Editor's Notes

In our ninth issue of Usability News:

paging vs scrolling of online text documents
tolerance to website download delays
use of breadcrumb navigation
cascading menus on web sites
optimizing screen design for older adults
personality characteristics of online purchasers

If you have a research study that you would like to do, but don't have the experience, time, or resources to do it, please contact us. We will do the research for you. As always, we thank you for your feedback and comments.

Usability News is distributed to over 3500 usability professionals, developers, managers, and researchers in over 60 countries. Contributions, suggestions, and submissions for future issues should be directed to barbara.chaparro@wichita.edu.

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The Impact of Paging vs. Scrolling on Reading Online Text Passages

By J. Ryan Baker

In a previous issue of Usability News, we examined the use of paging vs. scrolling for the presentation of search results. In that study we found that a moderate amount of scrolling (fifty links per page) was preferred to search result presentations that required either a large or small amount of scrolling (one-hundred links per page and ten links per page, respectively). Participants were also fastest at searching in the fifty-link condition.

In this study, we examined the use of paging vs. scrolling in reading passages, including participants' reading comprehension in paging and scrolling conditions. Dyson and Kipping (1998) found that participants read through paged documents faster than scrolled documents, but showed no differences in reading comprehension.

METHOD

A Pentium II based personal computer, with a 60 Hz, 96dpi 17" monitor with a resolution setting of 1024 x 768 pixels was used. Content for the passages came from Barron's "Passkey to the ACT" (2001) study guide. The articles had a mean of 713.7 words (S.D. = 36.83). The passages were presented in 10 point Verdana. Participants’ performance was tracked using Ergobrowser™ software.

Participants

Fifteen participants (3 males, 12 females) volunteered for this study. They ranged in age from 18 to 40, with a mean age of 23.3 (S.D. = 6.11 years). The median Web use for the participants was 7-14 hours per week (100% used the Web a few times per week or more).

Procedure

Participants were asked to read one passage from each of three distinct layouts: one passage presented over four web pages, ("Paging", see Figure 1), one passage presented over two separate web pages with no scrolling necessary, ("Full", see Figure 2), and an entire passage presented on one web page, ("Scrolling", see Figure 3).

After reading each passage, participants were given five multiple-choice comprehension questions related to the given passage (e.g., "In making decisions about parent-child relationships, judges are often guided by the principle that: [A: the family unit is the basic unit of society]"), and following those, five search task items (e.g., "What did the economic needs of families and communities necessitate until the end of the 19th century?"). Participants were not permitted to refer to the passages when answering the comprehension questions. Information in the search tasks had to be found within 5 minutes in order to be considered correct. Participants moved through the pages using the "forward" and "back" button presented on the page in the paging and full conditions, or by clicking on the scrollbar in the scrolling condition. The Paging condition required the users to click a page-forward button 3 times, the Full condition required the users to click on a page-forward button 1 time, and the Scrolling condition required user to click a maximum of 7 times on the window scroll button. The layouts were counterbalanced using a Latin square design. The layouts were stored on a local server, virtually eliminating download time in each condition.

Paging condition

Figure 1. "Paging" condition

Full condition

Figure 2. "Full" condition

Scrolling condition

Figure 3. "Scrolling" condition

After finishing all questions for each condition, participants answered a satisfaction questionnaire. The questionnaire consisted of a 6-point Likert scale, with 1 = “Disagree” and 6 = “Agree” as anchors. The questionnaire items were: "The layout made it easy to find information," "This site was visually pleasing", "The arrangement of this site promotes comprehension," "I am satisfied with this site," and "The layout looks professional." After participants completed the questionnaire for all conditions they ranked the three layouts for general preference.

RESULTS

A within-subject ANOVA design was used to investigate participant performance (mean reading time, comprehension, and search completion time) and perceived ease of use of the three conditions. A Friedman χ² was used to analyze preference for all three conditions.

Reading Task Completion Time

Evaluation of the average time (in seconds) taken to read each passage revealed a significant difference between the three groups [F (2,28) = 3.42, p < .05] (S.D. Paging = 72.4, S.D. Full = 53.5, S.D. Scrolling = 57.89; See Figure 4). Post hoc analysis found reading time in the Paging condition to be significantly slower than the Full or Scrolling conditions.

Reading Task Completion Time (in seconds)

Figure 4. Mean Reading Task Completion Time (in seconds)

Comprehension Questions Correctly Answered

Evaluation of the number of comprehension questions correctly answered revealed no significant differences between the three conditions [F (2,28) = 1.213, p = .31] (S.D. Paging = 1.32, S.D. Full = 1.16, S.D. Scrolling = 1.40; See Figure 5).

Comprehension Questions Correctly Answered

Figure 5. Comprehension Questions Correctly Answered

Search Task Completion Time

Evaluation of the time (in seconds) taken to complete the search tasks revealed no significant differences between the three groups though there was a trend for the search time in the Paging condition to be longer than that in the Full or Scrolling conditions [F (2,28) = 1.795, p = .185] (S.D. Paging = 92.83, S.D. Full = 139.43, S.D. Scrolling = 83.48; See Figure 6).

Search Task Completion Time (in seconds)

Figure 6. Mean Search Task Completion Time (in seconds)

Perceptions of Site Efficiency

Well-suited for Reading

No significant differences were found in the perception that a particular condition was more well-suited for reading [F (2,28) = .079, p = .924]. (S.D. Paging = 1.33; S.D. Full = 1.40; S.D. Scrolling = 1.53). (See Figure 7).

Well-suited for reading

Figure 7. Well-suited for Reading (1 = Disagree and 6 = Agree)

Easy to Find Information

No significant differences were found for participant satisfaction between the conditions in terms of user perceptions' that information was easy to find [F (2,28) = .547, p = .585]. (S.D. Paging = 1.43; S.D. Full = 1.47; S.D. Scrolling = 1.33). (See Figure 8).

Easy to Find Information

Figure 8. Easy to Find Information (1 = Disagree and 6 = Agree)

Arrangement Promotes Comprehension

No significant differences were found for the perception that a particular layout promoted comprehension [F (2,28) = .483, p = .622]. (S.D. Paging = 1.37; S.D. Full = 1.42; S.D. Scrolling = 1.37). (See Figure 9.).

Arrangement Promotes Comprehension

Figure 9. Arrangement Promotes Comprehension (1 = Disagree and 6 = Agree)

Layout Preference

Analysis of layout preference using a Friedman χ² showed no significant preference for any of the conditions [Friedman χ² (2, N=15) = .133, p = .936.] (See Figure 10.)

Mean Site Preference

Figure 10. Mean Site Preference (the lower the bar, the higher the preference)

CONCLUSION

The findings from this study show that participants using the paging condition took significantly longer to read the passages than either the full or scrolling conditions. Participants also showed no significant differences in their ability to answer comprehension questions correctly, nor in their perceptions or satisfaction of the reading conditions. This is somewhat surprising given that previous research has shown paging to be typically faster than scrolling (Dyson & Kipping, 1998). One might have expected that the Scrolling condition may be more time consuming given the users had to click the scroll bar more times to view the entire passage than they did in the Paging (3 clicks) or Full (1 click) condition. However, several users commented that they were more accustom to scrolling when reading documents on the web. It may be that since participants had more exposure to scrolling they were able to read through the documents more quickly using that mode of navigation. Participants stated that they found the Paging condition to be "too broken up," and that they had to "go back and forth" quite a bit to search for information. It is possible then, that for searching as well, viewing more of the document on a single screen facilitated easier scanning.

REFERENCES

Barron's Passkey to the ACT. (2001). George Ehrenhaft (Ed.) Barron's Educational Series: New York.

Bernard, M. L., Baker, J. R., & Fernandez, M. (2002). Paging vs. Scrolling: Looking for the Best Way to Present Search Results. Usability News, 4.1. ../usabilitynews/41/paging.htm

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.

Breadcrumb Navigation: An Exploratory Study of Usage

By Bonnie Lida, Spring Hull, & Katie Pilcher

Just as Hansel and Gretel created a breadcrumb trail to find their path back home, today’s internet user often finds a need to get back to a website’s previously visited locations; hence, the cyber “breadcrumb trail” was created. This textual representation of where and how information is located within the website allows the user to link to major categories of information along a continuum of sequential order. For example, the breadcrumb path for a leather chair on the Office Max website would be: Home > Furniture > Chairs > Leather Chairs. The location of this navigational path is often prominently placed in the upper left quarter of the website page.

In general, breadcrumbs serve two purposes: 1) they provide information to the user as to where they are located within the site, and 2) they offer shortcut links for users to “jump” to previous categories in the sequence without using the back key, other navigation bars, or the search engine. Breadcrumb paths give the site location information and links in a backward linear manner. Navigation methods, such as search fields or horizontal/vertical navigation bars, serve to retrieve information for the user in a forward-seeking approach. As suggested by Marchionini (1995), systems that support navigation by both browsing and analytical strategies are most beneficial to users since various patterns, strategies, tactics, and moves associated with both types of strategies are normally used.

Breadcrumb trails, according to Bowler, Ng, and Schwartz (2001), help users browse and search for information as well as provide paths back up the web hierarchy. Toms (2000) found that the search tool was most useful in focused searching; while menus were considered essential for browsing. She also suggests that users need both a stable orienting device, such as a menu, to facilitate pathways through the site, as well as a system that supports scanning to smooth the progress of the search (Toms, 2000). However, research on breadcrumbs as a navigation tool has been limited. Studies researching breadcrumb navigation have used simple site structures which have been designed conditions with or without breadcrumb navigation bars for the study. These studies found the availability of breadcrumb navigation bars results in more efficient site navigation and satisfaction (Bowler, et al. 2001; Maldonado & Resnick, 2002).

In an attempt to better understand how, when, or even if, users use breadcrumb navigation in a real-time online environment, we conducted an exploratory study to determine if participants use breadcrumbs when given a list of items to find on a website. In addition, we were interested in monitoring what other navigational methods they use to access information or e-commerce items (i.e., back button, navigation bars, search).

In this study, we evaluated participants' navigational strategies, user satisfaction, and general preference for two sites that utilize “breadcrumbs” – Google Directory directory.google.com, a web information search site, and Office Max www.officemax.com, an e-commerce office supply site. In addition to breadcrumb navigation, the Google directory (Figure 1) is organized in main and sub-categories and offers search capability.

Figure 1. Google Directory with breadcrumb Games > Board Games > Economy and Trading

Participants using Office Max (Figure 2) also had access to a breadcrumb navigation, search, a hierarchical left side vertical navigational structure, and a top of page horizontal navigational bar.

Figure 2. Office Max site with breadcrumb Home > Supplies > Post-It,Flags, & Markers > Post-It Notes

Participant performance was measured by the number of clicks, "Back" button selections, searches, and time to complete the ten tasks. This data was gathered by the tracking program Ergobrowser™. Data to collect breadcrumb usage was via Mousetrack 1.0 from LGSoft. Pentium 4-based personal computers, with a 60 Hz, 96dpi 17" monitor with a resolution setting of 1024 x 768 pixels on a campus network were used to access the sites.

After completing the tasks on each site, participants answered the End-User Computing Satisfaction (EUCS) instrument (Doll, Xia, & Torkzadeh, 1994), which was adapted for web usage and consisted of 12 satisfaction questions using a 1-5 Likert scale.

METHOD

Seventy-two participants (13 male, 59 female) with an average age of 23.8 volunteered for the usability study. All participants were familiar with the web – 83% reported searching for information at least weekly, while 64% had purchased a product online. Participants were asked to find ten items on the Office Max site and place them in their shopping cart. In addition, they were asked to find and record answers to ten information search questions on Google. The order of the sites was counterbalanced across participants. Participants had approximately 20 minutes per site to search for the information. The tasks were organized such that items from similar categories were grouped together so that use of the breadcrumb would enhance efficiency (i.e., the 1st five items in the OfficeMax task list were all from the category Furniture). After tasks for both sites had been completed, users answered additional questions related to their knowledge of breadcrumbs, recall of whether a breadcrumb was present on the sites, and recall of the path to a specific item.

Information Search Tasks (Google Directory):

What is the height of Luke Skywalker from the movie Star Wars?
What character did DeForest Kelley play in Star Trek V – The Final Frontier?
Name two actors in the cast of Toy Story 2 animated movie.
What is Michelangelo’s last name?
How old was Claude Monet (artist) when he died?
What company developed the Elite Force action video game?
Did the Star Trek video game, Generations, get a “good” or “bad” review from the Game Zone website?
Who developed the Monopoly board game?
In the area of psychology, what did Al Gore’s handwriting analysis reveal about his personality?
What do the letters, D, I, S, C, stand for in the DISC personality test?

E-Commerce Tasks (Office Max):

Items that you need:

1 high back office chair
2 file cabinets (lateral, 2 drawer)
1 file cabinet (vertical, 2 drawer, letter)
1 home/office safe
1 leather guest chair
1 scientific calculator
1 cordless phone with caller ID
1 8-outlet surge protector
2 boxes of hanging file folders
4 packages of post it notes

RESULTS

Results from a paired samples t-tests between sites revealed significant differences across the sites in terms of satisfaction, number of breadcrumbs, searches, back clicks used, time, total clicks and recollection of seeing a breadcrumb path.

Participants were queried as to the biggest problem they encountered with each site. The results found that “Not being able to find the information I am looking for” was the most cited problem by 60.8% of the participants in the Google directory search; in the OfficeMax site, 41.9% of the participants found their biggest problem was “It takes too long to view/download pages”. The overall satisfaction totals for both sites revealed participants were significantly more satisfied with the OfficeMax site (M = 57.52, SD = 8.17) than the Google directory site (M = 44.18, SD = 13.32), t(70) = -7.33, p < .01, for the search tasks.

We calculated the optimal number of clicks necessary to find the items for Office Max to be 67 (including 8 breadcrumb links) and 2 backs; for Google the optimal path was 68 clicks (including 7 breadcrumb links) and 8 backs. Figures 3 through 7 show the average number of breadcrumbs used, backs, total clicks, searches, and completion time for the two sites. As can be seen, the average breadcrumb usage is fairly low for each site (M = 2.11, SD = 2.46 for Google; M = 3.25, SD = 3.75 for Office Max), t(62) = -2.06, p < .05. The back button was used significantly more in the Google directory (M = 59.25, SD = 30.23) than for OfficeMax (M = 16, SD = 18.21), t(62) = 10.31, p < .01. The total number of clicks was high (M = 152.54, SD = 64.75 for Google; M = 94.07, SD = 29.09 for Office Max), t(62) = 6.71, p < .01. Although participants were instructed not to use the search to access information or products, 61% used this method in Google (M = 5.89, SD = 7.09) and 47% in Office Max (M = 3.00, SD 4.23), t(70) = 3.57, p < .01. Significant differences were also found for the task completion times between the two sites. The questions for the Google directory site took longer to find (M = 1652.98, SD = 482.91) than the products to purchase on the OfficeMax site (M = 917.02, SD = 256.58), t(62) = 10.73, p < .01.

Breadcrumb Usage

Figure 3. Average number of times Breadcrumb navigation bar was used.

Type-in Search Usage

Figure 4. Average number of times Search was used.

Use of "Back" Button

Figure 5. Average number of times the Back button was used.

Task Completion Time (in seconds)

Figure 6. Average time to complete ten tasks for each site.

Number of Clicks

Figure 7. Average number of clicks used to complete ten tasks for each site.

The median split of breadcrumb usage was found to be 4.0, within a range of 0 to 21, 28 (48%) of the participants were categorized into non-breadcrumb user (<4) and 31 (52%) as a breadcrumb user (≥4). No significant differences were revealed when breadcrumb users were compared with their efficiency data--total clicks, backs, searches, and time.

When participants were asked if they recalled seeing a breadcrumb path (with an example provided) seventy-nine percent of participants recalled seeing one on Google (M = 1.61, SD = .49) and 40% recalled seeing one on OfficeMax (M= 1.20, SD = .40), t(70) = 5.33, p < .01. (Figure 8).

Recall Seeing Breadcrumb Path

Figure 8. Number of users who reported recalling a breadcrumb path on each site.

DISCUSSION

This exploratory study was conducted to determine whether participants used the breadcrumb trail as a navigational tool within a site. We found the overall usage of the breadcrumb in site navigation to be low. Breadcrumb users were not found to be more efficient than non breadcrumb users. Participants used a variety of navigational means, such as Back, left and top navigation bars, and searching to find the information instead of or in addition to the breadcrumb tool.

Eighty-nine percent of the participants reported seeing a breadcrumb path on the sites; however, it is not known if the participants understood the function of the breadcrumb path. Although we designed the tasks to aid the users' learning by choosing items that repeated the same main and subcategories, participants did not utilize the breadcrumb tool. Future studies should investigate whether users understand the purpose of the breadcrumb path, and if training to use this navigational tool aids their search efficiency and mental model of the site.

The tasks in this study were designed to allow participants to efficiently use breadcrumbs to find the answers to questions in the Google directory search, or find the products to purchase on the Office Max task list. However, there were significant differences between sites in terms of satisfaction and all dependent measures. These differences were not entirely surprising given the site size and opportunities for new browser windows to open in the Google directory search for which using the back button was necessary. However, the optimal path clicks for both sites was relatively similar (67 total clicks, 2 backs, 8 breadcrumbs for OfficeMax and 68 total clicks, 8 backs, and 7 breadcrumbs for Google). Yet the average number of clicks in comparison was extremely different (94 total clicks, 16 backs, and 3 breadcrumbs for OfficeMax and 153 total clicks, 59 backs, and 2 breadcrumbs for Google). The results suggest there is reason to further investigate the differences between navigational strategies for an e-commerce task versus an information search task.

Participants in this study also reported seeing a breadcrumb path more often in the Google directory search, yet they used this navigational tool less on that site. This finding is even more interesting considering that participants reported their biggest problem on Google was not being able to find the information. Although it would appear from past research and theory that the breadcrumb path aids the user in navigation efficiency and their place within the site, our results did not find that to be the case. The results of this study put forward many new questions regarding the use of breadcrumb and efficiencies in navigation for future research.

REFERENCES

Bowler, D., Ng, W., and Schwartz, P. (2001). Navigation bars for hierarchical websites. Retrieved 01/20/03 from University of Maryland, Student HCI Online Research http://www.otal.umd.edu/SHORE2001/navBar/index.html

Doll, W. J., Xia, W., & Torkzadeh, G. (1994). A confirmatory factor analysis of the end-user computing satisfaction instrument. MIS Quarterly, December, 453-461.

Maldonado, C. A. & Resnick, M.L. (2002). Do common user interface design patterns improve navigation? Proceedings of the Human Factors and Ergonomics Society 46^th Annual Meeting, 1315-1319.

Marchionini, G. (1995). Information seeking in electronic environments. Cambridge: Cambridge University Press.

Mousetrack 1.0, LGSoft, 2002.

Toms, E. G. (2000). Understanding and facilitating the browser of electronic text. International Journal of Human-Computer Studies, 52, 423- 452.

Cascading versus Indexed Menu Design

by Michael Bernard & Chris Hamblin

If there is one basic truism about the Web it is that every designer has their own opinion concerning the best method for presenting menu items on a web page. Two common ways to present menus are to either hierarchically cascade the menu items upon mouse-over, or to simply place most, if not all, of the menu items in a categorical index. Cascading menus have the advantage of requiring little screen real estate. However, they have been much maligned for several reasons. First, it is sometimes difficult to use for the reason that users must precisely control their mouse movements in order to select the correct menu item. It becomes increasing difficult with the number of levels a user must navigate. Second, cascading menus hide menu information until the user positions the mouse over the menu level above it (see Walker, 2000).

Index menus, on the other hand, tend to take up valuable real estate. They also can present an overwhelming amount of menu information at one time. Unfortunately, there has been very little empirically validated research comparing different types of menu layouts since the the advent of the Web (see Norman, 1991). In response to this lack of research, this study sought to compare user performance and satisfaction of two basic types of cascading menu layouts to a categorical index menu layout.

In addition, since users have different reasons for searching on the web, this study also sought to examine user performance for two types of searches: the direct search, where the item being searched for is explicitly known, and the implicit search where the subject material being searched for is known, but the specific item is not.

METHOD

A Pentium II based PC computer, with a 60 Hz, 96dpi 17" monitor with a resolution setting of 1024 x 768 pixels was used. The participants’ performance was tracked using Ergobrowser™ software.

Participants were instructed to search three types of menu layout conditions. In one condition, the menu items were arranged in accordance to a categorical index menu layout (Index, see Figure 1). Another condition arranged the items in accordance to a drop-down or "horizontal" cascading menu layout ( Horizontal, see Figure 2). A third condition arranged the items in accordance to a vertical cascading menu layout (Vertical, see Figure 3). The menu links were the same size (10 pt. Verdana) in all three conditions. There were no delays in the presentation of the submenu for both the Horizontal and Vertical cascading menus. In addition, both cascading menus had one level of depth and had the same submenu items cascade from it. These menu items corresponded to the items that were presented in the categorical index menu.

Figure 1. The Index menu layout for an electronics website condition

The Horizontal menu item layout

Figure 2. The Horizontal menu layout for an electronics website condition

Figure 3. The Vertical menu layout for an electronics website condition

Participants

Eighteen participants (8 males and 10 females) volunteered for this study. They ranged in age from 20 to 49, with a mean age of 32.6 (S.D. = 8.1 years). Eighty-nine percent for the participants use a computer daily, and most (72.2 %) use the Web 25 hours or more per week.

Procedure

Participants were presented with three web sites, each with a different menu item layout condition. The website domains consisted of either an online electronics, general merchandise, or a children's toy store.

In order to present a realistic search environment, participants were presented with both directed search and browsing questions. For each condition, participants were instructed to search for specific information pertaining to six explicit and six implicit task questions. The explicit task questions directly stated in the question the specific merchandise item to be searched (such as, "You want to buy a Nikon 8-mm camcorder"). The implicit tasks required participants to search for an item that was implied in the task question, but was not explicated stated (such as, "Your parents are having their 40^th anniversary and you would like to give them a gift. They always talked about going down the Mississippi River and viewing the plantation homes"). Each question had to be properly answered within five minutes to be considered correct. Participants could repeatedly search until they found the correct information by using the Back button, or until the time expired. The menu layout conditions, the web domain, and the task questions were counterbalanced by means of a Latin square design.

After finishing all the questions for each condition, participants answered a satisfaction questionnaire. The questionnaire consisted of a 6-point Likert scale, with 1 = “Disagree” and 6 = “Agree” as anchors. The questions were as follows: "I felt lost/disorientated while searching for information," "The site was easy to navigate," "The menu structure was frustrating to use." After participants answered the respective questionnaires for each condition they ranked the four link arrangements for general preference.

Results and Discussion

A within-subject ANOVA was used to investigate actual performance (mean task completion time and search efficiency) and perceived performance for four types of menu item conditions. Post hoc comparisons were done using the Bonferroni test. The preference for each condition was measured by means of a Friedman χ².

Task Completion Time

Assessing the time needed to complete the search tasks found a significant layout main effect [F (2, 34) = 5.39, p < .01] in that participants searching in the Index condition found task information more quickly then the other two conditions. Participants searching with explicit task questions found the information significantly faster than searching with the implicit task questions for all three conditions [F (1, 17) = 25.42, p < .001]. There was no task by menu item layout interaction (see Figures 4, 5, and 6 for means and standard deviations).

Explicit task completion time

Figure 4. Explicit task completion time (S.D.) for explicit task questions

Implicit task completion time

Figure 5. Implicit task completion time (S.D.) for implicit task questions

Figure 6. Task completion time (S.D.) for both implicit and explicit questions

It is somewhat surprising that the task completion time differences were so great. That is to say, the results revealed a 6.4 second, average per-task time difference between the Index and the Horizontal conditions. Moreover, the average completion time difference between the Index and the Horizontal conditions increased to 8.5 seconds per task when participants searched using implicit task questions. These differences can obviously be quite considerable over a extended period of time. For example, according to the Nielson/Net Ratings (2003), the average home Internet user accesses 40 pages during a typical surf of the Web. Thus, the difference in time between these two menu arrangements would be 4.27 minutes for an average search.

Perceived Disorientation

Examining perceptions of search-related disorientation revealed a marginal main effect approaching significance [F(2, 34) = 2.84, p = .072], suggesting that the Horizontal menu layout was perceived as being the most disorientating of the three menu item layouts (see Table 1 below for means and standard deviations).

Perceived Ease of Navigation

Examining the perception that a specific menu layout was easier to navigate found no significant differences between the three layout conditions (see Table 1 below for means and standard deviations).

Perceived Frustration

Examining the perceived frustration of the participants with regard to the use of a specific menu layout conditions found no significant differences between them (see Table 1 below for means and standard deviations).

Table 1. Impressions of Link Locations - Mean (S.D.) (1 = “Disagree” and 6 = “Agree”)

Subjective Evaluation	Index	Horizontal	Vertical
Perceived Disorientation	2.50 (1.04)	3.89 (1.18)	2.11 (0.96)
Perceived Ease of Navigation	4.44 (1.20)	4.22 (1.40)	4.44 (1.20)
Perceived Frustration	2.38 (1.42)	2.50 (1.50)	2.39 (1.24)

Link Arrangement Preference

Analysis of the participants’ preference for each menu layout revealed no significant differences in ranking. However, examining the number of times a participant chose a particular menu layout as a first preference choice did indicate that the Index layout was particularly favored over the other Horizontal menu item layout (see Figure 6).

Number chosen as first preference choice

Figure 6. First preference choices of participants.

CONCLUSIONS

Several observations can be made from this study. First, significant search time differences between the three menu conditions were detected that strongly favored the Index menu layout. In addition to the reasons mentioned above, other possible reasons for this outcome could be that the menu items in the Index condition were simply closer together, thus resulting in faster menu selection times (Fitts, 1954). Another reason could be that the Index menus were centrally located on the screen, and thus were easier to see and acquire. This is bolstered by anecdotal comments supporting this notion. For example, participants stated that with the Index layout, "all of the subcategories are visible," and the menu was "located at the center of the screen, where [I] would typically look first." Moreover, participants selected the Index as their first preference choice more than the other two layouts.

The poorest performer, both objectively and subjectively, was the Horizontal layout. Participants in this condition took longer to find the task information, and they had the opinion, though non-significantly, that this layout was more disorientating than the other two layouts. It is possible that the distance this layout was from the center of the screen contributed to its poorer participant performance. In fact, one participant commented that this layout "was more difficult to see and reach than the others because of its height on the screen."

It is plausible that substantially deeper menu structures may produce different objective and subjective outcomes. Consequently, an up-coming study, which will be reported in the next edition of Usability News, will examine these menu layouts with deeper hierarchical levels.

REFERENCES

Fitts, P. M. (1954). The information capacity of the human motor system in controlling the amplitude of movement. Journal of Experimental Psychology, 47, 381-391.

Nielson/Net Ratings (2003). September 2002 global Internet index average usage. Retrieved January 30,2003: http://www.nielsen-netratings.com/hot_off_the_net.jsp

Norman. K. (1991). The Psychology of Menu Selection. Norwood, NJ: Ablex Publishing Co.

Walker, D. (2000). A flying menu attack can wound your navigation. Retrieved January 30,2003: http://www.shorewalker.com/pages/flying_menu-1.html

Examining Web Design Conventions Across Site Types

M.R. Patel, Managing Director of Fifosys Limited www.fifosys.com ¹

This study examined the viability of a Category-Based Usability Theory, which indicates that usability of websites should be accounted for on the basis of the category the website is in. While Web design experts have provided general design guidelines, it is believed that with different site types, design guidelines may differ.

If the conceptual model of the user is to be observed then true usability must come from analyzing current practices of Web design of the most popular websites within a category or field, and not merely by following recommendations from Web usability experts.

To determine if there are categorical differences across websites, home pages from the 30 most popular websites of 2001 voted for by the general public. The following were evaluated for each site: (i) Layout (tables or frames, frozen or liquid), (ii) Text (number of words on page, use of color, animation), (iii) Links (number of links, color of links), (iv) Images (number), (v) Screen size (to determine if horizontal and vertical scrolling required), (vi) Speed, and (vii) User Aids.

It was hypothesized that:

1) Significant differences will exist between most category averages, implying certain conventions existing within those categories.

2) Websites within a certain category will be better represented by the results of the category than the overall results.

3) No website will load within the 10-second download guideline on a 56.6K Modem Internet connection (Neilsen, 1996). However the majority of websites should do so with a 1Mps Internet Connection.

4) Website’s with an e-commerce objective will download noticeably quicker than those that only provide information.

RESULTS

Layout

The testing of page layout showed that 93% of providers had designed their page using tables. Interestingly, all of the websites within On-line Shopping were liquid, whereas with the other categories only a third and at most in the Entertainment category 50% were liquid and the rest frozen. We defined sites as being liquid when their content width adjusts itself to the users screen size. The fact that all On-line Shopping websites have implemented this function in their design could imply that by squeezing as much content into the window as possible there are more products visible, hence more sales. It may also suggest that they are more concerned about the users of their sites who open up multiple windows when perhaps comparing products.

Text

Travel sites in particular have the lowest percentage of non-linked words. Entertainment sites had more information than any other category. The fact that 66% of Entertainment sites had pop-ups also shows that they may be trying to provide even more information. E-commerce sites as expected had the lowest number of non-linked words. This implies that very little information exists on these pages that do not have the objective of trying to encourage the user to click to a purchase page.

Screen Size

The general level of scroll for each home page was not that different between any particular categories. First all websites were tested on an 800 x 600 screen size, which is very common on the smaller 15” monitors. The results showed that only 33% in the categories of On-line shopping and Reference sites had a horizontal scroll bar. When testing the larger screen size, 1024 x 768, 10% had a scroll bars. It is expected that the rest would have vertical scroll bars as they are popular on websites and have a large amount of content to provide the users, especially the information sites.

Speed

Sites in the on-line shopping category had the fastest download time (and smallest standard deviation) compared to the overall average. When carrying out the speed test using a 1Mbps connection all the websites downloaded from 3-10 seconds.

User Aids

User Aids were considered features such as Search, Account Log-ins, and About Us. All the websites to a certain extent had accounted for these functions. However, it was particularly interesting that in the category of on-line shopping all websites had a ‘sign-in’ field and 83% had ‘search’ and ‘about us.’ We could take this to imply that the provider understands that the user wishes to know more about the organization they are shopping from and wants to maximize the users experience by making it easier for them to purchase by including the search. With only 46% of other categories including a sign-in field it can be suggested that the on-line shopping providers plan and expect for return traffic to their websites.

CONCLUSION

In evaluating the resulting data we can identify that On-line shopping and Travel sites particularly stood out in that that they were the fastest to download and had the least number of words. The fact that these sites have an e-commerce objective clearly shows in the design of the website. The fact that the majority of text on an e-commerce home page is links rather than detailed textual information, indicates that they have accounted for usability by giving the user exactly what he or she wants: direct links to make a purchase. This study demonstrated that there are differences in web design across site categories. Understanding these design conventions will help web designers address the needs of their target audience and enhance the usability of their site.

¹This article is part of a larger research thesis, which can be obtained by contacting Mitesh Patel at m.patel@fifosys.com.

REFERENCES

Nielson, J. (1996). Top ten mistakes in web design. Alertbox, http://www.useit.com

WebUser Issue 23 2001, Web-user.co.uk

Can Internet Shoppers Be Described by Personality Traits?

By Gina M. Copas

E-commerce retailers (e-tailers) have for some time focused on identifying the shopping habits and trends of their customers, as opposed to the Internet community as a whole. Historically, the Internet shopper profile is portrayed as a homogeneous group of affluent males (Lebhar-Friedman, Inc., 2000 & Enos, 2000). In fact, prior research has mostly focused on variables such as gender and age as characteristics of Internet purchasing behaviors. However, it has been theorized that there might be an Internet culture that is more influential on buying behavior than just ones gender or age (Ebiz, 1999). Frequent Internet users are considered to be part of an "Internet community", therefore it should be considered whether or not there are shared traits among online users.

Personality traits are used to describe the strong consistencies that people demonstrate in their behavior across time and situations. People display behaviors that fall into a continuum of trait extremes. This behavior can be malleable to the situation such as the differences in behaviors across various shopping venues. For example, while consumers may not hesitate to give their credit card to a cashier or give personal or credit card information over the phone, research has shown that many consumers are concerned with online security. Therefore, this study explores Internet purchasing behaviors and the following personality traits: Vigilance and Openness to Change.

Vigilance is a personality trait that relates to the tendency to trust versus being suspicious about others' motives and intentions. High scorers expect to be taken advantage of and may be unable to relax their vigilance when it might be advantageous to do so. Low scorers tend to expect fair treatment (Conn & Rieke, 1994). Research indicates that Internet purchasers are more trusting (Donthu & Garcia, 1999). It was hypothesized that greater vigilance scores would be associated with fewer online purchases and decreased comfort with Internet purchasing. Conversely, lower scores on the vigilance scale will correspond with more online purchases, increased comfort and more positive attitudes towards Internet purchasing.

Openness to change is a personality trait that relates to being open to new circumstances as opposed to wanting to stay in familiar situations. High scorers are open to change and enjoy experimenting with new ideas and situations. Low scorers like routine and are attached to familiar situations (Conn & Rieke, 1994). Internet purchasers have been described as more innovative (Donthu & Garcia) and not uncomfortable with using technology (Ebiz, 1999). It was hypothesized that higher openness to change scores would be associated with more online purchases and more positive attitudes and increased comfort towards Internet purchasing.

Self-reliance was also investigated as an Internet behavior characteristic, however, it will not be reported on for the purpose this article.

METHOD

Participants/Materials

Five hundred and thirty-five participants from Wichita State University including both undergraduate and graduate business/marketing and psychology students participated in this study. All participants reported having access to the Internet. The ages of participants ranged from 18 to 51 and the average age was 23 (S.D. = 5.71).

Procedure

Data was collected by survey. Personality questions were selected from the 16PF Personality Inventory to identify Vigilance, Openness to Change, and Self-Reliance. Because of situational specificity, some survey questions were modified to measure the personality trait in the specific domain of E-commerce rather than general personality traits (Kazdin, 1998). There were 20, 5-point continuous scale questions pertaining to the frequencies of and attitudes towards Internet usage, specifically making online purchases. The survey was offered to every student in the participating classes and took approximately 15 minutes to complete.

RESULTS

The sample population accessed the Internet frequently, with 86.5% using the Internet to communicate at least weekly and 75% access the Web to explore and have "fun" at least weekly. Two-thirds of the population had long-term experience, over 4 years, using the Internet. Only 18% of the sample made regular online purchases (at least monthly); however, approximately half (55.4%) use the Internet to search for specific products at least weekly.

The mean vigilance score was 10.98 (S.D. = 2.75) out of a range of possible scores from 1 (trusting) to 16 (suspicious).

Table 1: Correlations: Vigilance by Internet Shopping Behaviors and Attitudes

Behavior/Attitude	Mean (Std Dev)	Significance
Buy products from online retailers^a	1.84 (.87)	r = -.156, p <.01, r² = .03
Buy products from online auctions^a	1.38 (.69)	r = -.087, p <.01, r² = .01
Comfortable shopping online^b	3.06 (1.23)	r = -.292, p <.01, r² = .09
Internet shopping saves money^b	3.12 (.86)	r = -.117, p <.01, r² = .01
Internet shopping is convenient^b	3.66 (.93)	r = -.107, p <.05, r² = .01
Like Internet shopping^b	3.12 (1.32)	r = -.264, p <.01, r² = .07

Note: a: 1 = Never to 5 = Daily ; b: 1 = Strongly disagree to 5 = Strongly Agree

The mean Openness to Change score was 15.04 (S.D. = 4.75) out of a range of possible scores from 0 (needs familiar) to 28 (open to change).

Table 2: Correlations: Openness to Change by Internet Shopping Behaviors and Attitudes

Behavior/Attitude	Mean (Stand Dev)	Significance
Buy products from online retailers^a	1.84(.87)	r = .333, p <.01, r² = .11
Buy products from online auctions^a	1.38(.69)	r = .215, p <.01, r² = .05
Search product information^a	3.45(1.19)	r = .216, p <.01, r² = .05
Make price comparisons^a	2.60(1.17)	r = .355, p <.01, r² = .13
Communicate with others^a	4.39(.95)	r = .187, p <.01, r² = .04
Have "fun" and explore^a	4.01(1.1)	r = .279, p <.01, r² = .08
Comfortable shopping online^b	3.06(1.23)	r = .300, p <.01, r² = .09
Internet shopping saves money^b	3.12(0.86)	r = .234, p <.01, r² = .06
Internet shopping saves time^b	3.54(1.0)	r = .187, p <.05, r² = .04
Internet shopping is convenient^b	3.66(.93)	r = .214, p <.01, r² = .05
Like Internet shopping^b	3.12(1.32)	r = .339, p <.01, r² = .12

Note: a: 1 = Never to 5 = Daily ; b: 1 = Strongly disagree to 5 = Strongly Agree

DISCUSSION

Results showed that Vigilance, or suspiciousness, was negatively associated with Internet purchasing behaviors that required commitment such as giving credit card or personal information. Vigilance was also negatively associated with Internet usage attitudes demonstrating a relationship between trust and Internet comfort levels. These results support the hypothesis that Vigilance as a personality factor can influence Internet shopping behaviors. The correlation between Vigilance and online shopping comfort accounted for 9% of the variance, which indicates that trust is an important issue when differentiating between online browsing behaviors and actually purchasing.

Results showed that the Openness to Change personality trait was positively associated with Internet behaviors and attitudes. This supports the hypothesis that Openness to Change as a personality factor can influence Internet shopping behaviors. The correlation between Openness to Change and making product price comparisons accounted for 13% of the variance, demonstrating that those who enjoy trying new things are quite willing to use technology as a shopping venue. The correlation between Openness to Change and actual online purchasing accounted for 11% of the variance in online behavior that required transmission of personal information and commitment; this is meaningful considering the volume of consumer dollars spent online.

The Census Bureau as reported in eBiz (Haney, February 16, 2001) stated that Internet retailing business increased 60% in a single year (from $17.3 billion in 1999 to $28 billion in 2000). This huge change in human behavior indicates that Internet consumer behavior is an important area of research. Understanding factors that distinguish between purchasers and non-purchasers may well be vital to retailers; both traditional and online. Internet retailers who zealously profile individuals' purchasing habits should be aware of population characteristics in order to retain their market and draw in consumers who do not make online purchases. E-commerce companies will want to use strategies that influence Internet shoppers to change their behavior from Internet shopping (searching online but purchasing elsewhere) to Internet purchasing; these strategies need to include user-friendly purchasing processes to ensure success during initial purchasing attempts as well as measures to increase consumer trust. Conversely, traditional retailers, who more moderately profile individual purchasing habits, will also want to have knowledge of population attributes in order to retain their market and regain market share lost E-commerce.

REFERENCES

Conn, S. & Rieke, M. (1994). 16PF Technical Manual (5th ed.). Champaign, IL: Institute for Personality and Ability Testing, Inc.

Donthu, N. & Garcia, A. (1999). The internet shopper. Journal of Advertising Research, 39 (3), 52-58.

Is there an internet culture? Ebiz (1999). Retrieved February 3, 2003: http://www.casselman.net/artist/eCult.html.

Enos, L. (2000, October 26). Net prices no lure for most e-shoppers. E-Commerce Times.

Kazdin, A. (1998). Research design in clinical psychology. (3rd ed.). Boston, MA: Allyn and Bacon.

Lebhar-Friedman, Inc. (2000). Internet commerce study reveals demographics, shopping trends. DSN Retailing Today, 39 (14), 17.

Aesthetics and Usability: A Look at Color and Balance

By Laurie Brady and Christine Phillips

As websites continue to fight for the attention of potential users, designers must begin to look not only at the inherent usability of the site, but also its perceived usability. For instance, Tractinsky (1997) found a correlation between perceived usability and aesthetics when investigating ATM machines . Subjects based their overall opinion of the usability of the ATM on the "look" of the machine. Moreover, in examining users' first impression of websites, Shenkman and Jonsson (2000) found that the best predictor for the overall judgment by typical users of a website was its beauty.

Design principles are frequently utilized by graphic designers to create aesthetically pleasing websites. The term harmony can be defined as a pleasing arrangement of parts, whether it be music, poetry, or color. In visual experiences, harmony is something that is pleasing to the eye. Two design principles that influence harmony are balance and color. When a website is harmonious, it engages the viewer and creates an inner sense of order, a balance in the visual experience. When something is not harmonious, it becomes either boring or chaotic (Lauer & Pentak, 2002). According to Lindgaard (1999), color is a strong predictor in the overall appeal of a website.

Balance too plays an important role in the appeal of a website. When websites are balanced, users feel a psychological sense of equilibrium (Lauer & Pentak, 2002). Related to this principle is the mathematical concept known as the Golden Section. The Golden Section refers to a proportion in which the ratio of the whole to the larger part is the same as the ratio of the larger part to the smaller. This translates into a ratio that is approximately that of a standard 8.5 x 11 page. The Golden Section has been used extensively by architects, musicians, artists, and mathematicians over the centuries, and is today utilized by graphic designers to create appealing websites.

This study focused on the role aesthetics plays in website usability. Perceived usability was measured as the design principles of color and balance were manipulated. Color and balance were selected due to their integrated influence on website harmony and stated importance in previous research (Matthews, 1999; Lindgaard, 1999).

METHOD

Participants

Eighty college students volunteered for this study (25 men, 55 women) and ranged in age from 18 to 43 (M = 20.53). The participants consisted of 41 freshman, 13 sophomores, 12 juniors, and 14 seniors. The median Web use for the participants was 2-6 hours per week (93% used the Web a few times per week or more).

Procedure

The website selected (www.createforless.com) was chosen based on the design principles of interest. The original site, and three variations of this site were used to test the impact of color and balance on perceived usability (see Figure 1). The sites were identical in content varying only in color, balance, or a combination of the two.

The original website had good balance or "equal distribution of visual weight along the horizontal and vertical axis," (Lauer & Pentak, 2002, p. 76). The first site variation consisted of poor visual balance. This balance was manipulated by dispersing the visual weight of the entire screen by moving the location of specific objects on the screen.

Color on the original site followed a triadic color scheme. Triadic color schemes involve hues that are equally spaced along the color wheel. Other standard color schemes include analogous, complimentary and split-complimentary. Color was manipulated by using a non-standard color scheme. This manipulation of color created the second variation from the original site. The final variation was a combination of the color and balance manipulations.

Participants examined one of the four sites. They completed five search tasks with answers located at various levels within the site. After completion of all the search tasks, participants completed a user satisfaction survey. Participants were then shown screenshots of all four sites and asked to rank the four sites based on perceived usability and overall aesthetic appeal.

Original Site	Altered Balance Site
Altered Color Site	Altered Color and Balance Site

Figure 1. Four site variations. (click on image to enlarge)

RESULTS

User Satisfaction

A between-subjects ANOVA was performed to determine if there were significant differences in overall user satisfaction scores derived from the satisfaction survey. No significant differences were found between the four sites [F(3, 76) = .427, p > .05].

Aesthetic Appeal

After viewing the screenshots of the four homepages, participants were asked to rank the sites from 1 to 4, with 1 being the most aesthetically pleasing and 4 being the least. Ranked aesthetic preference was measured by means of a Friedman χ². Significant differences were detected [χ² (3) = 40.05, p < .01]. Post hoc analysis indicated that the original site was significantly preferred over the site with manipulated color, and the site with both color and balance manipulations. The site with altered balance was significantly preferred over the site with manipulated color, and the site with both color and balance manipulations (see Table 1).

Table 1. Aesthetic Appeal Mean Rankings

Site	Mean Rank
Original Site	1.95
Altered Balance	2.15
Altered Color	2.77
Altered Color and Balance	3.13

Perceived Usability

After viewing the screenshots of the four homepages, participants were also asked to rank the sites from 1 to 4, with 1 being the site they perceived easiest to use and 4 being the site perceived as most difficult to use. Ranked usability preference was measured by means of a Friedman χ². Significant differences were detected [χ² (3) = 28.21, p < .01]. Post hoc analysis indicated that the original site was significantly preferred over the site with manipulated color, and the site with both color and balance manipulations. The site with altered balance was significantly preferred over the site with both color and balance manipulations (see Table 2).

Table 2. Perceived Usability Mean Rankings

Site	Mean Rank
Original Site	1.95
Altered Balance	2.42
Altered Color	2.56
Altered Color and Balance	3.07

DISCUSSION

In general, there were no statistical differences in user satisfaction between the four sites. This appears to support the idea that user satisfaction is related more to successful navigation than aesthetic appearance. However, when asked to predict which of the four sites the users thought would be the easiest to use, they ranked the aesthetically pleasing site the highest. The aesthetically pleasing site (original) ranked significantly higher than the site with manipulated color and the site with both color and balance manipulations. The manipulated balance site also ranked significantly higher than the site with both color and balance manipulations.

Regarding aesthetic appeal, both the original site and the altered balance site were significantly preferred over the site with manipulated color and the site with both color and balance manipulations. A common theme that emerged from the study was the importance of color. The sites that used the triadic color scheme consistently ranked higher than the ones with altered color schemes. A majority of the participants commented that color was a factor in how they ranked both the aesthetic appeal of the site and how easy they thought the site would be to use.

In terms of initial impressions of a website, it appears that design principles do indeed play a role. Further research is needed to determine how or if design principles also affect inherent usability of websites.

REFERENCES

Lauer, D. A., & Pentak, S. (2002). Chapter 5: balance. Design Basics. (pp. 75-98). Australia: Wadsworth.

Lindgaard, G. (1999). Does emotional appeal determine perceived usability of web sites? Hawthorne: University of Technology, School of Information Technology.

Matthews, K.K. (1995, July 25). Aesthetics and usability. Retrieved March 7, 2002: http://home.att.net/~kiana.matthews/independent_study/Aesthetics_Paper.htm

Shenkman, B. O., Jonsson, F. (2000). Aesthetics and preferences of web pages. Behaviour & Information Technology, 19(5), 367-377.

Tractinsky, N. (1997). Aesthetics and apparent usability: empirically assessing cultural and methodological issues. Paper presented at the 1997 Chi conference. Retrieved March 10, 2002: http://www.acm.org/sigchi/chi97/proceedings/paper/nt.htm

Can Expanding Targets Make Object Selection Easier
for Older Adults?

By Michael Bohan & Deborah Scarlett

Given the proliferation of computers and rapidly aging demographic trends, there is a critical need for user interface designs that accommodate older adults. It is known that many adults in this age group experience declines in cognitive, sensory, and/or motor capacities that may interfere with their ability to interact effectively with current user interfaces.

Motor behavior slows with age. Compared to younger adults, older adults take longer to complete the same movement, and their movements are more variable, less smooth, and less coordinated (Seidler & Stelmach, 1996). The loss of fine motor skills makes it difficult for older adults to position cursors on computer screens, particularly when interacting with small objects (Chaparro, et al., 1999; Walker et al., 1996). This can lead to greater frustration and possibly increased risk of cumulative trauma due to prolonged periods of time in awkward postures. This article describes one of a series of studies designed to explore alternative interaction techniques to make object selection easier for older mouse users.

When searching for ways to make object selection easier, consideration must be given to the trade-off between screen space and object accessibility. Increasing the size of objects makes their selection easier by virtue of Fitts’ law (1954), but it also reduces the amount of screen space available for displaying other objects and information. Alternative solutions have been suggested which make use of a larger cursor activation area (Kabbash & Buxton, 1995) or a dynamic control-display gain (Keyson, 1997) to enable faster selection of targets without increasing their size. These interaction techniques have been shown to be successful in improving the performance of older adults in basic object-selection tasks (Worden, Walker, Bharat, & Hudson, 1997).

Another promising interaction technique involves dynamically expanding objects on the screen as the cursor approaches them (McGuffin & Balakrishnan, 2002). This technique was found to significantly improve target selection time in younger adults, suggesting that subjects were able to modify their initial motor response (i.e., to a small initial target) to take advantage of the final expanded target size. However, it is unclear whether this same capability would be shared by older adults. Some research suggests that older adults are unable to adjust a motor response based on new visual information once the movement has been initiated (Heath, et. al., 1999). An additional concern is that a target which suddenly changes size could be distracting for older adults.

A preliminary experiment was conducted to assess the potential usefulness of expanding targets as a means to improve object selection for older computer users. Specifically, we investigated: (a) whether older adults could adjust their initial motor response to take advantage of the larger final target size and (b) whether performance is affected by the point at which the target begins to expand.

METHOD

Participants

Eight young (M age = 20 yrs) and eight older (M age = 81 yrs) participated in the study. All participants reported to be daily computer users.

Materials

A Pentium II based personal computer, with a 60 Hz, 96dpi 17” monitor with a resolution setting of 1024 x 768 pixels was used. A Java program¹ was modified to display two static targets (small – 5mm x 5mm square, large – 25mm x 25mm square) and three expanding targets (from an initial size of 5mm to a final size of 25mm). The expansion point occurred at 10%, 50%, or 90% of movement completion (see Figure 1). Participants completed a total of 20 trials per each condition for a total of 100 trials.

The three points of target expansions

Figure 1. The three points of target expansions.

Procedure

Participants were introduced to the target acquisition task and allowed to practice each of the five conditions prior to beginning the experiment. Participants then completed the trials for each condition in random order and were encouraged to take rest breaks between conditions.

RESULTS and DISCUSSION

Figure 2 shows the movement times for younger and older adults for the static and dynamic target conditions. A 2 x 5 split-plot ANOVA showed a main effect of age and a main effect of target condition [F(1,14) = 28.26, p < .001; F(4,56) = 38.83, p < .001 respectively). The older adults took significantly longer to acquire the targets than did the younger adults across all conditions. Post-hoc analyses showed that movement times for the 10% and 50% expanding target conditions were equivalent to those of the large static target for both age groups. However, in the case of the 90% expanding target condition, movement times were no different than that for the small static target for both age groups. Thus it would appear that all participants were able to adjust their initial motor response to take advantage of the final target size when expansion occurred early enough in the course of the movement. However, when expansion occurred late in the movement, neither group was able to adjust their movement accordingly.

Movement time for young and older adults

Figure 2. Movement time for young and older adults. Early expansion of the target resulted in better performance than late or no expansion.

This finding was inconsistent with McGuffin & Balakrishnan’s (2002) study in which they reported significant gains in performance for younger adults even when expansion began after 90% of movement completion. However, the discrepancy may be a result of an important difference between the expansion-algorithms used in the two studies. In the algorithm used by McGuffin and Balakrishnan, target expansion occurred at a set rate once the expansion point was crossed. The expansion would occur regardless of the cursor’s position relative to the target once beyond the expansion point. In our experiment, the size of the target was yoked to the cursor’s position relative to the target’s center. Thus, once the expansion point was crossed, the target size increased or decreased as the subject moved the cursor toward or away from the target’s center. One consequence was that the rate of expansion (and contraction) varied with the expansion point. That is, in the 90% condition, the target had to reach its maximum size (or minimum size) within a much shorter movement distance than that for the 50% and 10% conditions, and therefore expand at a much faster rate. The expansion rate may have been too fast to allow subjects to update their movement plan based on the new visual information about the target’s size. We are currently investigating this issue.

CONCLUSION

The results of this study, together with those of McGuffin and Balakrishan (2002), demonstrate that expanding targets are a promising interaction technique for improving target selection for older adults. Future studies will investigate how expansion rate impacts target acquisition and how it may be optimized for older adults. In addition, we are comparing this technique to other methods of optimizing target selection (such as "sticky" icons and area cursors).

¹Code was obtained from McGuffin, & Balakrishnan (2002) and modified for purposes of this study.

REFERENCES

Chaparro, A., Bohan, M., Fernandez, J. E., Choi, S. D. & Kattel, B. (1999). The impact of age on computer input device use: psychophysical and physiological measures. International Journal of Industrial Ergonomics, 24, 503-513.

Heath, M., Roy E.A., & Weir, P.L. (1999). Visual-motor integration of unexpected sensory events in young and older participants: a kinematic analysis. Developmental Neurophysiology, 16(2), 197-211.

Kabbash, P., & Buxton, W. (1995). The “Prince” technique: Fitts’ law and selection using area cursors. Proceedings of the CHI ’95 Conference on Human Factors in Computing Systems (pp. 273-279). New York: ACM.

Keyson, D.V. (1997). Dynamic control gain and tactile feedback in the capture of cursor movements. Ergonomics, 1287-1298.

McGuffin, M. & Balakrishnan (2002). Acquisition of expanding targets. CHI 2002, 4(1), 57-64.

Seidler, R. & Stelmach, G. (1996). Motor Control. In Encyclopedia of Gerontology: Age, Aging, and the Aged. San Diego: Academic Press Inc. pp. 177-185.

Walker, N. Millians, J., & Worden, A. (1996). Mouse accelerations and performance of older computer users. In Proceedings of the Human Factors and Ergonomics Society 40^th annual meeting (pp. 151-154). Santa Monica, CA: Human Factors and Ergonomics Society.

Worden, A., Walker, N., Bharat, K., & Hudson, Scott (1997). Making computers easier for older adults to use: area cursors and sticky icons. Proceedings of the CHI ’97 Conference on Human Factors in Computing Systems (pp.266-271). New York: ACM.

Examining Tolerance for Online Delays

By Paula Selvidge¹

The World Wide Web (WWW) has become an increasingly important medium for communication, commerce, and entertainment. The WWW user population is estimated to grow to 320 million by the year 2002 (Bouch et al., 2000). The 10^th WWW User Survey reported that speed, or taking too long to download pages, was the third major problem with the Internet reported by users (GVU, 1998). This problem translates into lost profits for e-commerce websites due to effects on users’ perceptions and performance. ZDNet (2002) reported a study of 12,000 online customers that revealed 48% of them gave up trying to purchase products because the web pages took too long to download. Brynijolfsson and Smith (2000) pointed out that trust is probably the single most important factor in e-commerce and the effects of time delay can significantly reduce consumer trust towards an e-commerce retailer. Unfortunately, addressing the factors that affect download time is not as simple as making hardware improvements. Since problems with delays are expected to persist, the effects of delays on aspects of website usability remain an important concern and are the focus of this study.

In this study, user tolerance for delays for three common WWW tasks, including information retrieval, purchasing, and downloading a text file was examined. These tasks were selected since the file sizes differ significantly among the three tasks, so it was expected that tolerance may be higher for those tasks with smaller file sizes. For example, tolerance for delays would be higher for downloading a text file than purchasing or information retrieval, since users may have an expectation that the task should take longer so they may be more willing to wait. End-users may be more tolerant of delays while purchasing online, since information must be exchanged to process the transaction, whereas information retrieval does not require information exchange.

The general purpose of this study was to examine how long participants would wait for web pages to load before abandoning a website. Previous research has primarily examined the effect of delays on preference and subjective evaluations of websites, but has failed to focus on the most important aspect, which is end-user behavior. The important question for e-commerce organizations is when will the potential customer leave the website because the wait is too long. The effects of different demographic characteristics, such as age (young adults/older adults), Internet experience level (novice/experienced), and type of Internet connection frequently used on tolerance for delays relating to three types of common Internet tasks (information retrieval, purchasing, downloading a text file) were investigated. It was hypothesized that (i) older adults would be more tolerant of delays than younger adults, (ii) participants with more Internet experience would be less tolerant of delays than novice users, (iii) participants would be more tolerant of delays for tasks involving downloading text files than purchasing or information retrieval tasks, and (iv) participants that frequently use high-speed connections to the Internet, e.g. cable or DSL modems, would be less tolerant of delays.

METHOD

Participants

A total of 101 participants in two different age groups with varying levels of Internet experience were recruited to participate in the experiment. The group of 61 young adults ranged in age from 18 to 30 (M = 20.13, SD = 2.63) and included 18 men and 43 women. The 40 older adults ranged in age from 60 to 88 (M = 70.65, SD = 7.60) and included 15 men and 25 women. Internet experience level (novice/experienced) was determined by the amount of WWW experience and frequency of WWW use. Participants with less than one-year experience with the WWW and frequency of WWW use less than a few times a month were classified as novice users, whereas participants with over 4 years experience and frequency of use at least a few times per month were classified as experienced users. Participants consisted of 24 novice and 37 experienced users in the young adult group and 15 novice and 25 experienced users in the older adult group. A Pentium-class computer with a 17” VGA monitor and 800 x 600 resolution was used in the experiment. The 800 x 600 resolution was selected due to potential visual limitations of the older adult participants. Two websites were created that enabled users to complete one of three common Internet tasks (information retrieval, purchasing, or downloading a text file).

The websites were similar in design, layout, and content in order to reduce possible effects of site design. The content of both sites was related to electronics, more specifically computers, cameras, and software. Two different design templates were selected that varied in color and title header graphics. The font size and style were consistent across sites (12 point Verdana), and all site backgrounds were white with black text. The websites were accessed from the hard drive during the experiment in order to control delays in page loading time. Each web page loaded after a 45-second delay. The 45-second delay level was selected based on prior studies that indicated significant differences in frustration between 20 and 30-seconds, so a delay level was selected beyond 30-seconds to include a majority of participants’ tolerance levels for download delays (Selvidge et al., 2001).

Procedure

All participants were tested on an individual basis in a 45-minute session. The experimenter typed in the two URL’s for the websites and minimized the websites on the task bar, so participants just selected a website from the task bar. After completing the survey, the experimenter read the task aloud and participants were instructed to complete one task (information retrieval, purchasing, or downloading a text file) on one of two websites. The participants were informed that they could leave the website they initially started on at any time or any reason, they could stay on the same site, or they could go back and forth between the sites, since the task information could be found on either website. Each page on both websites loaded after a fixed 45-second delay throughout the task. The delay started with the users’ action of selecting a hyperlink, Back, or Forward command button. During the delay period, the page where the user initiated the action remained on the screen while a message window (2.5 mm x .75 mm) with the text “Working…” was presented in the center of the screen to provide feedback that the page was loading. After the delay, the page selected was presented immediately with all text and graphics fully loaded. The correct answer for each task was located on the third level of each website. The browser program recorded the web page selected, elapsed time when participants left the website, and number of times each site was selected. After completing the task, the experimenter asked the participants why they did/did not leave the first website, the type of Internet connection they used most frequently, and they were also asked to rank the speed for task completion based on their experience for information retrieval, purchasing, and downloading a file.

RESULTS

Delay Time

The mean delay times were 86 s (SD = 57 s) for young adults and 151 s (SD = 60 s) for older adults (see Figure 1). A 2 (age) x 2 (experience level) x 4 (task) between-subjects ANOVA with delay time as the dependent variable revealed a significant main effect of age, F(1, 84) = 18.64, p < .01, but no effect of experience, age by task, age by experience, experience by task, or age by experience by task, p > .05. A one-way ANOVA was conducted to determine the effects of internet connection on delay time and revealed a significant main effect F(2.97) = 3.80, p < .05. Post-hoc analysis showed a significant difference between the Cable/DSL users and the dial-up users (Figure 2).

Site Changes

The means for site changes for young adults were 3.95 site changes (SD = 6.74) and 0.26 site changes (SD = .72) for older adults (see Figure 3). The actual number of site changes ranged from 0 to 4 for the older adults (N = 8) and 0 to 35 for the young adults (N = 30). A 2 (age) x 2 (experience) x 4 (task) between-subjects ANOVA with number of site changes as the dependent variable revealed a significant main effect of age, F(1, 84) = 8.65, p = .004; h²= .09; 1 - b = .82, but no effect of experience or any interactions, p > .05.

Task Type and Experience

No effect of task type (information retrieval, purchasing, downloading a text file) or Internet experience level was found for either delay time or number of site changes.

Figure 1. Older adults waited longer than younger adults.

Figure 2. Dial-up users waited longer than Cable/DSL users.

Figure 3. Older adults switched sites less frequently.

DISCUSSION

Results of this study showed that:

Older adults were more tolerant of delays than younger adults in that they waited longer before leaving a site and switched sites less often.
Participants that frequently use high speed connection are less tolerant of delays than those used to a dial-up connection.
Internet experience level or task had no impact on delay tolerance.

Older adults not only waited longer, but a majority did not leave the site at all. Only 20% of older adults left, while 49% of young adults left to go to the other site. In addition, 70% of the young adults abandoned the site before the home page even loaded. It was interesting to note that the older participants were frustrated by the delays as evidenced by their comments, but they did not elect to leave the site to escape the wait. When asked why they left or stayed on one website, only 29% of older participants commented that the website was slow. Others commented that they were curious, unsure if the site was working, or stayed because they were satisfied with aspects of the site.

The findings from this study have direct implications for website design. Older adults will wait longer for downloads and are less likely to leave a site, so web designers could incorporate meaningful graphics or other media in the place of text to enhance the usability of the site for this population. If web designers are targeting users with high-speed connections, page size should be limited, since high-speed users leave websites faster and switch sites more frequently. If web designers are targeting young adults, home page size should be small and download quickly, since young adults frequently abandon sites on the home page. In general, use techniques to minimize page sizes because sites with short delays will be revisited more frequently. In summary, the findings stress the importance of designing for the targeted end-user to maximize performance and end-user satisfaction.

¹Note: This research is part of a larger dissertation study that examined the effects of end-user attributes on tolerance.

REFERENCES

Bouch, A., Kuchinsky, A., & Bhatti, N. (2000). Quality is in the eye of the beholder: Meeting users’ requirements for Internet quality of service. CHI Proceedings, 2(1), 297-301.

Brynjolfsson, E. & Smith, M. (2000). Frictionless commerce? A comparison of internet conventional retailers. Management Science, 46, 563-585.

Graphic, Visualization, & Usability Center (GVU) (1998). GVU’s 10^th WWW user survey. Retrieved January 20, 2003: http://www.gvu.gatech.edu

Selvidge, P., Chaparro, B., & Bender, G. (2001). The World Wide Wait: Effects of delays on user performance. International Journal of Industrial Ergonomics, 29(1), 15-20.

ZDNet PC Magazine (2002). The e-complaints window, Retrieved January 20, 2003: http://www.zdnet.com

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