen overlay is not a practical selection device
for desktop interfaces with small GUI targets.

\end{abstract}

\begin{keyword}
Touch screen overlay \sep
Mouse \sep
Selection device \sep
Fitts' Law \sep
Performance evaluation \sep
GUI items
\end{keyword}

\end{frontmatter}

% main text
\section{Introduction}
\label{sec-introduction}

The purpose of this paper is to investigate how effective a touch screen
overlay is compared to a mouse, when selecting typical graphical user
interface (GUI) items used in information systems. The target types
tested were buttons, check boxes, combo boxes and text boxes, which are
typical of those found in an interface for an information system. Each
target type was tested at three different sizes (see
Section~\ref{sec-GUI}).

The testing occurred in the context of a research project undertaken by
the Department of Human Nutrition at the University of Otago. This
project aimed to improve complementary food diets for toddlers in New
Zealand by designing a computer program to help formulate
population-specific food-based dietary guidelines for this high risk
group. The program was a rapid assessment decision-making tool, designed
specifically to assist nutrition programme planners in selecting
appropriate and improved home-based complementary foods
\citep{Ferg-E-2004}. The testing for our study took place within this
program environment.

% do we need this?
The remainder of the paper discusses the experimental design and the
results obtained. Section~\ref{sec-GUI} briefly describes the types of
targets used in the experiment, while Section~\ref{sec-evaluation}
describes the measures used to evaluate the selection devices. The
experimental design is described in Section~\ref{sec-method}.
Section~\ref{sec-analysis} describes how the data were analysed, and
Section~\ref{sec-results} presents the results of the experiment. Our
conclusions are presented in Section~\ref{sec-conclusions}.

\section{GUI targets}
\label{sec-GUI}

Since the 1980s much research has been put into developing human
computer interface guidelines. Today's interfaces are made up of a
combination of different targets that could include text boxes, check
boxes, combo boxes, list boxes, buttons, labels, tool bars etc. Results
of research undertaken by \citet{Sear-A-1991-IJMMS} showed that touch
screens can be successfully used as a selection device and can have
advantages over a mouse, even for small targets. But these results were
based on selecting arbitrary shapes and not typical GUI items commonly
found in today's GUIs.

To accurately test the performance of each selection device within the
experiment, varying sized targets were used. The sizes represent small,
medium and large for each target.

Apple has produced some guidelines for developers to follow when
designing interfaces for software \citep{Appl-2004-HIG}. In particular,
for each target three different sizes are given corresponding to large,
small and mini. The sizes used in this experiment were based on these
guidelines and are shown in Table~\ref{tab-target-sizes}.

\begin{table}
	\caption{Target sizes (width $\times$ height) used in the experiment.}
	\label{tab-target-sizes}
	\begin{tabular}{llll}
		\hline
		\textbf{Target type}	&	\textbf{Large}							&	\textbf{Medium}							&	\textbf{Small}	\\
		\hline
		Text box				&	$\unit[63]{mm} \times \unit[11]{mm}$	&	$\unit[55]{mm} \times \unit[8]{mm}$	&	$\unit[47]{mm} \times \unit[6]{mm}$	\\
		Combo box				&	$\unit[63]{mm} \times \unit[11]{mm}$	&	$\unit[55]{mm} \times \unit[8]{mm}$	&	$\unit[47]{mm} \times \unit[6]{mm}$	\\
		Button					&	$\unit[28]{mm} \times \unit[13]{mm}$	&	$\unit[24]{mm} \times \unit[9]{mm}$	&	$\unit[17]{mm} \times \unit[6]{mm}$	\\
		Check box				&	$\unit[9]{mm} \times \unit[9]{mm}$	&	$\unit[6]{mm} \times \unit[6]{mm}$	&	$\unit[4]{mm} \times \unit[4]{mm}$	\\
		\hline
	\end{tabular}
\end{table}

\section{Evaluation methods}
\label{sec-evaluation}

Each selection device was assessed using a combination of performance
and comfort measures.

\subsection{Performance}
\label{sec-evaluation-performance}

The dependent measure described by ISO 9241-9 is throughput
\citep{ISO-2000-9241-9}. Throughput is noted by
\citet{Mack-IS-2001-EHCI} as being a very important measure as it
reflects the efficiency of the user completing the task and it is a
measure of both speed and accuracy. The formula for calculating
throughput is given in the following equation:
\[
	\mathit{throughput} = \mathit{ID}_{e} / \mathit{MT}
\]
where
\[
	\mathit{ID}_{e} = \log_{2}(D / W_{e} + 1)
\]

$\mathit{ID}_{e}$ represents the index of difficulty and is defined in
terms of bits whereas movement time is defined in terms of seconds.
Therefore throughput is measured in bits per second (bps). $D$
represents the distance to the target. Throughput is used by the ISO
9241-9 standard as the performance measurement.

$W_{e}$ is the effective width and differs from the width of the
target. It reflects the spatial variability in the sequence of trials.
The formula for calculating effective width is given in the following
equation:
\[
	W_{e} = 4.133 \times \mathit{SD}_{x}
\]
	
$\mathit{SD}_{x}$ is the standard deviation in the selection
coordinates measured along the path to the target

Due to the nature of making a selection within a drop-down list, the
throughput for a combo box was adjusted to take into account the extra
distance to the desired list item.

Movement time is defined as time taken to successfully select a target.
Error rate is defined as the number of selections made outside of the
intended target. The error rate is the ratio of incorrect selections to
correct selections made, so an error rate of 100\% means as many errors
as correct selections.

Both movement time and error rate were left out of the ISO standard
9241-9 in terms of performance measurements but \citet{Doug-SA-1999-CHI}
recommend computing both measurements to give a more detailed
performance analysis for the selection device.

\subsection{Comfort}
\label{sec-evaluation-comfort}

A questionnaire was used to assess comfort and user satisfaction of each
selection device. The selection device assessment questionnaire
consisted of sixteen questions, eight of which were taken from the ISO
``Independent Questionnaire for Assessment of Comfort''
\citep{Doug-SA-1999-CHI}. The remaining eight questions related
specifically to the targets tested and the size of the targets tested.

In particular, the questionnaire aimed to assess the participants'
comfort in using the input device, the difficulty in accurately
selecting each of the targets and the preferable size of each target
using the input device.

The responses to twelve of the questions were based on a five point
ordinal scale. The remaining four questions referred to the
participant's preferred size for each target and were based on a three
point response corresponding to the sizes tested---small, medium and
large.

\section{Method}
\label{sec-method}

An experiment was carried out to test the effect of size for different
GUI targets with different selection devices. The experiment consisted
of completing a series of simple point and select tasks. Small, medium
and large sizes were tested for a combo box, text box, check box and
button. The selection devices tested were a touch screen overlay and
mouse. The test was multi-directional, meaning the target appeared in
more than one direction to the user. A variety of different sizes,
angles and distances were used for each target position.

\subsection{Participants}
\label{sec-method-participants}

A participant sample size of twenty four was used for the experiment.
Each participant was allocated to one of two groups with each group
using one selection device in testing.

The allocation of groups was based upon the results of a questionnaire
completed by each participant prior to testing. The purpose of the
questionnaire was to establish the level of computer, mouse and touch
screen experience of each participant. A participant was allocated to a
selection device group depending on what device they had the least
amount of experience with.

Due to the testing being done within a nutrition program environment,
the participants were all nutritionists (typical users of the program).
There were 21 female and 3 male participants with all having a
university level of education. All participants were unpaid volunteers.

\subsection{Apparatus}
\label{sec-method-apparatus}

Software written in Visual Basic.Net with Microsoft Studio 2003 was used
to implement the test as illustrated in
Figure~\ref{fig-test-screenshot}. Each test was connected to a Microsoft
Excel worksheet and the data corresponding to the relevant measures
(movement time, number of errors and selection coordinates) were
captured using the software and written to the Excel worksheet.

\begin{figure}
	\includegraphics{test-screenshot}
	\caption{Screenshot of the test with the target in the top left of
	the screen and the ``go'' button in the centre.}
	\label{fig-test-screenshot}
\end{figure}

The touch screen used in testing was a 17'' Magic Touch USB overlay
Model KTMT-1700-USB-M. This touch screen uses a lift-off touch strategy.
A touch screen overlay is a piece of equipment external to the monitor.
It sits in front of the monitor and behaves similarly to a touch screen
monitor. Using an overlay results in a gap between the overlay and the
monitor itself, this causes a slight discrepancy between where the user
touches the overlay and where the cursor is positioned on the screen.

The touch screen overlay was fitted to a Dell 15'' Flat Panel Model
E151FPb monitor. A flat panel monitor was chosen because it was noticed
during pre-testing that typical CRT monitors with rounded screens caused
a gap between where the users touched the screen and where the cursor
gets positioned. A flat panel is less likely to suffer this problem. The
device used for testing the mouse was a Dell PS/2 Optical Mouse Model
M071KC. Both devices were connected to a Dell Inspiron 7500 laptop
computer which ran the testing software.

\subsection{Procedure}
\label{sec-method-procedure}

The participant was initially given an introduction to the test by the
research observer. The introduction included a brief summary of the aims
of the study and what the test involved. The participant was also given
and told to read an instruction sheet which they had access to
throughout the duration of the test. After reading the instruction sheet
the participant had the opportunity to ask questions or raise any
issues.

Participants were instructed to complete each block of tests as quickly
as possible without losing accuracy. In between blocks of tasks,
participants were given the opportunity to rest for as long as they
wished. It was made clear to the participant that a task was only
complete once the target was successfully selected. Selecting the
button, check box and text box required the participant to simply click
on the target. The strategy required to select a combo box was
different. A combo box is a two-step target compared to the other
targets which were simple one-step targets. First the combo box must be
selected in order to show the list of items and then an item from the
displayed list must be selected. During the testing the participant was
instructed to always select the third item in the list when selecting a
combo box as illustrated in Figure~\ref{fig-combo-box}.

\begin{figure}
	\caption{The two-step action required to select the combo box.}
	\label{fig-combo-box}
\end{figure}

The participant was then instructed to complete a practice task
involving fifteen random trials of the same point and select tasks used
in the test. This brought all participants to a minimal level of
experience with their selection device. This also meant each participant
knew how to correctly select each device including the combo box.

At the conclusion of the test the participant was required to fill out a
questionnaire regarding comfort and user satisfaction with the selection
device used.

\subsection{Design}
\label{sec-method-design}

A mixed design experiment was used with the selection device as a
between-subjects factor. The independent (between-subject) variables
were:

\begin{itemize}

\item Target Type (text box, combo box, button and check box)

\item Target Size (large, medium and small)

\item Target Distance (\unit[40]{mm}, \unit[80]{mm} and
	\unit[160]{mm})

\item Target Angle ($45^{\circ}$, $135^{\circ}$, $225^{\circ}$
	and $315^{\circ}$)

\item Trial (1 to 144)

\item Block (1 to 6)

\end{itemize}

The entire test was divided into six blocks. Each block contained every
possible combination of target type (4), size (3), angle from starting
point (4) and distance (3). There were 144 trials in each block and the
entire experiment per participant consisted of a total of 864 trials
(six blocks of 144 trials).

The different combinations of target location on the screen are
illustrated in Figure~\ref{fig-target-positions} and are a combination
of distance and the angle from the starting point.

\begin{figure}
	\includegraphics[scale=0.85]{target-positions}
	\caption{Positions of targets tested. The black box represents the
	starting point and the rounded rectangles represent the target
	positions.}
	\label{fig-target-positions}
\end{figure}

The dependent variables within the experiment were throughput (TH),
movement time (MT) and error rate (ER).

The index of difficulty was ascertained for each task using the
combination of distance and width. This showed that the test had a range
of Fitts' Index of Difficulty values from 0.7 bits (\unit[63]{mm} width
and \unit[160]{mm} distance) to 5.4 bits (\unit[4]{mm} width and
\unit[40]{mm} distance). The ordering of the target size presented to
the participant within each block in the experiment was deliberately set
to large, medium and lastly small to compensate for learning.

\section{Analysis}
\label{sec-analysis}

The data collected from the software included movement time, error rate
and throughput and was used to evaluate selection device performance. A
mixed design repeated measures analysis of variance model (MANOVA) was
used for movement time and throughput to examine within subject
differences in target and size, as well as between subject differences
in device. A Greenhouse and Geisser correction of the F-ratio was used
whenever the Mauchly's test results showed that assumptions of
sphericity were violated.

Post hoc tests, for multiple comparisons, were made using the Bonferroni
method. Due to the skew observed in the error rate data inter-device
difference in error rates were assessed using the Mann-Whitney U Test.

The comfort questionnaire was based on a five point ordinal scale. In
general five indicated a bad rating. Because of the small data size, a
Mann-Whitney (non-parametric) test was used. All statistical analyses
were performed using SPSS version 11.0.

\section{Results and discussion}
\label{sec-results}

\subsection{Adjusting for learning}
\label{sec-results-learning}

\citet{Doug-SA-1999-CHI} recommend that input device studies should
apply a repeated measures paradigm and test for learning effects. The
effects of learning have been shown to affect movement time and accuracy
\citep{Doug-SA-1999-CHI}.

From analysing the results of movement time and throughput over each
test block, it is clear for the combo box and check box that learning
occurs from the first to second block with the touch screen (as seen in
Figure~\ref{fig-movement-time-learning}). Due to prior experience, no
learning is observed with the mouse. No learning occurs with the text
box or button most likely due to their large size and simple selection
behaviour.

\begin{figure}
	\caption{Learning is displayed for movement time by device and block
	for the combo box and check box.}
	\label{fig-movement-time-learning}
\end{figure}

Helmhert contrasts show that the differences between blocks become
non-significant after block 1 $(p > 0.05)$. For movement time of the
check box, the effect of block * device was significant $(F(1.608,
1385.960) = 4.763, p < 0.05)$.

Using Helmhert contrasts, the differences between blocks become
non-significant after block 1 $(p > 0.05)$. This again shows that
there was learning involved in block 1.

To account for learning with the combo and check box, results from block
6 only will be used to calculate the performance measures of measurement
time, throughput and error rate. The results from block 6 alone would
give a good measure of performance.

\subsection{Movement time}
\label{sec-results-movement}

The results showed that the mouse had an overall movement time of
\unit[1.3]{s} for all targets compared to \unit[1.6]{s} for the touch
screen. Therefore we can conclude that a mouse is on average 15.2\%
faster than a touch screen overlay. This is interesting as
\citet{Sear-A-1991-IJMMS} found that the movement time between a mouse
and touch screen (monitor) was similar for rectangle targets larger than
\unit[2]{mm}. Therefore the nature of the two types of touch screen
(overlay and monitor) may affect the movement time associated with the
type of touch screen. It is also likely that due to the loss of accuracy
found with the overlay during testing, the touch screen monitor will
have a lower movement time compared to the touch screen overlay.

The movement times for each target showed that the text box has the
fastest movement time, followed by the button, the check box and then
the combo box. These results are illustrated in
Figure~\ref{fig-movement-time} and follow Fitts' Law in that the largest
target (the text box) had the fastest movement time.

\begin{figure}
	\includegraphics{movement-time}
	\caption{Movement time for each target type across both devices and
	all sizes.}
	\label{fig-movement-time}
\end{figure}

As expected, the combo box had the slowest movement time due to the
two-click behaviour involved in making a selection. The sizes of the
combo box were exactly the same as the text box but movement time was
119\% slower. Thus the extra movement of selecting an item from the drop
down list increases the movement time involved with the combo box
dramatically. As the distance to the list item is relatively short from
the main combo box area, the significant increase in movement time is
therefore most likely due to users making more errors.

A touch screen has similar movement time to a mouse for medium and large
sized targets. But for the small targets, the touch screen was 67\%
slower than the mouse. The only time where the touch screen was found to
be faster than the mouse was with the largest target type - the large
text box.

The movement time for the small check box with the touch screen was 69\%
slower than that of the mouse. The small check box was the smallest item
tested having a width of \unit[4]{mm} and height of \unit[4]{mm}. We can
conclude that the touch screen was not efficient for selecting targets
as small as \unit[4]{mm}. \citet{Sear-A-1991-IJMMS} showed a touch
screen has similar movement time to the mouse for targets as small as
\unit[2]{mm}. Although a touch screen monitor can be used with targets
as small as \unit[2]{mm}, a touch screen overlay should only be used for
targets with a size of greater than \unit[4]{mm}. The results from the
error rate analysis also support this

\subsection{Throughput}
\label{sec-results-throughput}

Throughput for the mouse was \unit[1.238]{bps}, slightly higher than the
1.215 bps throughput for the touch screen. The device by itself was
shown not to have a significant effect on throughput $(F(1, 22) = 0.02,
p > 0.05)$. Throughput did not vary for size but throughput did vary
depending on target type $(F(2.07, 45.55) = 4.77, p < 0.001)$. Check
boxes had the highest throughput rate of \unit[1.967]{bps} (sd = 0.720).
This is interesting as the check box was shown to have the second worst
movement time and the worst error rate (see
Figure~\ref{fig-throughput}).

\begin{figure}
	\includegraphics{throughput}
	\caption{Throughput for each target type across both devices and all
	sizes.}
	\label{fig-throughput}
\end{figure}

Upon further investigation it was seen that the movement time for the
check box was in fact in the middle range of all targets and due to its
small size it had a high index of difficulty. Therefore these two
factors are the reason for the check box having such a high throughput
rate. The combo box had the worst throughput of \unit[0.501]{bps} (sd =
0.213). The index of difficulty was not very high for the combo box and
so it was due to its high movement time that the combo box had such a
low throughput rate.

The overall throughput rate of \unit[1.2]{bps} for the mouse is much
lower compared with previous research. A study by
\citet{Doug-SA-1994-SIGCHI} showed a mouse had a throughput rate of
\unit[4.15]{bps}. \citet{Mack-IS-1991} compared three devices (mouse,
tablet and trackball) using four target sizes (8, 16, 32 and 64 pixels)
over two different types of tasks: pointing and dragging. The throughput
for the mouse in this case was 4.5 bps. This may indicate the level of
difficulty with selection within this experiment is a lot higher than
within previous research. This could be due to the selection of GUI
targets instead of arbitrary rectangle targets.

\subsection{Error rate}
\label{sec-results-errorrate}

The error rate for the mouse was only 2.7\% which is consistent with
previous studies. The touch screen on the other hand had an error rate
of 60.7\%. \citet{Sear-A-1991-IJMMS} found that the touch screen had
an average error rate of 49\% but this was across much smaller targets.
This suggests there is a loss in accuracy from using a touch screen
overlay compared to a touch screen monitor.

The check box had a significantly high amount of errors; 78.5\% for all
sizes and both devices and in particular, 312.5\% for the small check box
with the touch screen. A 100\% error rate indicates one wrong selection
made for every correct selection. The touch screen incurred the majority
of the errors. With the check box the mouse had an error rate of 4.4\%
and the touch screen had an error rate 152.5\%. The distinguishing factor
of the check box compared to the other targets was its small size. We
can conclude from this that the touch screen overlay has inaccuracy in
selecting small targets (\unit[4]{mm} or less).

Buttons and text boxes had much lower error rates compared to that of
the check box and combo box (as seen in Figure~\ref{fig-error-rate}). As
buttons and text boxes also had low movement times, we can conclude that
these two targets have very good overall performance.

\begin{figure}
	\includegraphics{error-rate}
	\caption{Error rate for each target type across both devices and all
	sizes.}
	\label{fig-error-rate}
\end{figure}

\subsection{Comfort}
\label{sec-results-comfort}

In terms of accurate pointing the mouse (2.083) was rated easier than
the touch screen (3.000). These differences were statistically
significant $(p < 0.01)$. The responses regarding the question on
neck, wrist and arm fatigue showed that the touch screen had a high
rating (4.083), whereas the mouse was rated in the midpoint range
(3.167). These differences were statistically significant $(p < 0.5)$.
The final question rated the overall difficulty in using the selection
device. The mouse (4.250) was rated easier to use than the touch screen
(3.333). These differences were statistically significant $(p <
0.05)$.

For user satisfaction with the touch screen, both the text box and
button were rated easy to accurately select and the preferred size was
both the large size and the medium size. This feedback is consistent
with the data collected in that text boxes and buttons have short
movement time and low error rates (easy to accurately select).

The combo box was rated in the midpoint range in terms of ease in
accurately selecting with the touch screen and the check box was rated
very hard to select. Three quarters of the touch screen users preferred
to select the large size combo boxes and check boxes and this reflects
the poor error rates and movement times associated with these two
targets with the touch screen overlay.

The participants using the mouse rated the text box and button easy to
accurately select with the medium and large sizes being the most
preferred. Both the combo box and check box were rated harder to select
than the button and text box with the check box having the worst rating.
Like the touch screen overlay, the preferred size for the combo box and
check box was large.

One participant noted the lack of arm support for targets at the top of
the screen. This is an interesting comment because the nature of using a
touch screen means the users arm might be raised off the desk and be
self supporting when selecting items towards the top of the desktop
screen.

Another suggestion was making the target change colour when the cursor
is located above it. This is a similar concept to that of interactive
rollover items commonly used in web pages. Auditory feedback has been
shown to affect the speed and accuracy when making a selection
\citep{Bend-G-1999-PhD}, and so it likely the visual feedback received
from GUI targets will affect the selection performance. All the targets
being tested provide some form of immediate visual feedback from the
button being visually depressed it to a tick appearing in the check box.
Future study is needed to assess how visual feedback affects selection
performance and what the most effective method of providing feedback is.

\section{Conclusions}
\label{sec-conclusions}

The goal of the study was to assess the ability of a touch screen
overlay in selecting different targets commonly presented to users in an
information system. The touch screen overlay sits over a normal monitor
and results in a gap between the overlay and monitor itself. This gap
was shown to decrease the accuracy of the touch screen.

The results showed that the touch screen overlay was both slower and
less accurate than the mouse. The touch screen was found to have
reasonable performance with large GUI items but poor performance with a
smaller GUI items. The touch screen overlay did have comparable movement
times to the mouse for medium and large sized targets. Throughput did
not vary across device or size but did vary across target. Both
selection devices had the same user preference except with the smallest
target, check boxes, in which the mouse had a higher preference. The
mouse was rated easier to make accurate selections with than the touch
screen. The touch screen overlay also has worse arm, wrist and finger
fatigue compared to the mouse. From these results we can conclude that
the mouse had higher user satisfaction than a touch screen.

In general we can conclude that a touch screen overlay with no external
device (i.e. pen) is not an effective selection device for targets
having a size of \unit[4]{mm} or smaller. When designing interfaces that
will be used with a touch screen overlay, selection within the interface
will be more efficient if the GUI items are larger than \unit[4]{mm}.

Although the results showed that the touch screen overlay was not
efficient and usable for selecting items with a size of \unit[4]{mm} or
less, this may not be the case when a pen or some external device is
used in conjunction with the touch screen overlay. In general there
seems to a lack of research done in device assessment with touch screens
and pens or other external devices. Further testing on touch screens
used with an external device such as a pen may well show that a touch
screen overlay is adequate and efficient for selecting small items
(\unit[4]{mm} or less).

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\end{document}

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SHELL=/bin/sh GRAPHICS:=test-screenshot.eps target-positions.eps \ throughput.eps movement-time.eps error-rate.eps IwC_paper.pdf: IwC_paper.ps IwC_paper.ps: IwC_paper.dvi IwC_paper.dvi: IwC_paper.tex $(GRAPHICS) latex $< latex $< IwC_paper.tex: IwC_paper.bbl test-screenshot.eps: test-screenshot.tif throughput.eps: barchart.plo ploticus -eps -tightcrop -o $@ $< yrange="0 2.25" ystubfmt="%2.1f" ylabel="Throughput (bps)" fieldname=throughput movement-time.eps: barchart.plo ploticus -eps -tightcrop -o $@ $< yrange="0 2.25" ystubfmt="%2.1f" ylabel="Movement time (s)" fieldname=movement_time error-rate.eps: barchart.plo ploticus -eps -tightcrop -o $@ $< yrange="0 100" ystubfmt="%g" ylabel="Error rate (%)" fieldname=error_rate clean: rm -f .aux .bbl .blg .log .dvi .ps %.bbl: %.bib latex $* bibtex $* %.pdf: %.ps ps2pdf $< $@ %.ps: %.dvi dvips -o $@ $< %.dvi: %.tex latex $< latex $< %.eps: %.tif convert $< $@ %.eps: %.sxd $(error Re-export $@ from $<)

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#musthave yrange #musthave ylabel #musthave fieldname #musthave ystubfmt #proc settings units: cm #proc getdata delim: comma fieldnameheader: yes data: target_type, throughput, movement_time, error_rate Text Box, 0.958, 0.972, 7.767 Button, 1.505, 1.035, 7.333 Check Box, 1.967, 1.638, 78.467 Combo Box, 0.501, 2.130, 33.467 #proc areadef areaname: slide yrange: @yrange xrange: 0 5 #proc yaxis: stubs: inc stubformat: @ystubfmt stubdetails: size=10 label: @ylabel labeldetails: style=B size=10 adjust=-0.2,0 grid: color=gray(0.7) #proc xaxis: stubs: datafields=target_type stubdetails: style=B size=10 tics: none #proc bars lenfield: @fieldname color: blue labelword: @@N labeldetails: size=10 adjust=0,0.2

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