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Najjar, L. J. (1998). Principles of educational multimedia user interface design. Human Factors, 40(2), 311-323.

  

 

Principles of Educational Multimedia User Interface Design

LAWRENCE J. NAJJAR,1 Georgia Tech Research Institute, Atlanta, Georgia

This paper discusses principles of educational multimedia user interface design. The purpose of the principles is to maximize the learning effectiveness of multimedia applications. The principles are based on the results of studies in psychology, computer science, instructional design, and graphics design. The principles help user interface designers make decisions about the learning materials, learners, tasks that the learners perform, and tests for measuring learning performance.

1Requests for reprints should be sent to Lawrence J. Najjar, Georgia Institute of Technology, Georgia Tech Research Institute, GTRI/EOEML/MARC Rm. 335, Atlanta, GA 30332-0823; http://mime1.marc.gatech.edu/imb/people/ larry.html.

 

INTRODUCTION

Multimedia user interfaces combine different media such as text, graphics, sound, and video to present information. Due to improvements in technology and decreases in costs, many human factors engineers will soon find themselves designing user interfaces that include multimedia. Since many educators, parents, and students believe that multimedia helps people to learn, one popular application of this technology will be the field of education.

Unfortunately, the existing educational multimedia user interface design guidelines are almost entirely based on the opinions of experts (e.g., Allen, 1974; Arens, Hovy, & Vossers, 1993; Feiner & McKeown, 1990, 1991; Reiser & Gagné, 1982) rather than on the results of empirical research. This gives us a weak foundation for making design decisions and slows progress in making educational multimedia user interfaces more effective.

The purpose of this paper is to describe empirically-based principles that multimedia user interface designers can employ to create applications that improve the likelihood that people will learn. The principles are derived from studies conducted in a wide variety of fields that include psychology, computer science, instructional design, and graphics design. The principles focus on educational multimedia applications. Other sources (e.g., Mayhew, 1992; Smith & Mosier, 1986) provide more general user interface design principles and guidelines.

In any learning situation, four basic factors should be considered when evaluating learning (Bransford, 1978; Jenkins, 1979): the characteristics of (a) the materials, (b) the learner, (c) the learning task, and (d) the test of learning.

Characteristics of the Materials

The characteristics of the learning materials can significantly affect learning. Learning material characteristics include the medium, physical structure, psychological structure, conceptual difficulty, and sequence (Bransford, 1978). The following principles suggest ways to design the learning materials to improve learning.

Use the Medium that Best Communicates the Information. Although opinions differ (e.g., Clark, 1983; Mayer, 1997), limited evidence suggests that some media are better than others at communicating certain kinds of information (e.g., Najjar, 1996b). For example, when a learner needs to remember a small amount of verbal information for a short period of time, information that is presented via the auditory medium is generally remembered better than information that is presented via text. In one study (Murdock, 1968), learners recalled and recognized 10 items from a list better when the experimenter presented the items using sound than when the experimenter used text. This result is very consistent (Penney, 1975; Watkins & Watkins, 1980). Studies that found conflicting results (e.g., Marcer, 1967; Sherman & Turvey, 1969) used long retention intervals or inappropriate instructions or scoring methods.

For retaining information over longer periods of time, text appears to be better than sound for communicating verbal information. Text was superior when the verbal information was a list of words (Severin, 1967), instructions (Sewell & Moore, 1980), four-line poems (Menne & Menne, 1972), and nonsense syllables (Chan, Travers, & Van Mondfrans, 1965; Van Mondfrans & Travers, 1964). However, one study (Van Mondfrans & Travers, 1964) found no learning differences between auditory and textual words. Also, if the learner's visual channel is already occupied, then it may be more appropriate to use audio verbal information than textual information. This situation occurs, for example, when pictorial animations and auditory verbal information are presented together (e.g., Baggett & Ehrenfeucht, 1983; Mayer & Anderson, 1992).

A picture, it is commonly said, can be worth a thousand words. Pictures seem to help people learn information more effectively than text. This picture superiority effect appears to be strong. For example, pictures of common objects were recalled and recognized better than their textual names (e.g., Lieberman & Culpepper, 1965; Nelson, Reed, & Walling, 1976; Paivio & Csapo, 1969, 1973; Paivio, Rogers, & Smythe, 1968). Exceptions seem to occur when the items are conceptually similar (e.g., all animals or all tools) causing the pictures to be easily confused (Nelson et al., 1976), or when the items are presented so quickly that learners cannot create verbal labels for the pictures (Paivio & Csapo, 1969). Also, pictures cannot be used to communicate abstract concepts such as "freedom" or "amount."

Pictures also seem to be better than text or auditory instructions for communicating spatial information. For example, pictures helped people to draw and label the human heart (Dwyer, 1967a, 1967b), recall and recognize spatial relationships in a story (Garrison, 1978), and solve bus route problems (Bartram, 1980). To communicate motion-based information that changes continuously over time, when it is important to show how the information changes over time, animation or video appear to be best (Baek & Layne, 1988; Rieber, 1990a, 1990b; Rigney & Lutz, 1976; Roshal, 1961; Spangenberg, 1973). These studies used knot-tying tasks, assembly or disassembly tasks, and interactive, explanatory computer animations. Animation or video does not seem to be helpful when the information to be learned is difficult for learners to understand (e.g., Rieber, 1989), the information does not need visual support (e.g., Carabello, 1985), or the learners do not practice with an interactive animation (e.g., Rieber, 1990b).

When used in more complex ways, the benefits of pictures are less strong. One study (Baggett, 1979) found that, on an immediate test, people recalled the structure of a story (exposition, complication, resolution) equally well when the story was presented via a silent movie or when it was presented via closely matched text. Another study (Nugent, 1982) also found no differences in immediate recall of story content when matched information was presented via silent video, text, or narration. However, when one of the studies (Baggett, 1979) tested recall performance after a week, performance was better for the pictorial story than the textual story.

Thus some media appear to communicate specific kinds of information better than other media. For communicating verbal information, text is better than auditory narration. For recalling and recognizing items, pictures are better than text. Pictures are also better than text or narration for communicating spatial information.

Use Multimedia in a Supportive, Not a Decorative, Way. There is strong empirical support for this design principle, especially for the use of supportive pictures with verbal information. Other multimedia combinations are not as well supported. The information being presented in one medium needs to support, relate to, or extend the information presented in the other medium. Several studies show that adding closely related, supportive illustrations to textual or auditory verbal information improves learning performance. For example, pictures improved recall of textual words (Paivio & Csapo, 1973), recall and comprehension of textual passages (Levie & Lentz, 1982), recall of auditory passages (Levin & Lesgold, 1978), and comprehension of auditory passages (Bransford & Johnson, 1972).

Some multimedia application designers apparently believe that pictures improve learner interest, motivation, and, therefore, learning. This does not appear to be the case. Adding unrelated illustrations does not improve learning, and in fact it may actually decrease learning. Unrelated illustrations did not improve comprehension and recall of textual material (Levie & Lentz, 1982; Sewell & Moore, 1980) or recall of illustration captions (Bahrick & Gharrity, 1976; Evans & Denny, 1978). One investigator (Peeck, 1974) found that adding supportive illustrations to text helped fourth-grade children retain verbal information. But unrelated illustrations (Peeck, 1985 as cited in Winn, 1993) made it harder for learners to comprehend the text.

These results suggest that the mere presence of illustrations does not improve the learning of verbal information. The illustrations must help explain information that is presented by the verbal medium. It appears that supportive illustrations allow learners to build cognitive connections between the verbal and pictorial information (Paivio, 1971, 1986; 1991; Clark & Paivio, 1991). This dual-coded information leads to improved learning (Mayer & Anderson, 1991; Najjar, 1995a; Paivio & Csapo, 1973).

It is clear that supportive illustrations help people to learn verbal information. A small number of studies suggest that animations (e.g., Mayer & Gallini, 1990; Park & Hopkins, 1993) and videos (Nugent, 1982; Spangenberg, 1973) may also improve verbal information learning. However, additional studies must be performed before we can extend this principle to media combinations other than illustrations with textual or auditory verbal information.

Present Multimedia Synchronously. There is strong support for the idea that verbal-pictorial information should be presented together. For example, college students performed better on problem-solving transfer tests when textual annotations were integrated into explanative drawings than when the experimenters presented the text and drawings sequentially (Mayer, 1989a, 1989b; Mayer & Gallini, 1990), or simultaneously in time, but physically spaced apart (Mayer, Steinhoff, Bower, & Mars, 1995). Creative problem solving and recognition were also higher when an auditory, explanative narration was synchronized with an explanative animation or movie compared to a situation in which the narration preceded or followed the animation (Baggett, 1984; Baggett & Ehrenfeucht, 1983; Mayer & Anderson, 1991, 1992).

Exceptions to the advantage of simultaneous presentation of related verbal and pictorial information occurred when the learners were very knowledgeable about the domain being studied (Mayer et al., 1995); when verbal recall, rather than problem-solving ability, was measured (Mayer, 1989a, 1989b; Mayer & Gallini, 1990); and when learning was measured a week later, after the learned information faded in both conditions (Baggett & Ehrenfeucht, 1983).

Synchronized presentation of verbal-pictorial information appears to improve learning better than sequential presentations. The synchronized presentation may help learners to use dual (verbal + pictorial) coding (Paivio, 1971, 1986, 1991; Clark & Paivio, 1991) to increase cognitive interconnections between the two forms of studied information and to prior knowledge.

Use Elaborative Media. There is limited, somewhat indirect evidence that the media themselves may encourage elaborative processing. Elaborative processing is extra cognitive processing of material that helps to integrate the material with prior knowledge. Elaborative processing often leads to improvements in learning performance (Anderson, 1980, 1983; Anderson & Reder, 1979; Palmere, Benton, Glover, & Ronning, 1983; Stein & Bransford, 1979; Pressley, McDaniel, Turnure, Wood, & Ahmad, 1987; Reder, 1979). Some media may encourage spontaneous elaborative processing of information more than other media (Najjar, 1996a). For example, pictures may be more elaborative than text. This appears to be the case when learning is measured using recognition (e.g., Hartman, 1961; Nelson et al., 1976; Read & Barnsley, 1977; Shepard, 1967) or recall (e.g., Paivio, 1975; Paivio & Csapo, 1973; Paivio et al., 1968). One study (Read & Barnsley, 1977) even obtained this result when the researchers used a study-test interval of 20 years.

Although there are some exceptions (see the previous section titled "Use the medium that best communicates the information"), the learning advantage for pictures, compared with text, may occur because pictures have more features available for processing than do words, and pictures may help access meaning more quickly and completely than words (Nelson, 1979; Smith & Magee, 1980;).

Text may also be more elaborative than audio verbal media. Several studies (Menne & Menne, 1972; Severin, 1967; Van Mondfrans & Travers, 1964) found that text-only conditions produced better learning than audio-only conditions. However, unlike audio conditions, text conditions also allow the learner to process the verbal information at the learner's pace.

Some multimedia combinations may be more elaborative than other multimedia combinations or single media due to the advantages of dual coding. Information that is processed through both verbal and pictorial channels appears to be learned better than information that is processed through just the verbal channel or just the pictorial channel (Barrow & Westley, 1959; Levin, Bender, & Lesgold, 1976; Mayer & Anderson, 1991; Nugent, 1982; Paivio, 1975; Paivio & Csapo, 1973; Pezdek, Lehrer, & Simon, 1984; Stoneman & Brody, 1983; Wetstone & Friedlander, 1974). For example, Severin (1967) found that learning performance in a combined audio and pictures condition was better than in a combined audio and text condition. Nugent (1982) obtained the highest learning levels when she presented information via combined text and pictures or combined audio and pictures compared to the same content presented via text alone, audio alone, or pictures alone.

It appears that elaborative media (e.g., pictures versus text, text versus audio narration) may improve learning performance more than media that may not be as elaborative. Multimedia that encourages the learner to use both verbal and pictorial channels to process the information also appears to be very effective.

Make the User Interface Interactive. This design principle is strongly supported by a variety of studies. Interaction is mutual action between the learner, the learning system, and the learning material (Fowler, 1980). An interactive user interface may allow learners to control, manipulate, and explore the material or periodically asks learners to answer questions that integrate the material. An interactive user interface appears to have a significant positive effect on learning from multimedia (e.g., Bosco, 1986; Fletcher, 1989, 1990; Stafford, 1990; Verano, 1987). For example, one researcher (Stafford, 1990) statistically analyzed 96 learning studies and concluded that interaction was associated with learning achievement and retention of knowledge over time. Other researchers (Bosco, 1986; Fletcher, 1989, 1990) examined 75 learning studies and found that participants learned the material faster and had better attitudes toward learning the material when they learned in an interactive instructional environment.

Interaction may improve learning because it encourages learners to elaboratively process the learning material (e.g., Bower & Winzenz, 1970; Jacoby, Craik, & Begg, 1979; Kolers, 1979; Salomon, 1984; Walker, Jones, & Mar, 1983). The interaction must be cognitively engaging. Learners who read screen after screen of text or who get only simple "Right" and "Wrong" feedback to their responses are unlikely to learn (e.g., Bosco, 1986; Fowler, 1980; Verano, 1987). Also, interactivity may have a stronger effect on immediate learning than long-term retention of the information (Fletcher, 1989).

Characteristics of the Learner

Characteristics of the learner can have an impact on learning. Characteristics of the learner include the learner's current skills, knowledge, and attitudes (Bransford, 1978). The following principles describe learner characteristics that are associated with learning from educational multimedia.

Use Educational Multimedia with Naive and Lower-Aptitude Learners. Because few studies on this topic exist, the evidence supporting this design principle is somewhat limited. Multimedia information appears to be more effective for learners with low prior knowledge or aptitude in the domain being learned. Regarding naive learners, Mayer and Gallini (1990) found that illustrations helped college students with low prior knowledge of automobile mechanics to recall textual explanatory information and to solve creative problems. Adding illustrations to the text did not generally affect the learning performance of students who had high prior knowledge of these devices. Other studies found similar effects for teaching natural science to fifth-graders (Kraft, 1961), geology and meteorology to college students (Dean & Enemoh, 1983; Kunz, Drewniak, & Schott, 1989), and basic training information to army recruits (Kanner & Rosenstein, 1960; Kanner, Runyon, & Desiderato, 1954). However, although this effect occurred in several studies, it was not always consistent (e.g., Mayer & Gallini, 1990, experiments 2 and 3).

Multimedia also appears to be more helpful for learners with low aptitude than learners with high aptitude. For example, in one study (Blake, 1977), college students with low or high aptitude in spatial and mental abilities learned the pattern of movement of five chess pieces via moving pictures (film), static pictures with animated arrows, or static pictures alone. The students with low aptitude performed better in the conditions with motion than the condition with static pictures alone. However, the students with high aptitude performed similarly on all three kinds of pictures. Wardle (1977, as cited in Levie & Lentz, 1982) gave 800-word textual passages on various science topics to seventh-grade students. Some of the passages included supportive illustrations. Poor readers performed better on a comprehension test when the passages included illustrations. For good readers, the illustrations had no effect.

Although only a handful of studies examined this principle, the results of these studies suggest that multimedia is most effective for people with low prior knowledge or aptitude in the domain being learned. This may be because experts have prior knowledge that can be used to understand and integrate the new information, but novices lack this advantage. Also, novices may not know which information is important and on which information they should focus their attention. Learners with high aptitude appear to be able to learn from relatively non-elaborative media such as text, but low-aptitude learners benefit most from the elaborative and explanatory advantages offered by multimedia. High-aptitude learners may be good learners, regardless of the media used to present the information (e.g., Kanner & Rosenstein, 1960; Kanner et al., 1954; Kraft, 1961).

Present Educational Multimedia to Motivated Learners. A variety of studies provide moderately strong support for this design principle. Using external rewards, such as points or grades, to improve motivation does not appear to improve learning (Anderson, 1994; Harley, 1965; Loftus, 1972). For example, Loftus (1972) found that when he increased the number of points for recognizing certain pictures from a large set of pictures, people spent more time looking at the more rewarding pictures, and recognized those pictures better in the recognition test. However, when he controlled for the amount of time spent looking at each picture, the reward had no effect. The reward affected what people learned, but not how well people learned. Other researchers (Condry, 1977; Entin, 1974; Lepper & Greene, 1978; Lepper, Greene, and Nisbett, 1973) found that adding external rewards to a task may actually decrease the learner’s intrinsic motivation and cause the learner to spend less time on the task than learners who are not externally motivated.

Intrinsic motivation, however, appears to improve learning. An intrinsically-motivated learner tends to learn more than an unmotivated learner. For example, Bickford (1989) found that high school students learned more from paper-based materials that were designed to improve intrinsic motivation than materials that were not designed this way. Entin (1974) found that students who scored higher on an achievement motivation questionnaire tried more math problems and scored higher on an achievement test than students who scored lower on the motivation questionnaire. Another study (Raynor, 1974) obtained similar results.

There are several ways to improve the learner's intrinsic motivation. The user interface designer can relate the content and objectives of the instructions to the needs and interests of the learner (Keller, 1983). This can be done by using familiar metaphors and analogies (Curtis & Reigeluth, 1984). For example, Ross (1983) found that learning performance in a statistics course was improved when the exercises used contexts that were related to the majors of the students rather than exercises that used generic contexts. Other studies (Flesch, 1948; Flesch & Lass, 1949; McConnell, 1978) suggest that instructional designs that use a personal style (e.g., personal pronouns, names of specific people, direct quotations, vignettes of famous people) rather than a formal style may stimulate learner interest. It appears that providing immediate, positive, verbal praise and informative feedback in a context that does not control the consequences of the performance (e.g., does not have a direct impact on the student’s grade) may improve intrinsic motivation (Bates, 1979; Condry, 1977; Deci, 1975; Keller, 1983). Also, general suggestions on how to improve learning performance should be given right before the next performance attempt (Keller, 1983; Tosti, 1978).

Multimedia material itself appears to offer motivational advantages because of its novelty, but these advantages (and the novelty) fade over time (Clark, 1983, 1985; Clark & Craig, 1992; Kulik, Bangert, & Williams, 1983). Finally, humor does not improve motivation because it can distract the learner from the instructional goals and interfere with comprehension (e.g., Markiewicz, 1974; Sternthal & Craig, 1973).

To Avoid Developmental Effects, Use Educational Multimedia with Adults and Older Children. Although it is difficult to establish specific age ranges, empirical studies provide moderate support for this design guideline. Multimedia appears to more effectively improve learning as children get older. On recognition and recall of information in films, older children did better than younger children and adults did better than older children (Stevenson & Siegel, 1969); the same result was obtained on recognition and recall of pictures (Dirks & Neisser, 1977; Hoffman & Dick, 1976), television commercials (Atkin, 1975a, 1975b, 1975c, 1975d; Rubin, 1972; Stoneman & Brody, 1983; Ward, 1972; Ward, Wackman, & Wartella, 1978), television programs (Leifer et al., 1971), and toy scenes (Dirks & Neisser, 1977).

Stoneman and Brody (1983) presented auditory-only, visual-only, or combined auditory-visual stories in which product advertisements were interspersed. Kindergarten children recognized more advertised products than preschool children. Second-grade children recognized more advertised products than kindergarten or preschool children. Hoffman and Dick (1976) showed several hundred pictures to three-year-old children, seven-year-old children, and adult college students. The seven-year-old children accurately recognized more pictures than the three-year-old children. The adults recognized more pictures than the seven-year-old children.

It appears that the younger children's processing occurs more at the perceptual level than the semantic level. Also, the ability to process auditory information seems to develop earlier than the ability to process visual information (Carterette & Jones, 1967; Stevenson & Siegel, 1969). With increasing experience and maturity, children appear to learn to process information at a deeper (e.g., Craik & Lockhart, 1972; Craik & Tulving, 1975), more semantic level and therefore improve their retention of information. This idea is supported by several studies (e.g., Ackerman, 1981; Hoffner, Cantor, & Thorson, 1989; Owings & Baumeister, 1979) which found that, when presented information using multimedia, younger children encoded more perceptual aspects of stimuli than older children. Older children encoded more semantic information than younger children. Rankin and Culhane (1970) obtained a similar effect when they compared the comprehension performance of sixth-graders and college students.

Older children and adults are more likely to be able to process the meaning of multimedia information rather than its appearance. Older children and adult learners should benefit from educational multimedia more than younger learners.

Characteristics of the Learning Task

The tasks that the learner performs with the learning materials can affect performance. Characteristics of the learning task include attending to the information, rehearsing it, and actively elaborating it. Educational multimedia user interface design principles for the learning task follow.

Use Multimedia to Focus the Learner's Attention. A small number of studies provide limited support for this design principle. Multimedia can help direct the learner's attention to relevant information and improve learning. For example, one study (Baxter, Quarles, & Kosak, 1978) asked adults in a shopping mall to "look over" a newspaper page that included a story with or without a large photograph. When asked questions about their recall of the newspaper story, the participants remembered more information when they saw the story with the photograph than when they saw the story without the photograph. It appears that the photograph got the participants' attention and caused them to read the accompanying story. Other researchers successfully used drawings (e.g., Paradowski, 1967; Tennyson, 1978), motion (Baek & Layne, 1988; Park & Hopkins, 1993), small "chunks" of textual and graphical information (Rieber, 1990b), and adjunct questions (e.g., McConkie, Rayner, & Wilson, 1973; Watts & Anderson, 1971) to focus the learner's attention.

However, getting a learner to pay attention to information does not necessarily mean that the learner will learn the information. For example, learners who are new to a field of knowledge may simply view a supplementary animation without trying to understand the information it shows (e.g., Reed, 1985). Also, irrelevant media, such as unrelated pictures (e.g., Levie & Lentz, 1982) or motion (Park & Hopkins, 1993) may distract learners and actually decrease learning performance.

Encourage Learners to Actively Process the Information. A variety of multimedia studies were performed in this area, so there is strong empirical support for this design principle. Learning appears to improve when the learning task encourages the learner to actively process the information (e.g., Bobrow & Bower, 1969; Bower & Winzenz, 1970; Jacoby, 1978; Slamecka & Graf, 1978). For example, one study (Dean & Kulhavy, 1981) asked students to learn the features of a fictitious country. One group of students studied a map on which the features were labeled. Another group copied the features and labels onto a blank map. The students who were forced to actively process the spatial information by copying the map performed better on a free recall test of the map information.

Reading text may also cause the learner to more actively process the information than simply hearing verbal narration (e.g., Aldrich & Parkin, 1988; Baggett & Ehrenfeucht, 1983; Palmiter & Elkerton, 1991; Pezdek et al., 1984) or watching a silent movie (Salomon, 1984). Similarly, materials that force learners to figure out confusing information may cause them to more actively process the information, which thereby improves learning performance (e.g., Auble & Franks, 1978; Bock, 1978; Hunt & Elliot, 1980; Kolers, 1979; Walker et al., 1983; Sherman, 1976).

Simple repetition of the information does not encourage learners to actively process the information and does not necessarily improve learning. For example, before changing the frequency of its radio broadcast, the BBC advertised the new frequency via radio, television, newspaper, and direct mailings. Listeners received around 1000 exposures to the information about the new frequency. However, only 17% of the listeners learned the new frequency (Bekerian & Baddeley, 1980). To encourage listeners to actively process information, a different study (Thomson & Barnett, 1981) arranged for participants to hear 16 fake radio commercials. In one condition the listeners heard the product name at the beginning (e.g., "Buy Brighto!") and end of the commercial (e.g., "Buy Brighto!"). In another condition, listeners heard the product name at the beginning of the commercial (e.g., "Buy Brighto!"), but the product name was left unpronounced at the end of the commercial (e.g., "Buy!"). The final condition was the same as the previous condition, except listeners wrote down the name of the product that was left unpronounced at the end of the commercial. Fifteen minutes later, an unexpected test showed that recall accuracy improved across the groups from 16% to 29% to 46%. Extra processing appeared to improve learning.

In addition, the type of active processing is important. For example, Craik and Tulving (1975) found that processing the structural characteristics of each word in a list (e.g., "Is the word in capital letters?") was not as effective as processing the meaning of the word (e.g., "Would the word fit the sentence: ‘He met a _____ in the street’?"). Other researchers (e.g., Craik & Watkins, 1973; Hyde & Jenkins, 1969; Parkin, 1984; Rundus, 1977) obtained similar results.

Processing tasks that encourage learners to integrate the information they are studying seem to improve learning. Several studies (e.g., Anderson & Biddle, 1975; Frase, 1975; Reder, 1979; Rothkopf, 1966) found that periodically asking learners to answer questions about the information they had just reviewed led to improvements in learning performance. Tasks that do not encourage learners to integrate the information may actually worsen learning performance (e.g., Stein & Bransford, 1979; Stein, Morris, & Bransford, 1978).

It is possible that tasks that encourage the learner to actively process and integrate the information may focus their attention on the information and cause them to process the information more elaboratively. This appears to be especially true when the processing focuses on the meaning of the information rather than its appearance, and when the processing integrates the information being studied. Information that is processed in this way is easier to connect with long-term memories, may improve retrieval, and may therefore result in improved learning (e.g., Anderson & Reder, 1979; Burns, 1992; Hirshman & Bjork, 1988; Reder, 1979).

Characteristics of the Test of Learning

The characteristics of the test of learning can have a significant effect on learning performance (Najjar, 1995b). Tests can measure verbal, pictorial, semantic, or even procedural aspects of the learning materials. The types of tests can include recall, recognition, and problem-solving. A principle for designing a test of learning follows.

Match the Type of Information Tested to the Type of Information Learned. This design principle is moderately supported by the small number of studies performed on this topic. Scores on learning tests are higher when the kind of information (e.g., verbal, pictorial) that the learner needs to retrieve to complete the test matches the kind of information that the learner studied (e.g., Dwyer, 1967a, 1978; Morris, Bransford, & Franks, 1977; Samuels, 1967; Watkins, 1974). For example, on a verbal learning test, children in a verbal condition performed better than children in a verbal-pictorial condition. On a pictorial test, children in a verbal-pictorial condition performed better than children in a verbal condition (Beagles-Roos & Gat, 1983).

Studies (e.g., Frost, 1972; Leonard & Whitten, 1983; Stein, 1978) also show that learners perform better when they are given the same kind of test (e.g., recognition, recall) that they were told to expect when they began studying the learning material. Students who expected, and got, a recognition test performed better than students who expected a recognition test, but got a recall test.

Learning performance improves when the way the learner stores the information (e.g., verbal, pictorial, semantic, for recall or recognition) is similar to the way the information is tested (e.g., Morris et al., 1977; Tulving & Thomson, 1973). To improve student learning performance, the test should match the kind of information that was learned, and the given test should match the expected test.

CONCLUSIONS

These empirically-validated principles will help educational multimedia user interface designers to build applications that improve learning. The most strongly-supported principles suggest that designers should (a) use closely related verbal and pictorial information together and (b) build in tasks that encourage learners to elaboratively process the information. To make their educational multimedia applications even more effective, designers should also apply more general user interface principles and guidelines (e.g., Mayhew, 1992; Smith & Mosier, 1986).

The design principles described in this paper are new, and user interface designers should use them with some caution. The number of studies supporting some of the principles (such as "Use educational multimedia with naive learners and learners with lower aptitude") is limited and some studies used narrow, somewhat artificial learning situations. Extending the results of these studies to other situations involves some risk. To more accurately evaluate the benefit of these design principles, we need to perform studies that use actual computer-based multimedia tutorials in realistic learning situations. Good candidates for these evaluations include the currently-popular, compact disk-based "edutainment" applications.

We also need to understand not just when multimedia is effective, but why it is effective (e.g., Najjar, 1997). As more is learned about human perception, cognition, and learning, the existing educational multimedia design principles can be refined and new, more effective principles can be developed.

ACKNOWLEDGMENTS

The author thanks Laurie Najjar for editorial assistance and Chris Thompson of Georgia Tech Research Institute’s Multimedia in Manufacturing Education laboratory for the use of support resources.

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Lawrence J. Najjar is a graduate research assistant at the Georgia Institute of Technology, where he expects to receive his Ph.D. in engineering psychology in 1998. He received an M.S. in engineering psychology from Georgia Tech in 1983.

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