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Effects of Age and Training Formats on Basic Computer Skill Acquisition in Older Adults.

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Title: Effects of Age and Training Formats on Basic Computer Skill Acquisition in Older Adults.
Language: English
Authors: Echt, Katharina V., Morrell, Roger W., Park, Denise C.
Source: Educational Gerontology. Jan-Feb 1998 24(1):3-25.
Peer Reviewed: Y
Page Count: 23
Publication Date: 1998
Document Type: Journal Articles
Reports - Research
Descriptors: Age, Computer Literacy, Memory, Multimedia Instruction, Older Adults, Online Systems, Optical Disks, Reading Comprehension, Skill Development
ISSN: 0360-1277
Abstract: Computer procedures were taught with either interactive multimedia CD-ROMs or manuals to 46 adults aged 60-74 and 46 aged 75-89. The younger group made fewer errors, required less help, and took less time. Both groups forgot some facts and procedures over time. Format did not affect performance. Spatial and verbal memory, text comprehension, and perceptual speed influenced performance. (SK)
Entry Date: 1998
Accession Number: EJ556491
Database: ERIC
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  Value: <anid>AN0000219612;EGR01JAN.98;1998Feb20.11:10;v2.3</anid> <title id="AN0000219612-1">EFFECTS OF AGE AND TRAINING FORMATS ON BASIC COMPUTER SKILL ACQUISITION IN OLDER ADULTS </title> <p>This study examined the ability of young-old (ages 60-74 years) and old-old (ages 75-89 years) adults to acquire and retain basic computer skills The effects of two types of training methods on computer skill acquisition in these age groups also were explored Participants in this study were trained to perform basic computer procedures with either an animated interactive multimedia compact disk (CD-ROM) or an illustrated manual. They were then tested on their ability to perform these procedures immediately after training and I week later. The findings resealed the following. The young-old adults made fewer performance and motor control errors, required less assistance, and took less time for training than the old-old adults Some forgetting of factual information about the computers and how to perform some of the procedures took place over time in both age groups. In addition, measures of spatial and verbal working memory were significant predictors of computer skill acquisition in some instances. Finally, performance was approximately the same with the CD-ROM and the manual in both age groups. </p> <p>Adults older than age 65 report having less experience with personal computers than younger adults (Adler, 1995; Rogers, Cabrera, Walker, Gilbert, & Fisk, 1996). According to Morrell and Echt (1996, 1997), there are several reasons for this discrepancy in use. One reason is that younger individuals have had more training opportunities available to them than older individuals. Second, older adults may not be able to afford personal computers or the computer training classes that are available. Finally, most computer training materials have been designed for younger learners. Although age-related changes in certain cognitive mechanisms have been demonstrated reliably (see Craik & Salthouse, 1992), only a few studies have been conducted on how these age-related changes in cognition might affect the acquisition and retention of computer skills in older adults. Thus, there is little evidence at hand to guide the development of instructional materials specifically for older adults even if training opportunities were made available for them to learn how to use computers or if they had computers at home. </p> <hd id="AN0000219612-2"> AGE-RELATED DECLINES IN COGNITION </hd> <p>Findings from most of the studies that have been conducted on computer use and older adults demonstrate that there are age-related differences in the acquisition and performance of computer procedures. Most results suggest that older adults require more time than younger adults to acquire computer skills (Charnels, Schumann, & Boritz, 1992; Czaja & Sharit, 1993; Elias, Elias, Robbins, & Gage, 1987; Hartley, Hartley, & Johnson, 1984; Zandri & Charness, 1989). Older participants usually commit more errors when performing computer tasks (Charnels et al., 1992; Elias et al., 1987; Gist, Rosen, & Schwoerer, 1988; Zandri & Charness, 1989), and they also require more assistance than younger adults (Charnels & Bosman, 1992). Morrell and Echt (1996, 1997) suggested that age-related declines in cognitive resources, such as perceptual speed and verbal and spatial working memory, and other cognitive mechanisms, such as text comprehension, may play substantial roles in some of the age-related differences in computer skill acquisition that have been observed. </p> <p>The performance of cognitive tasks with increased age has been characterized by a general slowing of perceptual and motor processes involved in perceiving and responding to items, especially as task complexity increases (Hale & Myerson, 1995; Spiriduso & MacRae, 1990). Of the decrements in cognition that occur with increased age, perceptual speed (the speed at which mental operations are performed) is considered to be fundamental to understanding age-related differences in computer task performance (Salthouse, 1985). Therefore, the complex nature of computer task performance and age-related decrements in perceptual speed may be responsible for the age differences in the amount of time taken during computer training and some of the age-related differences in computer task performance that have been documented. </p> <p>Reliable findings also indicate that working memory capacity declines with age and is especially taxed when task complexity is increased (Salthouse, Mitchell, Skovronek, & Babcock, 1989). Working memory is usually conceptualized as the simultaneous processing and storage of information. Baddeley (1986) distinguished two types or systems that control the storage and processing of information in memory. One is the "central executive," which has a limited amount of processing capacity, some portion of which may be devoted to the short-term storage of information. Other storage demands may be divided between two subsidiary slave systems: the "articulatory loop," which is able to maintain verbal information (verbal working memory), and the "visuospatial scratch pad," which performs a similar function though the visualization of spatial material (spatial working memory). These constructs hold a number of implications for the study of computer skill acquisition in older adults. Verbal working memory capacity may influence the learner's ability to integrate written instructions. Spatial working memory capacity may affect performance when instructions are presented primarily in visual formats (e.g., in illustrations or animations). It is important to note, however, that results from research by Salthouse and Babcock (1991) suggest that age-related differences in perceptual speed contribute to some of the age-related differences in working memory that have been observed when performing simple operations. Therefore, these cognitive resources may predict the ability of older adults to acquire computer skills differentially in certain instances. For example, measures of perceptual speed may be better predictors of how well older adults can acquire simple computer skills than measures of working memory. </p> <p>Finally, the ability to comprehend text also may be an important consideration in the study of computer skill retention in older adults because text is the most common presentation format for computer instructions (e.g., pamphlets, manuals, on-line tutorials). The underlying assumption is that if information is better understood it is better remembered. It has been reliably shown, however, that older adults are less able to comprehend recently presented material than are young adults (Hartley, 1988). Therefore, it is possible that older adults are disadvantaged compared with younger adults in learning computer skills because of age-related declines in text comprehension. Further, measures of the more global cognitive construct of text comprehension may be better predictors of the acquisition of more complex computer skills in older adults than measures of perceptual speed and working memory, as scores on tests of perceptual speed and working memory have been shown to be more precise predictors of performance when cognitive demands are low. </p> <p>Little is known about the role of these various cognitive constructs in mediating the computer performance of older adults, as only a few studies have included instruments that might measure their effect on computer use by older adults (Kelley & Charness, 1994). Further, understanding the relationship between the cognitive changes that accompany aging and the performance of computer tasks might be especially beneficial for designing instructional materials for teaching adults older than age 75 (old-old adults) to use computers because the cognitive declines just outlined are likely to be more apparent in this age group than in young-old adults (aged 60-74). The research on teaching older adults to use computers, however, provides little information regarding computer skill acquisition in old-old adults (with the possible exception of Zandri and Charness [1989], whose sample included individuals up to age 84). Most of the available research has included comparisons between young adults (college students) and older adults ranging in age from 40 to 75. Further, little information is available in general about age-related changes in cognition in old-old adults compared with young-old adults. Therefore, Park (1992) suggested that comparisons between young-old and old-old adults may be more informative than those between young adults and old adults because such methodology may substantially reduce cohort effects and thus provide needed insight into age-related changes in very late adulthood. </p> <hd id="AN0000219612-3"> TRAINING STUDIES </hd> <p>There are several studies available that have examined the effectiveness of one training modality over another with young and older adults with some success. Gist et al. (1988) investigated the effects of a video modeling training technique compared with a computer-based tutorial on younger and older workers' ability to learn how to use a spreadsheet program. The modeling condition was found to increase performance relative to the tutorial condition for both age groups. It is possible that the model's demonstration reduced the amount of integration of the instructional material required relative to the other training condition by showing how the steps were actually were performed. Thus, demands on working memory were reduced and performance was facilitated. </p> <p>To determine if self-paced or fixed-paced learning conditions proved superior in older adults, Charness et al. (1992, experiment 2) conducted a study using word processing tasks. Their findings revealed that performance, independent of age, was greater under self-paced training conditions, indicating superior performance in situations lacking time pressure. In this instance, the self-paced condition may have alleviated the demands on perceptual speed in the older and younger adults, which in turn enhanced performance. </p> <p>Finally, Kelley, Charness, and Mottram (1994) investigated the effectiveness of three different interface styles on the learning of word processing in young, middle-aged, and older adults. The interface styles used were (a) keystrokes or function keys, (b) menus only, and (c) combination of menus and command icons. The menus and the menus-plus-command icons interfaces were the most effective in facilitating computer task performance across the age groups. In this study, the authors likened the superior formats to a cued recall paradigm, which is considered by researchers in cognition to reduce memory demands. Although none of these studies showed that one type of training might be differentially effective in training older adults to use computers relative to young adults, the results from these works do suggest that training methods that reduce cognitive demands are likely to enhance the acquisition of computer skills in both young and old adults. </p> <hd id="AN0000219612-4"> INSTRUCTIONAL DESIGN </hd> <p>Morrell and Echt (1996, 1997) suggested that instructions designed to take into consideration age-related changes in cognition should facilitate learning how to perform basic computer skills in older adults. In a study on a potentially relevant behavior, Morrell and Park (1993) compared the effect of instructions composed of text only, illustrations only, or text with illustrations on the ability of young and old participants to perform procedural assembly tasks. Results indicated that participants of both age groups made fewer errors in performance when provided with instruction composed of both text and illustrations compared with text- or illustration-only conditions. According to these authors, the addition of realistic-text relevant illustrations minimized the working memory demands of text by demonstrating visually the steps required for a procedure. Other findings suggest that animated illustrations might provide superior instruction on a wide variety of tasks compared with traditional static illustrations as were used by Morrell and Park (1993; Rieber, Boyce, & Assad, 1990; Spangenberg, 1973). Palmiter and Elkerton (1993) found that animated demonstrations paired with text resulted in greater computer skills acquisition and performance by young adults compared with text-only instructions. Presumably, training materials that include text and animated demonstrations reduce the spatial resources required to perceive the relationships in a dynamic presentation (Blake, 1977), reduce the abstract nature of ideas that involve changes over time (Rieber, 1994), and provide a more fluid and elaborate illustration of a procedure, which might function to reduce the number of inferences required of the learner. Thus, working memory demands may be reduced by animated illustrations above and beyond the level of static illustrations when combined with text. Moreover, animated instructions paired with text that support working memory might facilitate the acquisition of computer procedures in older adults to a greater degree than the level produced by static illustrations and text. </p> <p>The present study was designed to achieve three goals. The first was to investigate how advanced age might affect learning how to perform basic computer operations. This study is unique in that it is the first to examine the effect of very advanced age on computer task performance compared with young-old adults. Second, because it is likely that certain underlying cognitive mechanisms might be influential in the performance of computer tasks, the effects of age-related declines in perceptual speed, verbal and spatial working memory, and text comprehension on the performance and retention of computer procedures are explored. This is another unique aspect of this research, as few training studies with older adults have included all of these different types of measures of cognitive constructs. The third goal was to examine how two different training methods (instructions presented by a traditional illustrated manual and an interactive animated compact disk format) might affect basic computer skills acquisition in older adults. Systematic exploration has not been conducted with these two training methods with the oldest old. </p> <p>In general, it was hypothesized that (a) the old-old adults, even with careful design, would exhibit greater difficulty in learning how to perform computer tasks compared with the young-old adults (regardless of training modality) because of greater declines in cognitive ability in the older age group; (b) underlying cognitive mechanisms, in particular, spatial and verbal working memory, would surface as primary predictors of computer task performance because of the intensive working memory demands involved in performing computer tasks; and (c) animated illustrations combined with text were expected to facilitate the acquisition of basic computer skills relative to instructions presented in text and static illustrations because the animations would demonstrate the procedures described in the text. Thus, working memory demands would be decreased with animation and text above what could be accomplished with illustrations and text because less integration of the instructional material would be required in the animated condition. </p> <hd id="AN0000219612-5"> METHOD </hd> <hd id="AN0000219612-6"> Participants </hd> <p>Ninety-two community-dwelling older adults participated in this study. Forty-six of the participants were young-old adults, ranging in age from 60 to 74 years (M = 68.24, SD = 4.05), and 46 of the participants were old-old adults, ranging in age from 75 to 89 years (M = 78.80, SD = 3.09). The participants were volunteers recruited from two sources: the existing subject pool available from the University of Georgia and respondents from an advertisement placed in a local newspaper in Athens, Georgia. Volunteers were compensated for their participation in the amount of $20. There were 11 men and 35 women in each of the age groups. All participants were screened and excluded if they had Macintosh computer or Windows software experience. </p> <p>Vision was measured by a Snellen eye chart and all participants possessed at least 20/30 corrected binocular vision. A demographic-socioeconomic status questionnaire also was administered at the start of the experimental session. This questionnaire included items from the Older Americans Resources and Services Instrument Multidimensional Functional Assessment Inventory (Duke University Center for the Study of Aging and Human Development, 1975) about self-perceived health and number of medications currently taken and items concerned with income, education, and race. There were no significant differences between the age groups or the instructional groups in the responses to the items concerned with self-perceived health, income, or education. Specifically, 83% of the participants rated their general health as being excellent, very good, or good, and 91% of the participants rated their health compared with others their age as excellent, very good, or good. In terms of income, 83% of the participants indicated a middle to high average yearly household income. Most of the participants (76%) indicated that they had attended some college or had attained a graduate degree. These percentages are outlined in Table 1. The young-old and old-old adults did not differ in their vocabulary scores as measured by the Shipley Vocabulary Test (young-old: M = 34.00, SD = 5.30; old-old: M = 34.32, SD = 5.05). The old-old age group, however, reported taking more medications than the young-old age group (F [<reflink idref="bib1" id="ref1">1</reflink>, 90] = 4.07, p < .05; MSE = 3.40; M = 1.44, SD = 1.19 for the young-old and M = 2.22, SD = 2.09 for the old-old). </p> <hd id="AN0000219612-7"> Training Materials </hd> <p>An animated interactive multimedia compact disk (CD-ROM) and an illustrated manual were designed to teach participants basic computer skills and were produced by research staff at the University of Georgia using Authorware Professional Software (Macromedia, San Francisco, CA) and Aldus PageMaker 5.0 (Aldus Corporation, Seattle, WA). A number of design decisions for the development of these materials were made to accommodate the sensory, perceptual, and cognitive decrements known to occur with aging. These included elimination of any extraneous, and therefore interfering, information that did not appear relevant to the learner's needs. The textual information was written in a clear, concise, step-wise manner, and the use of computer jargon was avoided. Twenty-four-point Helvetica was used as the typeface for body copy. Key terms and concepts in the text were presented in bold type weight. Color in the blue-green wavelengths that have proved difficult for elderly learners to distinguish were avoided (Fozard, 1990). </p> <p>In the CD-ROM format, which was presented on line, textual information on how to perform basic procedures on a Macintosh computer was presented in steps, and each step or set of instructions was accompanied by an animated sequence that demonstrated the procedure. The manual-based instructions consisted of the same step-by-step written instructions as the interactive CD-ROM, with each step in the procedure illustrated in the text. The illustrations were created by capturing the series of frames directly from the animated demonstrations in the CD-ROM. Thus, the two instructional media differed primarily in terms of animation and whether the instructions were presented in the manual or on the computer. </p> <p>The training materials were structured around the theme "the house of Macintosh." The "house" was composed of three floors, each covering two topics of instruction. The first floor covered information and procedures relevant to the computer hardware (e.g., the mouse, pointing, clicking) and the desktop (e.g., the hard drive, menus, trash can). The second floor provided instruction about computer software (e.g., applications, documents) and icons, files, and folders (e.g., application icons, document icons). The third floor presented information about desktop management (e.g., copying files, emptying the trash) and windows (e.g., opening windows, closing windows). Each unit of instruction first described a procedure in text, and then a demonstration of the procedure was provided either in animation or illustrations. After the demonstration, the participants were required to perform two practice exercises for each procedure, and they received immediate feedback on their performance. There were 32 practice exercises over the six instruction units. At the end of each of the six sections, there were also five to seven multiple choice questions, which assessed the amount of factual information retained from each portion of instruction. </p> <p>An assessment of the skills gained through training was conducted when the participants reached the "top floor" of the house of Macintosh. The assessment was composed of three sections. The first section was composed of the same multiple choice questions presented throughout the training. The second section consisted of one of the two practice exercises that were presented for each procedure during training. The third section consisted of 20 new procedural exercises designed to test the ability of the learners to generalize the recently acquired procedural skills to new situations. </p> <p>All questions, practices, and immediate assessment exercises were performed on the computer for both instructional formats. In the CD-ROM format, these were a continuous part of the programming. In the manual format, the instructions directed the participants to press the space bar on the computer to perform the procedures. </p> <hd id="AN0000219612-8"> Design </hd> <p>This experiment was a 2 x 2 x 2 mixed factorial design, with age (young old vs. old-old) and instructional format (CD-ROM vs. manual) as the between-subject variables, and time of measurement (immediate assessment [immediately after training] vs. delay assessment [1 week later]) as the within-subject factor. </p> <hd id="AN0000219612-9"> Procedure </hd> <p>All participants were tested individually. The experimenter described the study as an attempt to learn more about how to teach people basic skills on a Macintosh computer. Before the computer instruction session, participants completed the vision assessment, the demographic questionnaire, and the Shipley Vocabulary Test, which measures verbal ability. The Shipley Vocabulary Test is composed of 50 multiple-choice items of increasing difficulty. The participants were presented with a word and instructed to choose which of the four available word choices had the same, or most nearly the same, meaning. Participants were then trained to perform the basic computer procedures with either the CD-ROM or the manual format. In both conditions, participants were told that the experimenter would remain in the room but that they should work through the training materials as independently as possible. In the CD-ROM condition, the participants were instructed to watch the computer screen, read the instructions, and perform the appropriate exercises on the computer after the experimenter had started the CD-ROM. Those participants in the manual condition were instructed to open their manuals first and then to watch the computer screen for further instructions. When prompted, participants were required to turn to the manual and read a section of instructions. The manual then instructed them to turn back to the computer, press the space bar, and perform the appropriate exercises. Participants were not able to review previous instructions in either condition. All participants were tested on the instructional material immediately after training, as described in the Training Materials section. </p> <p>After the participants finished the training session and immediate assessment, which took approximately 1.5 to 2.5 hours to complete, they were given a 10-minute rest period. The remainder of the cognitive battery was then administered. The first instrument administered was the Reading Span Test (Salthouse & Babcock, 1990), a measure of verbal working memory. This task required that participants read aloud a simple sentence that was presented on the computer screen. In addition, they answered a related question while simultaneously remembering the last word in the sentence they had just read. Participants initially were presented with a set of items requiring the recall of one word, and then the task was increased in complexity over sets of trials until an entire set was missed. Salthouse and Babcock (1990) indicated that the correlations between the total number of correct trials with odd-numbered sequence lengths and the total number of correct trials with even-numbered sequence lengths to be .76 and .75, respectively, for the Reading Span Test. </p> <p>Next, two selections from the Nelson-Denney Form H Reading Test (Brown, Fishco, & Hanna, 1993), which represents a measure of text comprehension, were administered. Participants were instructed to read each passage carefully and then to answer the five multiple-choice items concerning what they had read. The third cognitive task was the Size Judgment Test, a measure of spatial working memory (Cherry & Park, 1993). The task involved listening to a series of words that were the names of objects or animals and then saying these back to the experimenter in order of their physical size, from smallest to largest item. The participants initially were presented with a series of three trials, each with three items, and then they were increased in complexity (more items) until an entire series of trials was missed. Findings by Cherry and Park (1993) indicated that the Size Judgment Test is reliable. They reported a correlation of .79 between the first and second test trials. </p> <p>Finally, the participants performed the Letter Comparison Task (Salthouse & Babcock, 1991) to obtain a measure of perceptual speed. This task required participants to determine if two strings of letters were the same or different. Three sets of these comparisons were administered, each of which was composed of either three, six, or nine letters. Participants were given 30 seconds to complete as many of the comparisons in each set as possible. </p> <p>The entire experimental session was administered in invariant order and took approximately 3.0 to 3.5 hours. To prevent fatigue, participants were encouraged to take rest periods as needed throughout the session. The training and assessment segments of the experimental session were self-paced, and the cognitive tasks were administered in accordance with the time limits specified in the original source as deemed applicable. Participants then returned 1 week later and completed the delay assessment, which was identical to the assessment conducted immediately after training. </p> <hd id="AN0000219612-10"> RESULTS </hd> <hd id="AN0000219612-11"> Data Scoring </hd> <p>Multiple Choice Responses </p> <p>Thirty multiple-choice questions were posed to the participants during the immediate and delay assessments. The total number of correct responses to the multiple-choice items made were considered a measure of declarative knowledge successfully acquired during training. </p> <p>Error Categories </p> <p>There were three types of dependent measures recorded during the performance of the computer tasks: performance errors, motor control problems, and interventions. Performance errors included omission errors, commission errors, and wrong action errors. An omission error indicated that a step to a procedure was left out. A commission error entailed including an inappropriate additional step(s) to a procedure. Wrong action errors represented a clear attempt at a step in a procedure. The attempt, however, was incorrectly executed (e.g., opening an incorrect menu). </p> <p>There were two types of motor control problems recorded: mouse control errors and clicking errors. Mouse control errors refer to errors that were committed as a direct consequence of difficulty related to using the mouse (e.g., failure to double-click quickly enough to execute an action). Committing a clicking error indicated the making of arbitrary or superfluous mouse clicks unrelated to the procedure. </p> <p>The interventions error category included experimenter assistances, resignation errors, skipping errors, and number of questions asked. Experimenter assistances were recorded when the experimenter had to demonstrate a procedure to the participant physically. In contrast, a resignation error indicated that a clear attempt had been made to complete a procedure, however, the participant gave up before completion and did not ask for assistance. A skipping error indicated that the participant did not attempt a procedure but clicked instead on the "click here to continue" button or turned the page in the manual. Question asking refers to the number of inquiries made of the experimenter during a procedure. Session time also was recorded in addition to these error types. </p> <hd id="AN0000219612-12"> Univariate Analyses </hd> <p>Analyses on Multiple Choice Responses </p> <p>The total number of correct multiple choice responses were subjected to a 2 x 2 x 2 analysis of variance (ANOVA), with age (young-old vs. old-old) and instruction type (CD-ROM vs. manual) as between-subject variables, and time of measurement (immediate assessment vs. delay assessment) as the within-subject variable. A significant main effect for age occurred for the number of correct responses to the multiple-choice questions (F [<reflink idref="bib1" id="ref2">1</reflink>, 88] = 4.52 MSE = 30.02, p = 0.36), with the young-old participants making more correct responses (M = 24.22, SD = 3.77) to the questions than the old-old participants (M = 22.43, SD = 3.61). In addition, a main effect of time of measurement was observed (F [<reflink idref="bib1" id="ref3">1</reflink>, 88] = 46.91, MSE = 3.75p = .001). More correct multiple choice responses were made at the immediate assessment (M = 24.65, SD = 4.18) than at the delay assessment (M = 22.72, SD = 4.12). </p> <p>Analyses on Types of Errors </p> <p>The various error categories (performance errors, motor control problems, and interventions) were subjected individually to 2 x 2 x 2 ANOVAs, with age (young-old vs. old-old) and instruction type (CD-ROM vs. manual) as between-subject variables, and time of measurement (immediate assessment vs. delay assessment) as the within-subject variable. </p> <p>As shown in Table 2, the young-old participants consistently outperformed the old-old adults across all error categories and the amount of time taken to complete the training session. In terms of performance errors, there was a main effect for age, with the old-old participants committing more mistakes than the young-old participants (F [<reflink idref="bib1" id="ref4">1</reflink>, 881 = 5.18, MSE = 868.78 p c .03). There was also a main effect of age observed for the number of interventions required by the participants (F [1, 88] = 10.15, MSE = 104.07, p < .002). The old-old participants required almost twice the amount of assistance with procedures than the young-old participants required. The old-old participants also made more motor control errors than the young-old participants, as indicated by the main effect of age for motor control problems (F [<reflink idref="bib1" id="ref5">1</reflink>, 88] = 8.77, MSE = 778.74, p <.004). Finally, the findings indicated the presence of a main effect of age for the amount of time required during the training session (F [<reflink idref="bib1" id="ref6">1</reflink>, 88] = 7.57, MSE = 97.46, p <.01). The young-old participants required significantly less time than the old-old participants to complete the training session. </p> <p>The findings revealed some evidence that suggests that time of measurement had an effect on performance. A significant main effect for time of assessment was observed, with more performance errors made on the delay assessment (M = 34.94, SD = 24.45) than at the immediate assessment (M = 29.11, SD = 21.09); F [<reflink idref="bib1" id="ref7">1</reflink>, 88] = 11.19, MSE = 139.49, p < .001). </p> <p>No effect of training condition surfaced from these analyses. There were no significant main or interaction effects for training method observed across any of the ANOVAs conducted. </p> <hd id="AN0000219612-13"> Correlational Analyses </hd> <p>To examine the effect of the cognitive variables on the performance of the computer tasks by the older adults, correlational analyses were initially conducted between each of the cognitive measures (perceptual speed, verbal and spatial working memory, and text comprehension) and the categories of dependent measures (performance errors, motor control errors, and interventions) by training method and time of measurement. Results from the correlational analyses revealed no systematic significant relationships between the cognitive variables and motor control errors and, therefore, these findings also are not reported. The same pattern of significant correlations was obtained for the correlational analyses that were conducted on immediate and delay assessments, so only the findings from the delay data are discussed. </p> <p>As illustrated in Table 3, the measures of spatial and verbal working memory had significant relationships with both performance errors and number of experimenter interventions for the two training conditions. The measure of perceptual speed was significantly related to number of experimenter interventions in the CD-ROM condition and to both performance errors and interventions in the manual condition. The measure of text comprehension was significantly related to performance errors and interventions in the CD-ROM condition and to number of experimenter interventions in the manual condition. </p> <p>On the basis of these correlations, chronological age, and the measures of perceptual speed, verbal and spatial working memory, and text comprehension were entered into sets of hierarchical regression analyses for performance errors and number of experimenter interventions for both training conditions to determine if the cognitive measures had differential effects depending on the method of training used. </p> <hd id="AN0000219612-14"> Regression Analyses </hd> <p>Individual sets of hierarchical regression analyses were conducted on the number of performance errors made by the participants and on the number of interventions required at delay testing by training condition. In the first step of each of these sets of analyses, chronological age was entered alone to determine how much variance could be accounted for by this variable. In the steps that followed, the cognitive variables were entered in order from the most specialized measures of cognition (perceptual speed and spatial and verbal working memory) to the most global measure (text comprehension) collected because the specialized measures were expected to be the best predictors of the ability of older adults to acquire relatively simple (or basic) computer skills. Therefore, in the second step, the score on the measure of perceptual speed was entered because it was designated to be the most fundamental to the acquisition of basic computer skills. The measures of spatial and verbal working memory were entered in the third step, as these measures of cognitive resources were considered to be the next most influential of the cognitive variables on performance. The measure of text comprehension was entered alone in the fourth step as the most global measure of cognition related to computer skills acquisition. These plans are outlined in Tables 4 and 5. </p> <p>In general, findings from the regression analyses suggested that the measures of cognitive resources may have differential effects on the number of performance errors made depending on how an individual is trained. The results indicated that the measure of spatial working memory was a significant predictor of performance errors for the CD-ROM condition alone. As shown in Table 4, chronological age was not a significant predictor of performance errors in step one. Further, the measure of spatial working memory remained the only significant predictor when all the variables were entered in step four. Overall, the combination of these variables accounted for approximately 32% of the variance in the CD-ROM condition. For the manual condition, chronological age and the cognitive variables accounted for approximately 28% of the variance in the number of performance errors observed. Chronological age accounted for about 14% of the variance in step one. When perceptual speed was entered after chronological age in the second step, the amount of variance was significantly increased (approximately 10%). The measure of perceptual speed also remained the only significant predictor of performance errors when combined with chronological age and the measures of spatial and verbal working memory in step three. Finally, the measure of text comprehension did not significantly increase the cumulative R<sups>2</sups> in either of the sets of analyses performed when added to the equations in step four, suggesting that the more specialized measures of cognition were better predictors of performance errors in both training conditions. </p> <p>The findings from the regression analyses conducted on the number of interventions required by the participants revealed that a specialized measure of cognition may be an important predictor of number of experimenter interventions only when being trained with an interactive CD-ROM. As illustrated in Table 5, results from the sets of regressions conducted in the CD-ROM condition revealed that chronological age accounted for approximately 33% of the variance in step one. When chronological age and the cognitive variables were entered in step four, however, the measure of verbal working memory remained the only significant predictor. Approximately 44% of the variance was accounted for by all these variables for the number of experimenter interventions observed. For the manual condition, chronological age accounted for approximately 33% of the variance in step one. Although perceptual speed was a significant predictor of number of experimenter interventions in step two when entered after chronological age, the influence of this variable was diminished when the other cognitive variables were entered in steps three and four, suggesting that they may be highly related. Thus, chronological age was the only significant predictor of number of experimenter interventions in step four. Overall, this combination of variables accounted for approximately 45% of the variance in the manual condition. Again, the measure of text comprehension did not significantly increase the cumulative R<sups>2</sups> in either of the sets of analyses performed. </p> <hd id="AN0000219612-15"> DISCUSSION </hd> <p>The results from this study have provided considerable insight into (a) the effects of age on the acquisition of basic computer skills in older adults, (b) the effects of time on the ability of older adults to retain computer procedures, (c) the influence of certain underlying cognitive variables on performance and assistance required as a function of training method, and (d) the effects of different types of training formats on elderly adults' ability to learn how to perform basic computer tasks. </p> <p>The major findings from this research may be summarized as follows. First, results from the univariate analyses on multiple-choice responses, performance errors, motor control problems, interventions, and the amount of time required to complete the training session indicated that the young-old adults consistently outperformed the old-old adults across all of these dependent measures. The old-old made more performance and motor control errors, required more assistance, and took longer to complete the training session than the young-old adults. In particular, the significant age differences observed in each of these categories suggest that the oldest old may have more problems learning how to perform computer tasks than other age groups. Interestingly, these results are similar to those usually reported from training studies with young (college students) and older adults, with older adults requiring more time and assistance and making more errors than young adults. These findings, however, are the first to document age-related differences in computer task performance between different segments of the older population. </p> <p>Second, there was some evidence to suggest that time of measurement had an effect on performance. More multiple-choice items were answered correctly on the immediate assessment than on the delay assessment, and fewer performance errors were made on the immediate assessment than at delay testing by the older adults. Forgetting over time, however, was not restricted to the oldest age group because both groups of older adults exhibited poorer performance during the delay assessment compared with the assessment conducted immediately after training. This is a unique finding, as this research is the first to document the effect of time of testing on computer task performance in groups of older adults. It is also important to note that there were no effects of time observed for motor control problems encountered, which suggests that initial problems with mouse movements may disappear with practice in older adults. </p> <p>Third, results from the correlational analyses conducted indicated that certain underlying cognitive mechanisms may be related to basic computer skills acquisition in older adults in some instances. These include spatial and verbal working memory, text comprehension, and perceptual speed. It also appears that measures of cognitive resources may have differential effects on performance and assistance needed when learning basic computer skills depending on how an older individual is trained. It was originally hypothesized that spatial working memory would be a consistent predictor of computer skills acquisition in this sample of older adults. This hypothesis was partially supported, as results from the hierarchical regression analyses revealed that the measure of spatial working memory was the only significant predictor in the CD-ROM format for performance errors at delay testing for both age groups. This finding is consistent with the reports in the computer training literature, which suggest that measures of spatial working memory are highly predictive of computer performance (see Kelley & Charness [1994] for further discussion). In addition, the measure of verbal working memory was a significant predictor of number of experimenter interventions in the CD-ROM condition at delay testing. This finding would suggest that, although on-line training may require spatial ability, there is also a corresponding verbal component that must be addressed. The fundamental cognitive resource, perceptual speed, was the most predictive variable for performance errors, whereas none of the cognitive measures was predictive of number of experimenter interventions in the manual condition. Finally, the measure of text comprehension did not add significant amounts of variance in any of the sets of regression analyses conducted, suggesting that measures of cognitive resources may be better predictors of basic or simple computer skills acquisition than more global measures of cognition. </p> <p>Finally, there was no significant main effect of training condition observed in this study. Participants in the CD-ROM condition performed at approximately the same level as participants in the manual condition at both times of measurement. This result was unexpected because most findings in the literature indicate that instructions composed of text with animated demonstrations, as opposed to text with illustrations, facilitate the acquisition of new material or skills. Further, animation was expected to reduce working memory demands to a greater degree than illustrations when combined with text. The failure of the CD-ROM to facilitate the performance of older adults to a greater extent than the manual instruction might indicate, however, that this training method may serve equally well as a training tool for older adults as a standard manual; that is, older adults may be able to use interactive software and a manual when learning computer tasks. Alternatively, it may be that the careful structure and design of the training materials used in this study are responsible for the equivalent performance in the two conditions; that is, accommodations meant to compensate for decrements in sensory, perceptual, and cognitive systems by following a series of design directives (as was the case here) may facilitate performance on tasks such as those in this study, regardless of presentation format. </p> <p>This research has provided new information on training older adults to use computers and on the effect of cognitive decline in the oldest-old on computer task performance. Overall, these findings suggest that older adults are capable of acquiring computer skills using different types of training materials. Additional care, however, should be taken when teaching the oldest-old how to use computers. </p> <p>This research was conducted as Katharina V. Echt's masters thesis directed by Denise C. Park and Roger W. Morrell and was supported by National Institute on Aging grant AC11715-03 to Roger W. Morrell as a research component of the Center for Applied Cognitive Research on Aging at the University of Michigan. The research was conducted at the University of Georgia. </p> <p>We thank Rich Marsh and Kathy Kidd for their valuable comments on an earlier version of this article and Joan Bennett for statistical assistance. </p> <p>Address correspondence to Dr. Roger W. Morell, Institute for Social Research, University of Michigan, 426 Thompson Street, Room 5256, Ann Arbor, MI 48106-1248, USA. E-mail: rmorreU@umich.edu </p> <hd id="AN0000219612-16">TABLE 1 Demographic characteristics of the participants</hd> <ct id="AN0000219612-17"> Young-old Old-old (%; n 46) (%; n 46) Self-perceived health Excellent 20 4 Very good 26 33 Good 35 48 Fair 20 15 Poor 0 0 Health relative to others Excellent 24 17 Very good 28 48 Good 37 28 Fair 11 7 Poor 0 0 Income <$10,000.00 11 9 10,000-19,999 18 24 20,000-29,999 29 22 30,000-49,999 20 22 50,000-69,999 16 16 >70,000 7 7 Education (yrs) 8 0 4 9-11 4 11 12 20 9 13-15 28 17 16 24 24 >16 24 35</ct> <hd id="AN0000219612-18">TABLE 2 Performance errors, interventions, motor control errors, and time</hd> <ct id="AN0000219612-19"> Dependent measures (M [SD]) Performance No. of Age group errors interventions Young-old 27.08 (16.97) 8.16 (7.16) Old-old 36.97 (23.99) 15.02 (12.62) Dependent measures (M [SD]) Motor Training Age group control time (min) Young-old 11.89 (10.83) 102 (32.74) Old-old 21.61 (19.79) 120 (29.75)</ct> <hd id="AN0000219612-20">TABLE 3 Correlations between performance errors and interventions and measures of vocabulary ability, text comprehension ability, perceptual speed, spatial working memory, and verbal working memory by training condition at the delay assessment</hd> <ct id="AN0000219612-21"> CD-ROM Performance No. of Measure errors interventions Spacial working -.50[**] -.43[*] memory Verbal working -.39[*] -.58[**] memory Text comprehension -.43[*] -.39[*] Perceptual speed -.34[*] NS Manual Performance No. of Measure errors interventions Spacial working -.43[*] -.47[**] memory Verbal working -.35[*] -.33[*] memory Text comprehension NS -.36[*] Perceptual speed -.43[*] -.47[**] Note. NS = not significant. [*] p <.05. [**] p <.001.</ct> <hd id="AN0000219612-22">TABLE 4 Outline of multiple regression analyses conducted on performance errors by training condition at delay assessment</hd> <ct id="AN0000219612-23"> Predictor Beta R<sups>2</sups> Cumulative F change R<sups>2</sups> CD-ROM condition Step one Age .222 .049 2.28 Step two Age .122 Perceptual speed -.296[*] .078 .127 3.13[*] Step three Age .056 Perceptual speed -.233 Spatial WM -.277[*] Verbal WM -.189 .153[*] .280 3.99[*] Step four Age .128 Perceptual speed -.203 Spatial WM -.271[*] Verbal WM -.054 Text -.247 .041 .321 3.79[*] Manual condition Step one Age .373[*] .139 7.13[*] Step two Age .246[*] Perceptual speed -.340[*] .099[*] .239 6.74[**] Step three Age -.238 Perceptual speed -.280[*] Spatial WM .028 Verbal WM -.221 .039 .278 3.94[*] Step four Age .227 Perceptual speed -.257 Spatial WM .029 Verbal WM -.218 Text -.075 .005 .282 3.15[*] Note. WM = working memory. [*] p < .05. [**] p < .001.</ct> <hd id="AN0000219612-24">TABLE 5 Outline of multiple regression analyses conducted on interventions by training condition at delay assessment</hd> <ct id="AN0000219612-25"> Predictor Beta R<sups>2</sups> Cumulative F change <sups>2</sups> CD-ROM condition Step one Age .328[*] .108 5.32[*] Step two Age .270[*] Perceptual speed -.17 .026 .134 3.32[*] Step three Age .149 Perceptual speed -.143 Spatial WM -.142 Verbal WM -.463[**] .281[**] .415 7.28[**] Step four Age .201 Perceptual speed -.121 Spatial WM -.137 Verbal WM -.363[*] Text -.182 .022 .438 6.23[**] Manual condition Step one Age .570[**] .325 21.22[**] Step two Age .459[**] Perceptual speed -.298[*] .076[*] .402 14.44[**] Step three Age .439[**] Perceptual speed -.214 Spatial WM -.096 Verbal WM -.136 .032 .434 7.87[**] Step four Age .420[**] Perceptual speed -.175 Spatial WM -.095 Verbal WM -.13 Text -.126 .013 .448 6.48[**] Note. WM = working memory. [*] p < .05. [**] p < .001.</ct> <hd1 id="AN0000219612-26"> REFERENCES </hd1> <p>Adler, R.P. (1995). Older adults and computers: Report of a national survey. Technical Report for SeniorNet, San Francisco. </p> <p>Baddeley, A D. (1986). Working memory. Oxford: Clarendon. </p> <p>Blake, T. (1977). Motion in instructional media: Some subject-display mode interactions. Perceptual and Motor Skills, 44, 975-985. </p> <p>Brown, J. I., Fishco, V. V., & Hanna, G. (1993). The Nelson Denney Reading Test. Chicago: Riverside. </p> <p>Charness, N., & Bosman, E. A. (1992). Human factors and aging. In F. I. M. Craik & T. A. Salthouse (Eds.), The handbook of aging and cognition (pp. 495-545). Hillsdale, NJ: Lawrence Erlbaum. </p> <p>Charness, N., Schumann, C., & Boritz, G. (1992). Training older adults in word processing: Effects of age, training technique, and computer anxiety. International Journal of Technology and Aging, 5, 79-105. </p> <p>Cherry, K E., & Park, D. C. (1993). Individual difference and contextual variables influence spatial memory in younger and older adults. Psychology and Aging, 8, 517-526. </p> <p>Craik, F. I. M., & Salthouse, T. A. (1992). The handbook of aging and cognition. Hillsdale, NJ: Lawrence Erlbaum. </p> <p>Czaja, S. J., & Sharit, J. (1993).Age differences in the performance of computer based work. Psychology and Aging, 8, 59-67. </p> <p>Duke University Center for the Study of Aging and Human Development. (1975). OARS Multidimensional Functional Assessment Questionnaire. Durham, NC: Duke University Center for the Study of Aging and Human Development, Duke University Medical Center. </p> <p>Elias, P. K, Elias, M. F., Robbins, M. A., & Gage, P. (1987). Acquisition of word processing skills by younger, middle-age, and older adults. Psychology and Aging, 2, 340-348. </p> <p>Fozard, J. L. (1990). Vision and hearing in aging. In J. E. Birren & K W. Schaie (Eds.), Handbook of the psychology of aging (3rd ed.) (pp. 150-170). New York: Academic Press. </p> <p>Gist, M., Rosen, B., & Schwoerer C. (1988). The influence of training method and trainee age on the acquisition of computer skills. Personnel Psychology, 41, 255-265. </p> <p>Hale, S., & Myerson, J. (1995). Fifty years old, fifty per cent slower? Meta-analytic regression models and semantic context effects. Aging and Cognition, 2, 132-145. </p> <p>Hartley, J. (1988). Aging and individual differences in discourse memory. In L. L. Light and D. M. Burke, (Eds.), Language, memory, and aging (pp. 36-57). New York: Cambridge University Press. </p> <p>Hartley, A. A., Hartley, J. T., & Johnson, S. A. (1984). The older adult as computer user. In P. K. Robinson, J. Livingston, & J. E. Birren (Eds.), Aging and technological advances (pp.347-348). New York: Plenum. </p> <p>Kelley, C., Charness, N., & Mottram, M. (1994). The effects of cognitive aging and prior computer experience on learning to use a word processor Paper presented at Cognitive Aging Conference, Atlanta, GA. </p> <p>Kelley, C. L., & Charness, N. (1994). Training older and younger computer novices to use a word processor. Canadian Psychology, 35, 16. </p> <p>Morrell, R. W., & Echt, K V. (1997). Designing instructions for computer use by older adults. In A. D. Fisk & W. A. Rogers (Eds.), Hand book of human factors and the older adult (pp. 335-361). New York: Academic Press. </p> <p>Morrell, R. W., & Echt, K. V. (1996). Instructional design for older computer users: The influence of cognitive factors. In W. A. Rogers, A. D. Fisk, & N. Walker (Eds.), Aging and skilled performance:Advances in theory and applications. (pp.241-265). Mahwah, NJ: Lawrence Erlbaum. </p> <p>Morrell, R. W., & Park, D. C. (1993). The effects of age, illustrations, and task variables on the performance of procedural assembly tasks. Psychology and Aging, 8, 389-399. </p> <p>Palmiter, S., & Elkerton, J. (1993). Animated demonstrations for learning procedural computer-based tasks. Human-Computer Interaction, 8, 193-216. </p> <p>Park, D. C. (1992). Applied cognitive aging research. In F. Craik & T. A. Salthouse (Eds.), The handbook of aging and cognition (pp. 449-493). Hillsdale, NJ: Lawrence Erlbaum. </p> <p>Rieber, L. P. (1994). Computers, graphics, and learning Madison, WI: Brown & Benchmark. </p> <p>Rieber, L. P., Boyce, M. J., & Assad, C. (1990). The effects of computer animation on adult learning and retrieval tasks. Journal of Computer-Based Instruction, 17, 46-52. </p> <p>Rogers, W. A., Cabrera, E. F., Walker, N., Gilbert, D. K., & Fisk, A. D. (1996). A survey of automatic teller machine usage across the adult life span. Human Factors, 38, 1-11. </p> <p>Salthouse, T. A. (1985). Speed of behavior and its implications for cognition. In J. E. Birren & K. W. Schaie (Eds.), Handbook of the psychology of aging (pp. 400-426). New York: Van Nostrand Reinhold. </p> <p>Salthouse, T. A., & Babcock, R. L. (1990). Computation and listening span tasks, Atlanta, GA: Georgia Institute of Technology. </p> <p>Salthouse, T. A., & Babcock, R. L. (1991). Decomposing adult age differences in working memory. Developmental Psychology, 27, 763-776. </p> <p>Salthouse. T. A., Mitchell, D. R., Skovronek, E., & Babcock, R. L. (1989). Effects of adult age and working memory on reasoning and spatial abilities. Journal of Experimental Psychology, 15, 507-516. </p> <p>Schwartz, J. (1988). The computer market. American Demographics, 10, 38 -41. </p> <p>Spangenberg, R. W. (1973). The motion variable in procedural learning. AV Communication Review, 21, 419-436. </p> <p>Spiriduso, W. W., & MacRae, P. G. (1990). Motor performance and aging. In J. E. Birren & K W. Schaie (Eds.), Handbook of the psychology of aging (pp. 183-200). New York: Academic Press. </p> <p>Zandri, E., & Charness, N. (1989). Training older and younger adults to use software. Educational Gerontology, 15, 615-631. </p> <aug> <p>By Katharina V. Echt The University of Georgia, Athens, Georgia, USA and Roger W. Morrell and Denise C. Park The Institute for Social Research, The University of Michigan, Ann Arbor, Michigan, USA </p> </aug> <nolink nlid="nl1" bibid="bib1" firstref="ref1"></nolink>
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  Data: Effects of Age and Training Formats on Basic Computer Skill Acquisition in Older Adults.
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  Data: <searchLink fieldCode="SO" term="%22Educational+Gerontology%22"><i>Educational Gerontology</i></searchLink>. Jan-Feb 1998 24(1):3-25.
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  Data: <searchLink fieldCode="DE" term="%22Age%22">Age</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Literacy%22">Computer Literacy</searchLink><br /><searchLink fieldCode="DE" term="%22Memory%22">Memory</searchLink><br /><searchLink fieldCode="DE" term="%22Multimedia+Instruction%22">Multimedia Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Older+Adults%22">Older Adults</searchLink><br /><searchLink fieldCode="DE" term="%22Online+Systems%22">Online Systems</searchLink><br /><searchLink fieldCode="DE" term="%22Optical+Disks%22">Optical Disks</searchLink><br /><searchLink fieldCode="DE" term="%22Reading+Comprehension%22">Reading Comprehension</searchLink><br /><searchLink fieldCode="DE" term="%22Skill+Development%22">Skill Development</searchLink>
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  Data: Computer procedures were taught with either interactive multimedia CD-ROMs or manuals to 46 adults aged 60-74 and 46 aged 75-89. The younger group made fewer errors, required less help, and took less time. Both groups forgot some facts and procedures over time. Format did not affect performance. Spatial and verbal memory, text comprehension, and perceptual speed influenced performance. (SK)
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