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206 Kalyuga Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. Chapter X Expert-Novice Differences and Adaptive Multimedia Slava Kalyuga, University of New South Wales, Australia Abstract This chapter provides an overview of theoretical frameworks and empirical evidence for the design of adaptive multimedia that is tailored to individual levels of user expertise to optimize cognitive resources available for learning. Recent studies indicate that multimedia design principles that benefit low-knowledge users may disadvantage more experienced ones due to increase in cognitive load required for integration of presented information with available knowledge base. The major implication for multimedia design is the need to tailor instructional formats to individual levels of expertise. The suggested adaptive procedure is based on empiricallyestablished interactions between levels of user proficiency and formats of multimedia presentations (the expertise reversal effect), and on real-time monitoring of users expertise using rapid cognitive diagnostic methods.

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Expert-Novice Differences and Adaptive Multimedia 207 Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. Introduction When the same digital multimedia materials are presented to novices and experts in a domain, these two categories of users would perceive the presentation rather differently. Imagine a sufficiently complex electrical wiring diagram displayed on a computer screen. Experienced electrical engineers, even if they have not seen this particular diagram before, may immediately recognize familiar functional parts and see the diagram as a representation of a whole device or system. They would be able to rapidly figure out how the circuit operates and what it is used for. On the other hand, first-year electrical trade apprentices may at best see only a set of familiar elements (resistors, switches, etc.) without understanding why all these elements are connected in this particular way. (Let us leave out laypersons that would see a collection of lines, circles, rectangles, and other strange symbols). Obviously, the apprentices need detailed explanations of the circuit operation to understand the diagram. Assume the above categories of users are provided with well-developed comprehensive multimedia instructions (for example, constructed according to multimedia design principles of Mayer, 2001, 2005). The instructions may have the diagram animated and include appropriately-placed (synchronized with animations) narrated auditory explanations. Such multimedia materials would certainly help the novice trainees to understand the operation of the circuit. However, when the same instructions are presented to the experienced engineers, they may find them rather annoying, especially if it is not possible to avoid the instructional details. If post-instruction test tasks are used to assess the understanding of the operation of the circuit, we could find that experts who were presented with the diagram-only format without any explanations outperform the experts who studied the multimedia instructional message. In fact, such relative declines in experts learning were observed on many occasions (see the following section for some references). The effect was related to changes in domain-specific knowledge base that people acquire as they become more experienced in the domain, and to the role this knowledge plays in guiding their cognitive performance. According to a large number of studies in cognitive psychology conducted over many decades, our knowledge base is the most important factor influencing our perception of incoming information. Some recent evidence of early vision that is independent of knowledge structures (e.g., see Pylyshyn, 1999, for an overview) would not change the general significance of the knowledge effect, especially during complex cognitive activities. According to another impressive set of cognitive studies initiated by investigations of the nature of chess expertise (de Groot, 1966), the knowledge base is a single most important factor determining expert-novice differences in cognitive performance (see Chi, Glaser, & Farr, 1988, for an overview). Finally, studies of information processing limitations imposed by the structure of human cognitive architecture (originated by Miller, 1956), and the ways we deal with these limitations by reorganizing our knowledge base and using multiple (e.g., visual and auditory) modalities, provide another theoretical framework and empirical evidence to complete the picture of expert-novice differences in perceiving multimedia messages. This chapter starts with a brief overview of major theoretical issues and empirical evidence that are essential for understanding multimedia design implications of expert-

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Perceptual Multimedia: A Cognitive Style Perspective 205 Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. Witkin, H. A., Moore, C. A., Goodenough, D. R., & Cox., P. W. (1977). Field-dependent and field independent cognitive styles and their educational implications. Review of Educational Research, 47, 1-64. Zwyno, M. S. (2003, November). Student learning styles, Web use patterns, and attitudes towards hypermedia-enhanced instruction. Proceedings of the 33rd ASEE/IEEE Frontiers in Education Conference (pp. 1-6).

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Perceptual Multimedia: A Cognitive Style Perspective 203 Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. However, what our results do highlight, independent of the cognitive style taxonomy being used, is that multimedia content does have a significant influence on the user experience, as measured by the QoP metric. This would imply that in order to deliver an enhanced multimedia infotainment experience, multimedia content providers should focus on relatively static multimedia video and take into consideration the appropriateness of the subject matter in order to aid in the uptake and proliferation of distributed multimedia. References Apteker, R. T., Fisher, J. A., Kisimov, V. S., & Neishlos, H. (1995). Video acceptability and frame rate. IEEE Multimedia, 2(3), 32-40. Chen, S. Y. (2002). A cognitive model for non-linear learning in hypermedia programmes. British Journal of Educational Technology, 33(4), 453-464. Chen, S. Y., & Angelides, M. C. (2003). Customisation of Internet multimedia information systems design through user modelling. In S. Nansi (Ed.), Architectural issues of Web-enabled electronic business (pp. 241-255). Hershey, PA: Idea Group Publishing. Chen, S. Y., & Ford, N. J. (1998). Modelling user navigation behaviours in a hypermediabased learning system: An individual differences approach. International Journal of Knowledge Organization, 25(3), 67-78. Chen, S. Y., & Macredie, R. D. (2002). Cognitive styles and hypermedia navigation: Development of a learning model. Journal of the American Society for Information Science and Technology, 53(1), 3-15. Chuang, Y. R. (1999). Teaching in a multimedia computer environment: A study of effects of learning style, gender, and math achievement. Retrieved December 21, 2001, from http://imej.wfu.edu./articles/1999/1/10/index/asp Demetriadis, S., Triantafilou, E., & Pombortis, A. (2003, June 30-July 2). A phenomenographic study of students attitudes toward the use of multiple media for learning. ACM SIGCSE Bulletin, Proceedings of the 8th Annual Conference on Innovation and Technology in Computer Science Education, Thessaloniki, Greece (pp. 183-187). Ford, N., & Chen, S. Y. (2001). Matching/mismatching revisited: An empirical study of learning and teaching styles. British Journal of Educational Technology, 32(1), 5-22. Fukuda, K., Wakamiya, N., Murata, M., & Miyahara, H. (1997). QoS mapping between user s preference and bandwidth control for video transport. Proceedings of the 5th International Workshop on QoS (IWQoS) (pp. 291-301). Fullerton, K. (2000). The interactive effects of field dependence-independence and Internet document manipulation style on student achievement from computerbased instruction. Doctoral dissertation, University of Pittsburgh.

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204 Ghinea & Chen Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. Ghinea, G., & Thomas, J. P. (2005). Quality of perception: User quality of service in multimedia presentations. IEEE Transactions on Multimedia, 7(4), 786-789. Jonassen, D. H., & Grabowski, B. (1993). Individual differences and instruction. New York: Allen & Bacon. Laing, M. (2001). Teaching learning and learning teaching: An introduction to learning styles. New Frontiers in Education, 31(4), 463-475. Neo, T., & Neo, M. (2004). Classroom innovation: Engaging students in interactive multimedia learning. Campus-Wide Information Systems, 21(3), 118-124. Pask, G. (1976). Styles and strategies of learning. British Journal of Educational Psychology, 46, 128-148. Pask, G. (1979). Final report of S.S.R.C. Research Programme HR 2708. Richmond (Surrey): System Research Ltd. Paterson, P. (1996). The influence of learning strategy in a computer mediated learning environment. Paper presented at ALT-Conference 96. Retrieved November 19, 1997, from http://www.warwick.ac.uk/alt-/alt-96/papers.html Riding, R. J. (1991). Cognitive styles analysis. Birmingham: Learning and Training Technology. Riding, R. J., & Douglas, G. (1993). The effect of cognitive style and mode of presentation on learning performance. British Journal of Educational Psychology, 63, 297-307. Riding, R. J., & Grimley, M. (1999). Cognitive style and learning from multimedia materials in 11 year old children. British Journal of Educational Technology, 30(2), 43-56. Riding, R. J., & Rayner, S. G. (1998). Cognitive styles and learning strategies. London: David Fulton Publisher. Riding, R. J., & Watts, M. (1997). The effect of cognitive style on the preferred format of instructional material. Educational Psychology, 17(1 & 2), 179-183. Stash, N., Cristea, A., & De Bra, P. (2004, May). Authoring of learning styles in adaptive hypermedia: Problems and solutions. Proceedings of the Thirteenth International World Wide Web Conference, New York, (pp 114-123). Steinmetz, R. (1996). Human perception of jitter and media synchronisation. IEEE Journal on Selected Areas in Communications, 14(1), 61-72. Watson, A., & Sasse, M. A. (1996). Evaluating audio and video quality in low cost multimedia conferencing systems. Interacting with Computers, 8(3), 255-275. Wijesekera, D., & Srivastava, J. (1996). Quality of service (QoS) metrics for continuous media. Multimedia Tools and Applications, 3(1), 127-136. Wijesekera, D., Srivastava, J., Nerode, A., & Foresti, M. (1999). Experimental evaluation of loss perception in continuous media. Multimedia Systems, 7(6), 486-499. Wilson, G. M., & Sasse, M. A. (2000, December). Investigating the impact of audio degradations on users: Subjective vs. objective assessment methods. Proceedings of OZCHI2000, Sydney (pp. 135-142).

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202 Ghinea & Chen Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. prefer clips of medium dynamism, where they do not feel overwhelmed, but neither are they bored by the presentation of the subject matter concerned. Summary This chapter has presented the results of two studies that looked at the impact of cognitive styles and multimedia content on users subjective Quality of Perception. The latter is a term which encompasses not only a user s enjoyment, but also his/her level of understanding of visualised multimedia content. Each of the studies used a different dimension for categorising participants cognitive style thus, the first study used the Field Dependent/ Independent categorisation, whilst the second employed the Verbaliser/ Visualiser dimension. Our results reveal that multimedia video clip dynamism is an important factor impacting, irrespective of the particular dimension of cognitive style being employed, upon participants QoP-IA levels. A similar conclusion as regards QoP-LOE can only be made, however, if the Field Dependent/Independent dimension is used. If one uses the Verbaliser/Visualiser dimension to classify cognitive style, clip dynamism has no significant effects on Biomodals, which, displaying characteristics of both Verbalisers and Visualisers, have adaptable preferences of accessing information and enjoy receiving information from multiple channels. Cognitive Styles verbalizer biomodal imager Mean QoP-LOE (Max=6) 2.6 2.4 2.2 2.0 1.8 1.6 Dynamism weak medium strong Figure 5: Cognitive styles and clip dynamism impact on QoP-LOE

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200 Ghinea & Chen Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. all. However, dynamism does not seem to be a factor influencing multimedia clip enjoyment of intermediate users. One possible interpretation is that individuals possessing an Intermediate cognitive style employ a more versatile repertoire of informationseeking strategies. Versatile users, who have acquired the skill to move back and forth between different information-seeking strategies, are more capable of adapting themselves to suit the subject content presented by the multimedia video clips. This finding is consistent with the views of previous work, namely that a versatile strategy can be better equipped for multimedia learning technology (Chen & Ford, 1998; Paterson, 1996). Analysis of the results obtained from the experiments shows that the degree of clip dynamism significantly impacts upon the QoP-IA component of QoP, irrespective of the user s cognitive style. The analysis has highlighted, moreover, the fact that the highest QoP-IA scores are obtained for clips which have a low degree of dynamism. Conversely, multimedia clips which have a high degree of dynamism have a negative impact on the user assimilation of the informational content being conveyed by the respective clips (Figure 4). Thus, clips which have relatively small inter-frame variability will facilitate higher QoP-IA scores: An object which might appear for only 0.5 seconds in a highly dynamic clip is less easily remembered than is the case when it appears for one second in a clip which is less dynamic. As far as the QoP-LOE component is concerned, analysis of our results reveals that while dynamism is a significant factor in the case of verbalisers and visualisers, this is not true of biomodals (Figure 5). As suggested by previous research (Riding & Rayner, 1998), biomodals can tailor learning strategies to the specific learning environments so the features of learning environments have no significant effects on their enjoyment. For verbalisers and visualisers, however, it was found that clips of medium dynamism had the highest levels of QoP-LOE, which suggests that such users do not find enjoyable clips which are static (or, conversely, highly dynamic). While the user may feel somewhat overwhelmed by a fast-paced clip, (s) he might possibly feel uninterested by a static clip with almost repetitive frame displays; it should come as no surprise, then, that such users 40 42 44 46 48 50 52 54 56 58 Weak Medium Strong Dynamism Mean QoP-IA Score (%) Field Dependent Intermediate Field Independent Figure 2. Impact of dynamism and cognitive styles on participants QoP-IA

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Perceptual Multimedia: A Cognitive Style Perspective 201 Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. 0 0.5 1 1.5 2 2.5 3 Field Dependent Intermediate Field Independent Cognitive Styles Mean QoP-LOE (Max = 6) Weak Dynamism Medium Dynamism Strong Dynamism Figure 3. Impact of dynamism and cognitive styles on participants QoP-LOE Cognitive Styles verbalizer biomodal imager Mean QoP-IA Score (%) 58 56 54 52 50 48 46 44 Dynamism weak medium strong Figure 4. Cognitive styles and clip dynamism impact on QoP-IA

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Perceptual Multimedia: A Cognitive Style Perspective 199 Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. Verbaliser Biomodal Visualiser Score 62.84% 62.98% 65.52% Documentary Snooker Enjoyment 4.17 3.94 3.91 Documentary Pop Music Documentary Table 6. Favourite clips Enjoyment will also influence users performance, especially for verbalisers, who perform better and enjoy more the Documentary clip and performed worse and enjoyed less the Rugby clip. It is consistent with the results of previous research (Chen, 2002), which highlight that positive user perceptions of the learning environment can enhance their performance; conversely, negative attitudes will tend to hinder learning performance. Degree of Dynamism Multimedia clip dynamism was found to significantly impact upon participants QoP-IA levels in our study (Figure 2). The correct one is that the level of significance was found to be p=.000 for field-dependent users and p=.001 for intermediate and field-independent users. Clip dynamism is given by Table 3, where the terms strong, medium, and weak were coded with the values of 3, 2, and 1, respectively. All users performed worst in the clips with strong dynamism. In particular, field- dependent users do not perform as well as field-independent and intermediate users. As suggested by previous works (Chen, 2002; Chen & Macredie, 2002), field-dependent users performance was hindered in situations where they need to extract cues by themselves. Thus, in multimedia clips with strong dynamism that provided too many cues, field-dependent users might find it difficult to select relevant cues. The dynamism of the visualised clips also influenced the level of enjoyment experienced by participants (p=.000). If a per-cognitive style analysis is pursued, we find that the level of enjoyment is influenced by the dynamism of the multimedia clip for both fieldindependent (p=.004) and field-dependent (p=.000) users. As shown in Figure 3, both field-independent and field-dependent users experienced higher levels of enjoyment from the clips with medium dynamism, while strongly dynamic clips were liked least of Verbaliser Biomodal Visualiser Score 35.59% 35.74% 34.49% Rugby Enjoyment 2.59 2.78 2.81 Rugby Table 7. Least favourite clip

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198 Ghinea & Chen Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. video clip was the one which field-independent users enjoyed most. It is probable that the wealth of detail present in this clip (information was conveyed through all three channels, video, audio, and text) is what makes the clip appealing to this particular type of users, who concentrated primarily on procedural details when processing information in a learning context (Pask, 1976, 1979). This is in contrast to the Most Enjoyed clip (i.e. Documentary) for the other two categories of users, in which information was only conveyed through the video and audio streams. Experiment 2 Our results indicate that clip categories, as given by their specific multimedia content matter, significantly influence participants components of QoP-IA. This shows that the information assimilation scores are significantly influenced by the content being visualised; moreover, this observation is valid irrespective of the particular cognitive style of the participant. However, closer analysis reveals that different cognitive style groups have different favourite clips. Pop Music, which displays information using multiple channels, including video, audio, and text, is the favourite clip, from an information assimilation point of view, for biomodals who combine the characteristics of both verbalisers and visualisers and are particularly adept at receiving information from either textual descriptions or graphic presentations. However, we did obtain some significant results that contradict those of previous research (Laing, 2001; Riding & Watts, 1997) (Tables 6 and 7). Although the Documentary clip does not display any text description, it is the clip in which, on average, verbalisers obtain the highest QoP-IA (F=10.592, df=5,40, p=.000). On the other hand, visualisers perform better in the Snooker clip, which, though static, includes information conveyed through video, audio, and text (F=14.8451, df=6,36, p=.000). However, irrespective of cognitive style, we found that the Rugby clip was the one in which participants obtained the lowest QoP-IA scores (F=32.743, df=15,72, p=.000). Although this clip is similar in some respects to others studied by us (such as the Snooker clip, which also has an abundance of information being portrayed through video, audio, and textual means), its main distinguishing feature is its high dynamism; there is considerable temporal variability due to the high inter-frame differences specific to clips featuring action sports. We therefore assume that the reason why participants scored so lowly in terms of QoP-IA on this clip is precisely because of its high dynamism, a hypothesis that shall be further explored in the section titled Degree of Dynamism . Field Dependent Intermediate Field Independent Most Enjoyed Documentary Forecast 3.18 2.86 3.02 Least Enjoyed Rugby Band Rugby 1.39 1.93 1.61 Table 5. Cognitive styles and QoP-LOE of clip categories

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