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Perceived Personality and Uses of Fonts -- We Need Your Input!

by A. Dawn Shaikh, Jeremy Slocum, and Zach Zaccagani

http://www.shaikh.us/fontstudy/

Often credited with creating a first impression, fonts are classified according to unique typographical features (serif, sans serif, etc) and overall appearance. The combination of appearance and typographical features frequently lead graphic artists and typographers to describe typefaces using personality traits (“less cuddly, more assertive,” Berry, 2004). In a recent BBC audio program (Peacock, 2005), fonts were depicted as feminine and masculine, among other traits. Typographers and designers are often interested in the typeface personality or “typographic allusion” which refers to “the capacity of a typestyle to connote meaning over and above the primary meaning which is linguistically conveyed by words” (Lewis & Walker, 1989, p. 243).

Studies have investigated the perceived personality of fonts for printed text; however, similar studies have not been conducted regarding onscreen text. We are investigating the perceived personalities and uses of a variety of fonts used onscreen.

As subscribers to Usability News, we thought it would be interesting to include your data in our analyses.  We are eager to include diverse populations to better generalize our findings to those who are designing and developing for digital media.

Please take the time (30-45 minutes) to complete our online survey by clicking the following link (this link will open a new browser window):

Click on this link to take the survey at http://www.shaikh.us/fontstudy/

We thank you for your time and your interest. Results of the survey will be posted in our next issue of Usability News.

REFERENCES

Berry, J.D. (2004). Now read this: The Microsoft ClearType font collection. Seattle, WA: Microsoft Corporation.

Lewis, C., & Walker, P. (1989). Typographic influences on reading. British Journal of Psychology, 80, 241-257.

Peacock, I. (Speaker). (2005). From Arial to Wide Latin (Radio Broadcast). London: BBC Radio. (Available online: http://www.bbc.co.uk/radio4/science/fromarialtowidelatin.shtml)

The Effects of Line Length on Reading Online News

By A. Dawn Shaikh

Summary: This study examined the effects of line length on reading speed, comprehension, and user satisfaction of online news articles. Twenty college-age students read news articles displayed in 35, 55, 75, or 95 characters per line (cpl) from a computer monitor. Results showed that passages formatted with 95 cpl resulted in faster reading speed. No effects of line length were found for comprehension or satisfaction, however, users indicated a strong preference for either the short or long line lengths.

INTRODUCTION

The amount of text-based information available online is steadily increasing. Universities are offering more online classes; publishers are releasing more online books and journals; and consumers are gathering online news, weather, and product information daily. Therefore, the examination of the factors that influence the readability of online text is very important. In a recent survey, Shaikh and Chaparro (2004) evaluated the reading habits of Internet users across five document types (journal articles, news, newsletters, literature, and product information) and found that users preferred to read journal articles in printed form, but other documents such as online news, newsletters, and product reviews in online formats.

Research has shown that many aspects of physical layout of online text impact reading performance and satisfaction; Dyson (2004) gives an excellent review. One such factor that has been studied is line length, or the number of characters presented per line of text. Research investigating line length for online text has been inconclusive. Several studies found that longer line lengths (80 – 100 cpl) were read faster than short line lengths (Duchnicky and Kolers, 1983; Dyson and Kipping, 1998). Contrary to these findings, other research suggests the use of shorter line lengths. Dyson and Haselgrove (2001) found that 55 characters per line were read faster than either 100 cpl or 25 cpl conditions. Similarly, a line length of 45-60 characters was recommended by Grabinger and Osman-Jouchoux (1996) based on user preferences. Bernard, Fernandez, Hull, and Chaparro (2003) found that adults preferred medium line length (76 cpl) and children preferred shorter line lengths (45 cpl) when compared to 132 characters per line.

Purpose

Shaikh and Chaparro (2004) found that 62% of respondents preferred to read news onscreen rather than on paper. The goal of this study was to investigate the effects of line length on reading performance of online news articles. This study investigated the effects of four line lengths (35, 55, 75, and 95 cpl) on reading speed, comprehension, and satisfaction.

METHOD

Participants

Twenty college students from a Midwestern university volunteered to participate in the experiment and were compensated with $25. All participants had 20/40 or better unaided or corrected vision. Participants reported visiting websites daily, had experience reading online, and were regular users of the Internet.

Materials

News articles with approximately 375 words (M = 367.9) were selected from MSN® and Yahoo® news. Average reading level for each passage was at the 12.0 grade level. The news articles covered a variety of topics ranging from computer viruses to innovative automobiles. The passages used Arial 10-point font with 12-point interlinear spacing between lines. Each paragraph was separated with an additional line break as is typically done on web pages. Hyphenation was not used in the text.

A total of 19 comprehension questions were written for each article including one title, main idea, and structure question and three factual and incidental questions, and 10 recognition questions (see Dyson & Haselgrove, 2001). A background questionnaire was used to collect demographic information as well as computer and Internet usage patterns. A Reading Satisfaction Evaluation consisting of 11 questions on a 7-point Likert Scale collected user reactions to the passage layout, perceived eyestrain, and fatigue. A Post-Experiment Questionnaire was used to determine layout preference.

Procedure

Following the completion of the consent form and the background questionnaire, participants were seated approximately 52 cm from the screen. The pages of text were displayed using Internet Explorer 6.0 in full screen mode to reduce distractions of tool bars, scroll bars, and menu items; paging (with no scrolling) was used to navigate the passages. The HTML pages contained “Next” and “Previous” buttons that users clicked with the mouse to navigate. All HTML pages were accessed from the computer hard drive to minimize download time.

Participants read a total of eight short news articles presented in counterbalanced order for line length. Two news articles were presented in each line length. Participants completed the set of comprehension questions after reading each passage. The Reading Satisfaction Questionnaire was given after each set of short passages. Following the last passage, the Post-Experiment Questionnaire was administered.

RESULTS

Reading Speed. Reading time was converted to words per minute. Results from a one-way within subjects ANOVA showed that there was a significant main effect of line length on reading speed, F(3, 57) = 3.45, p = .02, η² = .15. The 95 cpl (M = 178.82, SD = 41.83) articles were read significantly faster than any of the other line lengths (35 cpl M = 167.21, SD = 33.66; 55 cpl M = 167.38, SD = 33.96 ; 75 cpl M = 169.44, SD = 33.48) (Figure 1).

Figure 1. The effect of line length on reading speed.

Reading Efficiency. Reading efficiency was computed by multiplying the reading speed by the percent correct on the comprehension questions. Results of a one-way within subjects ANOVA showed a marginally significant effect of line length, F(3, 57) = 2.68, p = .06, η² = .12. Significant differences were found between 35 cpl and 95 cpl with the 95 cpl being more efficient.

Overall Comprehension. To compute an overall comprehension score, raw scores were adjusted per question type to yield a total comprehension score of 6 (based on the six types of questions). In doing this adjustment, each type of question was worth a total of one point. Results from a one-way within subjects ANOVA showed no effect of line length on overall comprehension.

Comprehension by Question Type. Results from a one-way within subjects ANOVA revealed a significant main effect of question type on comprehension, adjusted F(3.98, 75.69) = 10.193, p = .001, η² = .35. Participants scored significantly lower on the structure questions than title, main idea, and factual questions across all line lengths (Figure 2).

Figure 2. The effect of question type on comprehension.

Satisfaction & Preference. There was no main effect of line length on overall satisfaction. There were also no significant differences in preference. However, 60% of participants chose either 35 cpl (30%) or 95 cpl (30%) as the most preferred line length. On the other hand, 100% of participants chose either 35 cpl (45%) or 95 cpl (55%) as the least preferred line length.

DISCUSSION

This study examined the effects of line length on reading performance. Reading rates were found to be fastest at 95 cpl. Readers reported either liking or disliking the extreme line lengths (35 cpl, 95 cpl). Those that liked the 35 cpl indicated that the short line length facilitated “faster” reading and was easier because it required less eye movement. Those that liked the 95 cpl stated that they liked having more information on a page at one time. Although some participants reported that they felt like they were reading faster at 35 cpl, this condition actually resulted in the slowest reading speed.

Circulation of newspapers at 814 of America’s largest daily newspapers declined 1.9% from September 2004 to March 2005 (Shin, 2005). This decline is part of a 20-year trend in newspaper circulation and is due, in part, to the increased use of the Internet and other forms of media (cable, satellite, etc). As users continue to choose online news sources, it is imperative to understand factors that contribute to improving the overall online reading experience for news. Participants were able to read news articles significantly faster while maintaining high reading efficiency using 95 cpl. Despite the fact that there were no differences in satisfaction scores, a line length that supports faster reading could impact the overall experience for users of online news sources.
 

Note: For additional information on this study, please see the proceedings of the Human Factors and Ergonomics Society's 49^th (2004) Annual Meeting, Orlando, FL.

REFERENCES

Bernard, M. L., Fernandez, M., Hull, S., & Chaparro, B. S. (2003). The effects of line length on children's and adults' perceived and actual online reading performance. Proceedings of the Human Factors and Ergonomics Society 47th Annual Meeting, 1375-1379.

Duchnicky, R. L., & Kolers, P. A. (1983). Readability of text scrolled on visual display terminals as a function of window size. Human Factors, 25, 683-692.

Dyson, M. C. (2004). How physical text layout affects reading from screen. Behaviour and Information Technology, 23, 377-393.

Dyson, M. C., & Haselgrove, M. (2001). The influence of reading speed and line length on the effectiveness of reading from screen. International Journal of Human-Computer Studies, 54, 585-612.

Dyson, M. C., & Kipping, G. J. (1998). The effects of line length and method of movement on patterns of reading from screen. Visible Language, 32, 150-181.

Grabinger, R. S., & Osman-Jouchoux, R. (1996). Designing screens for learning. In H. van Oostendorp & S. de Mul (Eds.), Cognitive aspects of electronic text processing. Norwood, NJ: Ablex Publishing Corporation.

Shaikh, A. D., & Chaparro, B. S. (2004). A survey of online reading habits of Internet users. Proceedings of the Human Factors and Ergonomics Society 48th Annual Meeting, 875-879.

Is Multiple-Column Online Text Better? It Depends!

By J. Ryan Baker

INTRODUCTION

Large high-resolution displays can now have resolutions of over 1900 pixels, resulting in extremely long lines of text. One way to resolve the problem of very long text lines is to divide the text into multiple columns, thus decreasing the width of each individual line. Some sites even allow users to customize pages into one, two, or three columns (for an example, see http://www.travelyellowstone.com).

To date, research investigating the optimal use of line length, multiple columns, and text justification is inconclusive. Longer line lengths typically result in faster reading times (Duchnicky and Kolers, 1983; Dyson and Kipping, 1997; Dyson and Kipping, 1998; Dyson and Haselgrove, 2001), but research suggests medium to short line lengths typically may result in higher comprehension (Tinker, 1963; de Brujin, de Mal, & van Oostendorp, 1992; Chaparro et al., 2004). In terms of columnar text, the research supports both long single columns of text (Dyson and Kipping, 1998), and multiple short columns (Lam et al., 2000) while preference seems to lie towards multiple short columns (Bouma, 1980; Dyson and Kipping, 1998; Andreyev & Martynov, 2000).

There has been little research done on the impact of text justification on online reading. Priestly (1991) and Hartley (1986) suggest that printed materials should be left-justified because the intra-word spacing remains constant, which helps slower readers identify words more quickly. However, Priestly notes that the question of whether instructional material is best presented in a full-justified or left-justified format is still debated. Full justification requires that both margins be aligned. To accomplish this, large spaces must sometimes be made between words, or words must be hyphenated, both of which can reduce reading speed and comprehension. Left-justified text is generally preferred because it removes the need for hyphenated words.

In summary, the major findings regarding line length, justification, and multi-column displays and online reading have been:

• Longer line lengths generally facilitate faster reading speeds.
• Shorter line lengths result in increased comprehension.
• The optimal number of characters per line is between 45 and 65.
• Paging through online text generally results in better comprehension than scrolling.
• Reading speed is faster for both single and multiple columns, but preference is for multiple short columns.
• Left-justified text is read faster than full-justified text.

This study investigated the effects of multi-column displays and justification on reading performance and satisfaction of an online narrative passage.

METHOD

In this study, participants read text displayed either as a single column (90 CPL), a 2-column format (45 CPL each), or 3-column format (30 CPL each) presented using either full or left justification.

Participants 

Sixty-six undergraduate students with normal or corrected vision participated in the study. Participants had an average age of 22.8 years. Data were collected on the participants’ amount of online reading experience and types of materials read online. Eighty-nine percent reported using the Internet a few times per week or more. Forty-eight percent of participants indicated that they read online for two to six hours per week, 15% reported reading online for seven to fourteen hours per week, and nine percent reported reading online for fifteen hours or more per week.

Materials

H.H. Munro’s (“Saki”) short story “The Lumber Room,” a passage of 2191 words, was used as the reading material. The story had a readability score of 9.6 on the Flesch-Kincaid Grade Level statistic. Six versions of the story were created: a single column with a width of 90 CPL, a 2-column format with column widths of 45 CPL, and a 3-column format with column widths of 30 CPL, each presented in either a full or left justification format (See Figures 1 – 6). 

Figure 1. One-Column Full-Justified Condition

Figure 2. Two-Column Full-Justified Condition

Figure 3. Three-Column Full-Justified Condition

Figure 4. One-Column Left-Justified Condition

Figure 5. Two-Column Left-Justified Condition

Figure 6. Three-Column Left-Justified Condition

Passages were presented on Dell Dimension 4600C desktop with a 17” display running 1024 x 768 screen resolution. Each of the passages was presented on six consecutive pages; users clicked on an arrow at the bottom of each page to advance to a subsequent page or return to a previous page. No scrolling was required. Users read the passages at a distance of approximately 60 cm and passages were displayed in 10pt Verdana font.

Procedure

The design of this study was a 2 x 3 randomized block design with matched subjects. Column format (single, 2-column, and 3-column) and Justification (Full, Left) were the independent variables.

Participants were matched across conditions based on reading speed predetermined by a online reading test. Participants were then asked to read the short story displayed in one of the six different column conditions (one, two, or three columns, in either a Full or Left-justified format). After reading the story, participants answered sixteen comprehension questions (fifteen multiple-choice and one recall question with ten units) about the story, modeled after those used by Dyson and Haselgrove (2001). The dependent variables of interest were:

• Reading speed, measured by the amount of time taken to read each story (converted to words per minute);
• Reading efficiency, measured by multiplying words per minute by the percentage correct on overall comprehension;
• Reading comprehension, measured by the number of questions about each passage answered correctly, as well as the type of questions answered correctly;
• Satisfaction, measured by participant response to a satisfaction questionnaire.

 RESULTS

Reading Speed and Reading Efficiency

A 2x3 randomized block ANOVA found a significant interaction for justification x number of columns, F(2,20) = 3.812, p = .040. η² = .276, 1 – β = .624 (see Table 1). Post-hoc Tukey’s HSD comparisons showed that reading speed was significantly faster for two-column full-justified (M=269.33) than for one-column full-justified, (M=224.31), and significantly faster for one-column left-justified (M=266.43) than for one-column full-justified (M=224.31), or three-column full-justified (M=227.60) (see Figure 7).

Table 1. Reading Speed Means and Standard Deviations
 

Figure 7. Participant Reading Speed

A 2x3 randomized block ANOVA found no significant main effects for reading efficiency though an interaction approaching significance for justification x number of columns was found, F(2,20) = 3.124, p=.066. η² = .238, 1 – β = .534.  

Reading Comprehension

To compute an overall comprehension score, raw scores were adjusted per question type to yield a total comprehension score of 6 (based on the six types of questions). A 2x3 randomized block ANOVA found no significant main effects or interaction for either justification or number of columns for total comprehension (Table 2).

Table 2. Total Comprehension Means and Standard Deviations

Satisfaction

A 2x3 randomized block ANOVA found no significant main effects or interaction on overall satisfaction.

Examination of Fast versus Slow Readers

Originally, participant reading rate was not considered as an independent variable in this study. Dyson & Kipping (1997) propose that fast and slow readers use different reading strategies that may impact comprehension. They suggest that faster readers are able to scan narrow columns more efficiently and increase their comprehension. Based on this idea, the fastest readers in this study were compared to the slowest readers by condition. Reading speed, reading comprehension, reading efficiency, and reading satisfaction were then analyzed using a 2 x 2 x 3 ANOVA.

In general, results from these analyses indicate that the fastest readers benefited most from the 2-column justified text, while the slowest readers performed best at the 1-column left justified format (see Figure 8). In addition, satisfaction levels were found to be higher for the fast readers at the two-column full-justification condition than the other conditions.

Figure 8. Average Reading Speed for Fast and Slow Readers

DISCUSSION

The purpose of this study was to examine how multiple columns and text justification impact online reading in terms of reading speed, comprehension, and satisfaction of a narrative passage. Results from this study showed that reading speed was significantly faster for two-column full-justified text than for one-column full-justified text. Post-hoc analyses showed that it was the fastest readers that benefited the most from this format.

Slower readers showed their fastest reading and highest reading efficiency at the one-column left-justification condition. This may be because the very short lines impeded the reader’s ability to take in an optimal amount of information at each fixation. Gutherie & Wigfield (2000) assert that a slow reader may lose all information about the beginning of a sentence from short-term memory before he or she has read to the end. Slow readers may also have had difficulty “keeping their place” with the multiple line length conditions for this same reason.

Numerous factors contribute to the ease of online reading. As more types of documents become digital, and more people read from online sources, finding the optimal presentation of these materials will become critical in the near future. Reading and comprehension tests are moving into the digital domain and studies such as this one can help researchers and designers know which types of layouts are best for their audience. A two-column full-justified format is best for situations where fast readers are the primary audience. However, for more a more equalized setting, a layout with no strong advantages or disadvantages may be best.

The results of this study suggest that there is not one best way to present text online. Although fast readers performed best at the two-column full-justified condition, slow readers benefited from a single column non-justified layout. This suggests that users should have the option to customize web pages to suit their reading needs. To date, there are very few sites that allow users to tailor information displays into multiple columns or adjust justification styles or font types. Giving users these options can help increase their reading speed with the text, and eventually may lead to a more optimal online reading experience.

REFERENCES

Andrevey, V., & Martynov, A. (2000). Effects of splitting text into multiple columns. Dept of Computer Science Class Project, Univ. of Maryland, College Park, MD. Available at: http://www.otal.umd.edu/SHORE2000/multicol/index.html

Bouma, H. (1980). Visual reading processes and the quality of text displays. In Ergonomic Aspects of Visual Display Terminals, E. Grandjean and E. Vigliani (Eds.) Taylor & Francis: London pp. 101-114.

Chaparro, B., Baker, J.R., Shaikh, A.D., Hull, S., & Brady, L. (2004). Reading online text: A comparison of four whitespace layouts. Usability News, 6.2. Available at: http://psychology.wichita.edu/surl/usabilitynews/62/whitespace.htm 

De Brujin, D., De Mul, S., & Van Oostendorp, H. (1992). The influence of screen size and text layout on the study of text. Behaviour and Information Technology, 11, 71-78.

Duchnicky, J.L., & Kolers, P.A. (1983). Readability of text scrolled on visual display terminals as a function of window size. Human Factors, 25, 683-692.

Dyson, M.C., & Haselgrove, M. (2001), The influence of reading speed and line length on the effectiveness of reading from a screen. International Journal of Human-Computer Studies, 54, 585-612.

Dyson, M.C., & Kipping, G.J. (1998), The effects of line length and method of movement on patterns of reading from screen. Visible Language, 32, 150-181.

Dyson, M.C., & Kipping, G.J. (1997), The legibility of screen formats: Are three columns better than one? Computers & Graphics, 21, 703-712.

Hartley, J. (1986). Designing Instructional Text. 2nd edition. Kogan Page, London.

Lam, K., Lam, Y., Liu, J., & Shin, U.G. (2000). Reading Comprehension and Rate: One Column vs. Three Columns. Dept of Computer Science Class Project, Univ. of Maryland, College Park, MD http://www.otal.umd.edu/SHORE2000/columns/index.html

Priestly, W. (1991). Instructional typographies using desktop publishing techniques to produce effective learning and training materials. Australian Journal of Educational Technology, 7, 153-163. Available at: http://www.ascilite.org.au/ajet/ajet7/priestly.html

Tinker, M.A. (1963). Legibility of type. Ames, IA: The Iowa State University Press.

Hotspots and Hyperlinks: Using Eye-tracking to Supplement Usability Testing

By Mark C. Russell

INTRODUCTION

Eye-tracking has been used in usability testing for many years, beginning primarily with cockpit design testing (Fitts, Jones and Milton, 1950). Such early studies were valuable in establishing some assumptions about the relationships between eye-movement data and the cognitive activity of a user. Frequency of fixations was assumed to be related to the importance of the control, while the duration of fixations was related with ease of interpreting information.

In recent years, eye-tracking has been adapted to usability studies involving web-based stimuli (for review see Duchowski, 2003; Hyönä, Radach and Deubel; 2003). Usability professionals and independent research groups have been attempting to identify the specific contributions of eye-tracking to website design and usability. Many such studies involve the identification of the specific targets of the users’ visual attention to different parts of the interface, or Areas of Interest (AOI). The data relative to these AOIs can then be compared in different ways, including order, number and duration of fixations to each AOI.

As part of a continuing investigation into the contributions of eye-tracking to usability testing, user eye-movement data was gathered during testing of three e-commerce websites. The data was examined in terms of various AOIs on the screens and was used to uncover more information about how the users interacted with these interfaces. 

METHOD

Thirty-six undergraduate and graduate students at Wichita State University (26 female, 10 male) at Wichita State University participated in this study. Seventy-two percent of the participants were between the ages of 18 and 26 years. A Pentium IV-based PC computer with 96 dpi, 17” monitor with a resolution setting of 1024 x 768 pixels was used. The monitor was integrated with the Tobii 1750 eye-tracking system, which was used to detect and collect participant eye-gaze data during testing. The Tobii 1750 eye-tracker samples the position of the user’s eyes on an average of every 20ms (i.e., 50Hz) and is characterized by the unobtrusive addition of the eye-tracking hardware (e.g., high resolution camera and near infra-red light-emitting diodes) to the monitor frame. This design aspect helps promote more natural user behavior by not placing unnatural restrictions on participants (e.g., helmets, head-rests, etc.). Three e-commerce websites specializing in the sale of educational toys were used in the study: Mastermind Toys, Toys to Grow On, and Wonder Brains.

RESULTS

Participant performance data was compared on three usability measures: time on task, number of pages visited, and perceived difficulty (Likert-type scale, 1 = “Very Easy”, 5 = “Very Difficult”). The eye-movement data collected during testing included the number and duration of visual fixations relative to different AOIs on each site’s homepage. The results discussed below are for two of the tasks performed during usability testing of the sites.

Task 1: Find Contact Information

This was a simple information search task that requested users to find contact information for the toy company. On this task Site 2 (MasterMindToys.com) had significantly higher scores for both perceived difficulty (F (2,33) = 5.459, p. = .009) and for Time on Task (F (2,33) = 9.841, p. < .001) (see Table 1).

Table 1. Usability Measures across Sites for Task 1

The specific links that lead to the company contact information were located in different areas of the homepages for each respective site. Site 2 (MasterMindToys.com) had the proper link located among a list of other hyperlinks on the right hand side of the page. By way of contrast, Site 1 (Toystogrowon.com) had the link at the bottom of the page, and Site 3 (WonderBrains.com) had the link located in multiple locations at the top and bottom of the page. The elevated time and difficulty scores for Site 2 suggest that users may have had some preconceived notions of where to find certain common webpage components on a homepage (i.e., contact information), which resulted in poorer performance when the link was in an unexpected location. This view is substantiated by research into web objects and user schemas (Bernard, 2001; Bernard 2002).

Eye-tracking data for this task was used to explore how users went about searching for these particular hyperlinks on the different homepages. Based on the average time to first fixation received to the individual AOIs on the homepage, the users of Site 1 started their visual search for the appropriate link in the center of the page then examined other web components along the edges the page, such as the top shopping cart links and left navigation bar (Figure 1).

Figure 1. Order of first fixations per AOI for Task 1 (Toystogrowon.com)

A similar bias for searching for the contact information link at the top of the page is shown by the AOI data for Site 2, suggesting that expectations as to this type of link’s typical location worked against the users when the link is located elsewhere, such as the links on the right side of the page, which were typically fixated upon last by users (Figure 2).

Figure 2. Order of first fixations per AOI for Task 1 (MasterMindToys.com)

The ClearView eye-tracking software can represent the areas of the screen receiving either more fixations or receiving the longest dwell times in a color-coded “hotspot” image of the interface, with the closer to red the more fixations occurred in an area of the interface and intensity decreasing with movement down the spectrum.

Inspection of these hotspots on the homepages for this task relative to the AOI definitions reveals a very distributed pattern of user eye-movement on Sites 1 and 2 (Figures 3 and 4). This suggests that users directed their visual attention to several areas other than that where the correct link was located. For whatever reasons, it was these areas that users searched most frequently and longest for the correct link in addition to the area where they eventually found it. 

Figure 3. Homepage fixation hotspots on Task 1 (MasterMindToys.com)

Figure 4. Homepage fixation hotspots for Task 1 (Toystogrowon.com)

On the other hand, the hotspots for Task 1 on Site 3 were more concentrated and directed primarily at the correct links located at the top and bottom of the page (Figure 5).

Figure 5. Homepage fixation hotspots on Task 1 (WonderBrains.com)

Task 2: Shopping by Age

This task asked participants to find a puzzle for children ages 5 and up. There were significant differences observed for difficulty (F (2,33) = 3.593, p. = .039), time on task (F (2,33) = 5.564, p. = .008), and number of pages (F (2,33) = 4.949, p. = .013) (see Table 2), with Site 1 (Toystogrowon.com) having the highest scores. These results suggest that there was something about Site 1 that made it more difficult for users to shop by age than on the other two sites. These findings are corroborated by a review of the AOI data for this task.

Table 2. Usability Measures across Sites for Task 2

This task could be completed in two different ways on all three sites: (1) using the categories on the left navigation bar to find a puzzle and narrow the search from there; or (2) using the shop by age option available from the homepage. On Site 1, the shop by age option was accessed through a single hyperlink, a solution used by only one participant. Based on the average time to first fixation for each AOI, the area where this link was located was typically attended to later than many other areas (Figure 6).

Figure 6. Order of first fixations per AOI  (Toystogrowon.com)

Examination of the fixation and dwell time data in terms of hotspot maps of the homepage during this task assists with the interpretation of this data (Figure 7). Although the left navigation array received the most attention, the “shop by age” option in the upper navigation array was minimally noticed, primarily by the one user that clicked on this link. Higher fixation rates or dwell times in this area would be indicative of users finding the option but perhaps not recognizing its function, and thus failing to choose it. The relative lack of visual attention to that area suggests that few users other than the one who chose the “shop by age” option ever fixated upon it.

Figure 7. Hotspot map of the homepage showing areas of highest fixation for Task 2

On Site 2 (MasterMindToys.com), all the participants but two used the “shop by age” option which was broken down into a range of age-related links on the top of the left navigation bar. This area of the homepage received the majority of the users’ visual attention (Figure 8). The product category links on the left navigation bar and the “shop by age” links above them were attended to relatively late on average, but this did not seem to impact performance for most participants. There were some aspects of the page not useful in this task that received considerable visual attention, including the large picture of the store interior and the center links to the right of the picture, similar to Task 1 on this site (discussed above). This observation is confirmed by the hotspot map of the homepage for Task 2 (Figure 8), and may indicate that these links are distracting and/or listed in a manner that is difficult to quickly glance through and eliminate as potentially useful during a search task. However, the overall design of the page and placement of the age-related links was conducive to a successful search for products by age, an assessment supported by the eye-tracking data.

Figure 8. Homepage fixation hotspots on Task 5 (MasterMindToys.com)

The users of Site 3 (WonderBrains.com) were more evenly split on the use of the “shop by age” option, though it was less popular and the age-related links received less attention than the standard toy categories higher up on the navigation bar (Figure 9).  In fact, examination of this hotspot map confirms that the most of the visual attention directed toward the homepage during this task involved the appropriate links—either categorical or age-related—and little else. This implies that the design of Site 3’s homepage was conducive to shopping (at least for this task) and held few visual distractions for participants.

Figure 9. Homepage fixation hotspots on Task 2 (WonderBrains.com)

DISCUSSION

Much can be learned about the nature of the user experience in the comparison of user visual attention afforded to different areas of web interfaces. Specifically, the use of eye-tracking data allows usability professionals to gather more information about what areas of interest (AOIs) are potentially: (1) most eye-catching; (2) most informative; (3) most frequently ignored; and (4) most distracting. In this way eye-tracking can be used to determine not only whether users are successful at navigating to a particular page of a website, but also where and how they search the interface for a targeted link or web object. This use of eye-tracking data as supplemental information to standard usability testing can be very informative as to both user expectations and resulting design recommendations.

The results of this study emphasize the importance of interpreting user eye-movement data in usability testing within the context of the interface being evaluated. In future studies, AOI eye-tracking could also be utilized not only within a single webpage or interface screen, but also across different pages of a site (see Pan et al., 2004), multiple exposures to a site (see Josephson and Holmes, 2002), and between different stages of a complex usability task. These comparisons could also be performed both in terms of iterative studies between different versions of web page/site and comparative studies between entirely different websites.

REFERENCES

Bernard, M. (2001). Developing schemas for the location of common web objects. Usability News 3.2. [Online]. Available:    http://psychology.wichita.edu/surl/usabilitynews/3W/web_object.htm

Bernard, M. (2002). Examining user expectations for the location of common e-commerce web objects. Usability News 4.1. [Online]. Available: http://psychology.wichita.edu/surl/usabilitynews/4S/web_object.htm

Duchowski, A. T. (2003). Eye tracking methodology: theory and practice. London: Springer. 

Fitts, P. M.,  Jones, R. E. & Milton, J. L. (1950). Eye movements of aircraft pilots during instrument-landing approaches. Aeronautical Engineering Review, 9(2), 24-29.

Hyönä, J., Radach, R. and Deubel, H. (2003). The mind’s eye: Cognitive and applied aspects of eye movement research, Amsterdam: Elsevier Science. 

Josephson, S. and Holmes, M. E. (2002). Visual attention to repeated images on the World-Wide Web: Another look at scanpath theory. Behavior Research Methods, Instruments, & Computers, 34(4), 539-548.

Pan, Hembrooke, Gay Granda, Feusner & Newman, (2004). Determinants of web page viewing behavior: An eye-tracking study, Proceedings of the Eye tracking research & applications symposium on Eye tracking research & applications, 2004, San Antonio, Texas.

Evaluating the Usability of Educational Websites for Children

By Shiva Naidu

Summary: This study examined the usability of educational websites for children. Children ages 7 - 11 performed seven search tasks with one of three websites. Overall, participants, especially those less than 10 years of age were not very successful. Terminology, number and organization of links, location of information above the fold, and length of individual pages all influenced performance on the tasks.

INTRODUCTION

Children between the ages of 6-12 are using the Internet more and more as a resource for finding information for school projects. The UCLA Center for Communication Policy (2003) reports that approximately 75% of children who used the Internet in 2002 went online at their school, an increase of about 12% from 2000. Educational website creators have the challenge of designing for a wide range of ages and abilities. Arsenenault (2004) tested the usability of 24 commercial websites for children elementary-aged children in a private school in Montreal, Quebec. She found that while children preferred an interactive website, too many frames caused confusion and tables with elaborate listings and poorly organized links were cognitively demanding (especially for those under ten years old). The use of icon metaphors, excessive animation, and required plug-ins also were reported to be problematic to this population.  

Bilal (2001) carried out an experiment with 17 children in an East Tennessee school using Yahooligans! as a test site. She found that browsing required less cognitive load than keyword searching. Searching by keywords often resulted in failure because of misspellings or inappropriate search terms. Bilal concluded that the children’s limited success on completing the assigned tasks was due to the Yahooligans! design not being based on children’s developmental level and cognitive abilities.

To further understand what aspects of educational websites influence performance and satisfaction, we evaluated childrens' success, navigational efficiency, and satisfaction with three educational websites^* - Enchantedlearning.com®, Factmonster.com™, and Infoplease.com’s Homework Center™ (see Figures 1- 3). EnchantedLearning.com™ is a site designed for children by Enchanted Learning Software. The Infoplease.com Homework Center and FactMonster.com are sites sponsored by Information Please, a division of educational publisher Pearson Education. These sites were chosen because they offered similar content but different interfaces to the users. FactMonster.com  was a very colorful and graphical site while The InfoPlease.com Homework Center was primarily text-based. EnchantedLearning.com offered a mix of graphical and textual links and generous areas of whitespace.

Figure 1. EnchantedLearning.com

Figure 2. FactMonster.com

Figure 3. InfoPlease.com Homework Center

METHOD

Participants

A total of 30 elementary-aged children (17 females, 13 males) ranging between 7 and 11 years of age (M = 8.67) volunteered for this study. Participants were recruited from local communities such as churches, scout troops, and after-school programs. All the participants had at least one year of experience using computers and the Internet specifically.

Procedure

Participants were asked to complete a series of seven informational search tasks on one of the three websites. Age of the participants was balanced across websites. The tasks were as follows:

• What is the state capital of Wyoming?

• Use the search field to find out in what country The Great Wall is located.

• Find a phone number or address which will get you in touch with the people who made the website.

• What is the planet Mars named after?

• Find a multiplication table that gives you the answer to 3 x 2.

• Sir Edmund Hillary was a famous explorer. What was he famous for?

• How do you say “Thank You” in Italian?

Tasks were presented in random order and took approximately 30 minutes to complete. After all tasks, participants were asked to complete a modified version of the System Usability Scale satisfaction survey (Brooke, 1986) using a “smiley-face” Likert scale derived from the Wong-Baker pain rating scale (1998) to rate their satisfaction with different aspects of the website. In addition, participants' success, time on task, and search efficiency were measured. Search efficiency, or lostness, was defined by the number of pages traversed beyond the optimum number of pages to complete a task. Time and efficiency data was gathered by the tracking program Ergobrowser™.

RESULTS

Success

Table 1 shows the percentage of participants that were successful on each task for each site. Factmonster.com had the highest rate of overall success (67.5%) followed closely by Enchantedlearning.com(62.8%) and then the Infoplease.com Homework Center(47.6%).

There were several tasks that seemed to suggest that the level of difficulty varied across website. Finding contact information proved to be extremely difficult on Enchantedlearning.com (10%) and the Infoplease.com Homework Center (33.3%) primarily because this information was located at the very bottom of the page. Participants using the Infoplease.com Homework Center also had trouble finding information on Mars, Sir Edmund Hillary, and the Italian language. The primary problem was the overwhelming number of link choices on this site and terminology that did not match what the participants' were thinking. For example, the information on how to say thank-you in Italian was not found by any of the participants using this site. This information was located under the "Almanac > Writing and Language >  Basic Phrases in Other Languages" links. Most participants looked for it under the "Speaking and Listening" link on the home page rather than "Almanac." Participants looking for information on Sir Edmund Hillary on FactMonster.com clicked on the "People" link and then "People Fun Facts" instead of the correct link of "Biographies". Those looking for this information on the InfoPlease.com Homework Center clicked on "Social Studies" or "History" instead of "Biographies".

Table 1.  Success rate for each task by website (bold indicates least successful tasks)

Efficiency

Results from a one-way ANOVA showed that the participants using FactMonster.com were able to complete all seven tasks the quickest - an average of 7 minutes faster than the InfoPlease.com Homework Center (F(2,27) = 3.76, p<.05) (Figure 4). Time to complete all tasks on EnchantedLearning.com was not significantly different from the other two sites. Average lostness was not significantly different across sites with EnchantedLearning.com having an average of 3.3 pages beyond the optimal path, FactMonster having 4.2, and the InfoPlease.com Homework Center having 4.8 (F(2,27)=.884, p=.42).

Figure 4. Average time to complete all 7 tasks for each site.

Satisfaction

Overall, participants rated EnchantedLearning.com, FactMonster.com, and the InfoPlease.com Homework Center equally well (26, 29, 29 respectively out of 44 total. The higher the number, the more satisfied the participants). The only individual satisfaction question that showed some difference across sites was in regard to the colors of the site. Participants using FactMonster.com were more positive about the colors than the other sites. Given that each participant worked with only one site (and had no other sites to compare it to), it was not too surprising that there were no differences in satisfaction. Our experience at SURL has been that children, in general, tend to be positive about a website even when they do not perform well.   

Differences by Age

Across all three sites, it appeared as though the older children had an easier time finding the information than the younger children (see Figure 4). This could be due to the fact that they (i) had more experience in school using the Internet and (ii) they had more knowledge of what the correct answer to the questions were and (iii) they had an overall better vocabulary which helped them understand the site's terminology. Despite this fact, all sites were designed for children in K-12. Educators of children in this age group (especially those less than 10) need to be very cognizant of a site's content and terminology to make sure it is best suited for their classroom. 

Figure 4. Success rate for each task by age

DISCUSSION

The results obtained suggest several things. Overall, the success rate on each website was low with this population. Factmonster.com was highest at 67.5%, which was better than the 43% with the InfoPlease.com Homework Center, but still not good odds for a child attempting to complete a homework assignment. The following were noted as important features that contributed to the participants' overall success with the sites:

Page Length: Many of the web pages on all three sites were long. Participants, especially the 7 and 8-year-olds, tended not to scroll down the page even when reminded that they could do so before the start of each task. This was especially evident with the task to find contact information. Both the Infoplease.com Homework Center and EnchantedLearning.com had its “contact us” link at the bottom of the homepage. Factmonster.com's higher success rate on this task was due to the fact that its Help icon was immediately visible at the top of the screen.

Too Many Choices: The Infoplease.com Homework Center offered many links on each page. For example, on the "Find the origins of Mars" task, once a user clicked on the Science category, there were many topics and sub-topics to choose from ranging from the earth sciences to technology. Users reported it to be "messy" and confusing, regardless of age. By contrast, Factmonster.com had fewer category links and was easier for participants to initially find a keyword related to what they were looking for.

Terminology: Enchantedlearning.com and FactMonster.com used simpler and more descriptive words to identify topics than the InfoPlease.com Homework Center. Factmonster.com used titles like “People” and “Word Wise” which were readily understood by the youngest children. However, they and the InfoPlease.com Homework Center also used terminology that was not as familiar to some children like “Biography” and “Almanac”.   

Font size and pictures: The younger children liked the larger font size and pictures offered on Enchantedlearning.com. This was a contrast to the Infoplease.com Homework Center that used a smaller font size and few pictures to guide the children. While EnchantedLearning.com was found to be easy to navigate, the older children commented that the large graphics made the site appear to be "just for little kids."   

Depth of the site: The deeper the participant had to travel to find information, the more lost they became. The youngest children, especially, tended to use the Back button solely for navigation. Most were unfamiliar with the fastpath of a Back-to-Home logo or icon. Therefore, it was easy for them to get lost looking for a particular answer if it was not close to the homepage.    

Advertisements: FactMonster.com, in particular, had a lot of animated advertisements on their site. This was very distracting to the participants, especially the 7-8 year olds. Some could not figure out how to close the ads (pop-ups) while others inadvertently clicked on a link within the ad and ended up on a completely different site. 

Target Audience: Even though a website may be geared for K-12, this does not guarantee that all children in these age groups will be successful. As Figure 4 shows, the 11-year old children did much better on the tasks than the 7-year olds. This was found to be true across all sites despite the fact that the look-and-feel of FactMonster.com and EnchantedLearning.com appeared to be geared more towards younger children.

CONCLUSION

This study evaluated the usability of three educational websites. Participants were fastest with FactMonster.com and more successful with FactMonster.com and EnchantedLearning.com than the InfoPlease.com Homework Center. None of the sites proved to be superior in terms of efficiency or satisfaction. Terminology, number and organization of links, location of information above the fold, and length of individual pages all influenced performance on the tasks. Older children (age 11) performed better on all sites than the younger children (age 7-8). Designers of K-12 educational sites should continue to conduct usability testing with a wide range of children to insure ease of use for all students.

*Note: Sites named in this article were tested in April - May 2005. Site design and content may have changed since this evaluation.  

REFERENCES

Arseneault, C. (2003). Having fun or finding information? Usability for kids sections of Web sites. 7th Museums conference and the Web 2003, North Carolina, USA. Retrieved July 10th, 2005 from http://www.archimuse.com/mw2003/papers/arseneault/arseneault.html
 

Bilal, D. (2001). Children’s use of Yahooligans! Search engine. II. Cognitive and physical behaviors on research tasks. Journal of the American Society for Information Science and Technology, 52(2), 118-136.

Brooke, J. (1986) SUS: A Quick and Dirty Usability Scale. Retrieved 07/11/05 from http://www.usability.serco.com/trump/methods/satisfaction.htm

UCLA Center for Communication Policy (2003). UCLA Internet Report 2003: Surveying the digital future, Year Three, Los Angeles, 1-89.

Wong, D., & Baker, C. (1998). Pain in children: Comparison of assessment scales. Pediatric Nursing, 14(1), 9017.

Online Flipping: Examination of the Digital FlipViewer®

By Spring Hull

Summary: This article examines the usability of FlipViewer® software for digital FlipBooks. The FlipViewer software allows users to read online documents in a three-dimensional e-book format simulates a paper document.  Participants performed 11 tasks with a FlipBook and their performance was evaluated. Some tasks were difficult for participants to complete, however, participants were satisfied overall with their experience using FlipViewer® and 100% indicated that they would recommend the product to others.

INTRODUCTION

According to Li and VanBorskirk (2005) Forrester report, nearly half of all U.S. marketers are prepared to increase online ad spending by redirecting resources from other marketing channels and it is estimated that $26 billion will be spent in 2010 for online advertising. This growth in online spending for advertising is positively correlated with an increase in viewing and reading documents online as Shaikh and Chaparro (2004) found in a survey that approximately 68% of respondents reported reading news related material online versus traditional print.

The rise in online reading has created a need for software that allows users to comfortably view and read documents on the computer screen. Many software products are now on the market that allow for reading of material online while simultaneously allowing valuable advertisement space for marketers. Zinio™, Texterity®, and Active Paper™ by Olive software are just a few of the products now available. Another product designed for reading text online is FlipViewer® - a three-dimensional page flipping electronic book (e-book) viewer and web browser. FlipViewer® allows users to view and read FlipBooks– digital documents that resemble traditional printed books.

The technology introduced by E- Book Systems in 1998, allows users to convert text, search results and images into interactive FlipBooks, displaying multimedia file formats including streaming media/flash in the form of a book on the computer screen. FlipBooks can be streamed over the Web, downloaded to a hard drive and stored on a CD according to E-Book Systems. FlipViewer® incorporates several unique features. For example, FlipViewer® allows users to turn one or many pages of a FlipBook at a time while having the option of returning to the original page using the mouse. Also, users can set the flipping speed and turn pages automatically using the Auto Flipping function. FlipBooks resemble traditional paper books and magazines and there is even an optional flipping sound when pages turn recreating the ambiance of reading a printed magazine.

This study evaluated the usability of the E-Book Systems FlipViewer® using a FlipBook magazine format.

Figure 1. Screen shot of FlipViewer® toolbar in the window frame view.

METHOD

Participants

Six students (4 females, 2 males) aged 19–29 (M=24 years) enrolled in undergraduate psychology courses at Wichita State University volunteered. Sixty-six percent reported visiting web sites daily and 50% reported spending 7 hours or more per week online.

Materials

The study used a Pentium-4 powered computer displaying at resolution of 1024 by 768 pixels on a 17” flat screen monitor. The April 2005 issue of “Fitness Management” FlipBook magazine found at http://ebook.lesurepub.com/ezine/currentIssue.opf was used for content. In addition, the FlipViewer® online tutorial http://www.Flipviewer.com/support/webhelp/fv12/fv121.htm and the Help function located on the FlipViewer® toolbar (example of the toolbar is shown in Figure 1) were available for participants to use to complete the tasks.

Procedure

Participants were presented eleven tasks in random order (see Table 1). Participants were given a maximum of five minutes to complete each task. Performance on each task was determined a success if the participant completed it correctly in less than five minutes. Tasks not completed in less than five minutes or completed incorrectly were determined unsuccessful. After each task, participants rated its difficulty on a 1-6 scale (1= very easy, 6= very difficult).

RESULTS

As shown in Table 1, several tasks were not successfully completed by all participants (Task 2, 4, 6, 10). In general, these tasks took longer to perform and were rated as more difficult than tasks that were completed in less time. An exception to this was Task 4, which was completed in less time and it was not perceived as difficult, but only 50% of the participants completed the task successfully. Participants rated this task as easy because they believed they had completed it successfully when they had not. Overall, Tasks 2 (search for word), Task 6 (grab and hold page 36 without losing page 6), and Task 10 (set auto-flipping) were found to be the most time-consuming and difficult. This was supported by a one-way repeated measures analysis for time to complete tasks [F (10, 50) = 6.08, p < .01] and post-task difficulty ratings [F (10, 50) = 4.20, p < .01].

Table 1. Participant performance on FlipViewer® usability tasks. Bold indicates the most time-consuming and difficult tasks.

Tasks 6 and 10 are novel features specific to FlipViewer®. The grab and hold feature is initiated by moving the cursor over the left bottom corner of the page until it becomes a hand; then left clicks to add more pages and right clicks to release the pages. Most participants were unsuccessful in completing this task and attributed their failure to the inability to find appropriate instructions in the tutorial and Help. Task 10 required participants to set auto flipping from page 40 to the end of the magazine.  Participants unsuccessful in performing this task also were unable to find instructions in the tutorial or Help. Task 2 required users to perform a keyword search. The search function for FlipViewer® uses a ‘Find Text’ option found in the drop-down menu under ‘Edit’ rather than a search field on the toolbar. Most participants did not find this approach to be intuitive.

Despite these three tasks, participants were able to successfully complete the other tasks such as bookmarking, zooming, changing the view, and page flipping speed. They were generally pleased with the look and usability of the FlipViewer® and reported they would use it again and recommend it to others.

DISCUSSION

Participants performed 11 usability tasks of a FlipViewer® FlipBook magazine. FlipViewer® was found to be a desired alternative for viewing material online as it imitates the “look” of the traditional printed book while offering many of the same functions as other document viewers as well as some unique features such as grab and hold and auto flipping. However, finding instructions on how to utilize these features was difficult for some participants. E-Book Systems might consider revising the current tutorial and Help function to include more information on those features new to users. Also, modification of some of the toolbar items (such as the search function and including options for copying text and graphics) might also enhance the FlipViewer® utility for users.

REFERENCES

Li, C., & VanBorskirk, S. (May 2, 2005). US Online Marketing Forecast: 2005 to 2010. Forrester Research, Inc. (summary available at http://www.forrester.com/Research/Document/Excerpt/0,7211,36546,00.html)

Shaikh, A. D., & Chaparro, B. S. (2004). A survey of online reading habits of Internet users. Proceedings of the Human Factors and Ergonomics Society 48th Annual Meeting, 875-879.

Smooth or Textured: Does Mouse Pad Surface Impact Performance?

By Jeremy Slocum and Shelby Thompson

Summary: This study examined the effects of mouse pad usage on performance of a target acquisition task. Results indicated no performance difference between three specialized mouse pads, a traditional mouse pad and no mouse pad. In addition, no significant differences were found between each of the mousing surfaces based on kinematic data. The results suggest that manufacturer claims of increased performance cannot be supported by empirical evidence.

INTRODUCTION

With the advent of high-speed processors and video cards, sales of computer video games have skyrocketed, leading to the development of organized ‘gaming’ communities and events. Within the competitive computer gaming community, optimized user input performance is of uppermost importance. Most of these games rely on fast-accurate movements of the mouse for aiming at a target, or manipulating movements during competitions. Manufacturers of computer accessories have benefited from an increased desire for gamers to have a “competitive edge” with regard to control of input by demanding high-dpi optical mice, specialized input devices and specialized mouse pads. However little empirical evidence exists showing these products improve basic input control with a computer, let alone computer gaming performance.

The goal of the present research was to test the claims of specialized mouse pad manufacturers that mouse pad surfaces can increase mousing performance for competitive gamers. The present study measured the effect of three different mouse pad surfaces on cursor control performance during a simple target acquisition task. Performance was examined through movement time (MT) and error rate (ER). The kinematic variables of peak velocity (PV), gross movement time (GMT: time from initial movement to first zero crossing in the velocity profile) and fine movement time (FMT: time from end of GMT to end of movement) were also examined to determine how the mouse pad surface affects the actual movements made by a user. It was hypothesized that as the texture of the mouse pad becomes smoother users will move faster (i.e., increased PV), but make more errors and show an increase in gross movement time (GMT).

METHOD

Participants

Twenty-five college students, 16 females and 9 males (M = 24.28 years of age) were matched according to movement time with a standard optical mouse without a mouse pad and then randomly assigned to one of four different mouse-pad conditions or a control group (no pad). All were right-hand experienced mouse-users and had normal or corrected-to-normal vision with no other physical impairments being reported.

Materials

The mouse pads used are shown in Figure 1: the Corepad (www.corepad.com), the G-Pad by Maxtill (www.maxtill.com), the Thunder 9 by X-Ray (www.xraypad.com), and a traditional foam mouse pad.

The Corepad (rougher surface) was 280 x 200mm and made of glass with “fencing” branded in to create texture. The G-Pad by Maxtill (smoother surface) was 265 x 215mm and made of frictionless tempered glass. The Thunder 9 by X-Ray (moderately smooth surface) was 291 x 236mm and made of rigid ABS material. The traditional mouse pad was 270 x 215mm and made of foam with a cloth surface. The table used had a 36 X 18” desktop area made of a low-glare Formica. The experimental apparatus consisted of a PC running Linux, a 21-inch monitor running at 1400 x 1050 with a resolution of 100 DPI and a refresh rate of 85 Hz, and a Logitech® MX™300 Optical Mouse (800 DPI).

Figure 1. The Corepad (top left), the G-pad by Maxtill (bottom left), and Thunder 9 (right)

Procedure

The experiment was divided into two sessions: a pre-session where subjects completed a target acquisition task without a mouse pad and a post-session in which subjects completed the same target acquisition task with a mouse pad or without if assigned to the control group. The purpose of the pre-session was to establish an average movement time in order to match each participant in the post-session. The experiment varied display target distance (17.5, 70, and 140 mm), display target size (2, 4, and 8), and angle of approach (0°, 45°, 90°, 135°, 180°, 225°, 270°, and 315°) in a discrete pointing task. Participants were asked to acquire the target "as quickly and accurately as possible." Amplitude, target size, and angle were randomized via the software. In the post-session, subjects were randomly assigned to one of five mouse pad groups: G-pad, Corepad, Thunder 9, traditional mouse pad, or no mouse pad.

RESULTS

With the emphasis of the study being the mouse pads, the data was collapsed across all conditions for each subject (N = 25, 5 subjects per pad). Results of a one-way ANOVA to test the adequacy of the matching procedure found no difference in MT (p = .998), indicating that each subject was appropriately matched across all post-session conditions. Additional one-way ANOVA’s found no significant difference for the remaining dependent variables (GMT, FMT, PV and ER).

With the subjects appropriately matched, a series of split plot ANOVA’s using each dependent variable was completed, with session (pre and post) being the within-subjects variable and mouse pad being the between-subject variable (Table 1). A significant main effect for session was found for MT [F(1,20) = 7.939, p =.011, h2 = .284] and FMT [F(1,20) = 6.208, p =.022, h2 = .237], showing a significant decrease in MT and FMT from the pre-session to the post-session. No significant main effect for mouse pad or interaction with session and mouse pad was found.

Table 1. Performance means for pre-session and post-session.

DISCUSSION

The results showed that different mouse pad surfaces did not significantly affect performance in terms of movement time (Figure 2) or error rate. A general significant decrease in movement time and fine movement time was found from the pre-session to the post-session, which is attributed to practice. The effect cannot be generalized to any particular mouse pad surface or mouse pads because the same decrease was seen in the control group which used no mouse pad.

Figure 2. MT for each target condition in the post-session. This figure outlines how there is little difference between performance for each of the mouse pad conditions.

Kinematic analysis was conducted to determine if the mouse pads significantly affected the actual movements made by users. It was predicted that as mouse pads became smoother users would attain a higher velocity, but would increase fine movement time. These predictions were not supported. The mouse pad surface did not have a significant effect on gross movement time, fine movement time, or peak velocity.

These findings show no true performance benefit from specialized mouse pads, nor did it affect the user’s kinematics. The claims of the manufacturers were not substantiated by these findings. However, more questions remain to be answered. This research did not specifically target experienced gamers as participants. Research should be conducted to examine the use of alternative mouse pads with this population (versus non-gamers). It could be that a certain level of skill is required to take advantage of the claimed benefits of the mouse pads. In addition gamer performance during actual play should be evaluated.

Note: For additional information on this study, please see the proceedings of the Human Factors and Ergonomics Society's 49^th (2004) Annual Meeting, Orlando, FL.

Contact Dawn Shaikh or Barbara Chaparro with questions regarding this site.
Last update: October 23, 2005

Disclaimer: Neither the Software Usability Research Laboratory, The Wichita State University, nor any agency thereof, nor any of their employees makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately-owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the Software Usability Research Laboratory, The Wichita State University, or any agency thereof. The views and opinions expressed herein do not necessarily state or reflect those of  Wichita State University, or any agency thereof.