Abstract
Early research with multimedia environments questioned whether these environments are effective in supporting learning. More recently it has been acknowledged that this question should really be about the specific conditions and reasons why multimedia is effective. However, while the argument has become more sophisticated, the techniques for evaluating learning with multimedia environments have not always followed suit. The dominant approach at present involves factorial designs with novices as participants, learning something for a short period of time with outcomes tested by an immediate pen and paper post-test. In this chapter, the positive aspects of this approach are reviewed, but it will be argued that such an approach limits the questions that can be answered. Four important such questions about learning with multimedia are proposed and then the chapter describes a range of methodologies that can be used to answer them.
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References
Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16(3), 183–198.
Ainsworth, S. E., Bibby, P., & Wood, D. (2002). Examining the effects of different multiple representational systems in learning primary mathematics. Journal of the Learning Sciences, 11(1), 25–61.
Ainsworth, S. E., & Loizou, A. T. (2003). The effects of self-explaining when learning with text or diagrams. Cognitive Science, 27(4), 669–681.
Buckley, B. C. (2000). Interactive multimedia and model-based learning in biology. International Journal of Science Education, 22(9), 895–935.
Chandler, P., & Sweller, J. (1992). The split-attention effect as a factor in the design of instruction. British Journal of Educational Psychology, 62, 233–246.
Card, S., Moran, T., & Newell, A. (1983). The psychology of human-computer interaction. Hillsdale, NJ: Erlbaum.
Cheng, P. C. H. (2002). Electrifying diagrams for learning: principles for complex representational systems. Cognitive Science, 26(6), 685–736.
Daily, L. Z., Lovett, M. C., & Reder, L. M. (2001). Modelling individual differences in working memory performance: a source activation account. Cognitive Science, 25(3), 315–353.
de Jong, T., Ainsworth, S. E., Dobson, M., van der Hulst, A., Levonen, J., Reimann, P., et al. (1998). Acquiring knowledge in science and math: The use of multiple representations in technology based learning environments. In M. W. Van Someren, P. Reimann, H. P. A. Boshuizen, & T. de Jong (Eds.), Learning with multiple representations (pp. 9–40). Amsterdam: Elsevier Science.
diSessa, A. A. (2004). Metarepresentation: Native competence and targets for instruction. Cognition and Instruction, 22(3), 293–331.
Goldman, S. R. (2003). Learning in complex domains: When and why do multiple representations help? Learning and Instruction, 13(2), 239–244.
Guercin, F. (2001). Can children process complex information from different media? In J.-F. Rouet, J. L. Levonen, & A. Biardeau (Eds.), Multimedia learning (pp. 59–64). Amsterdam: Pergamon.
Howe, C., Tolmie, A., Anderson, A., & Mackenzie, M. (1992). Conceptual knowledge in physics: The role of group interaction in computer-supported teaching. Learning and Instruction, 2, 161–183.
Kalyuga, S., Chandler, P., & Sweller, J. (1999). Managing split-attention and redundancy in multimedia instruction. Applied Cognitive Psychology, 13(4), 351–371.
Klein, P. D. (2003). Rethinking the multiplicity of cognitive resources and curricular representations: alternatives to ‘learning styles’ and ‘multiple intelligences’. Journal of Curriculum Studies, 35(1), 45–81.
Kozma, R., Chin, E., Russell, J., & Marx, N. (2000). The roles of representations and tools in the chemistry laboratory and their implications for chemistry learning. Journal of the Learning Sciences, 9(2), 105–143.
Lane, P. C. R., Cheng, P. C. -H., & Gobet, F. (2000). CHREST+: A simulation of how humans learn to solve problems using diagrams. AISB Quarterly, 103, 24–30.
Lewalter, D. (2003). Cognitive strategies for learning from static and dynamic visuals. Learning and Instruction, 13(2), 177–189.
Lowe, R. K. (2003). Animation and learning: selective processing of information in dynamic graphics. Learning and Instruction, 13(2), 157–176.
Mayer, R. E. (2001). Multimedia Learning. Cambridge: Cambridge University Press.
Mayer, R. E. (2003). The promise of multimedia learning: Using the same instructional design methods across different media. Learning and Instruction, 13(2), 125–139.
Mayer, R. E., & Gallini, J. K. (1990). When is an illustration worth ten thousand words? Journal of Educational Psychology, 82(4), 715–726.
Mayer, R. E., & Moreno, R. (1998). Split-attention effect in multimedia learning: Evidence for dual processing systems in working memory. Journal of Educational Psychology, 90(2), 312–320.
Mayer, R. E., & Sims, V. K. (1994). For whom is a picture worth 1000 Words – extensions of a dual-coding theory of multimedia learning. Journal of Educational Psychology, 86(3), 389–401.
Moreno, R., & Mayer, R. E. (2000). A coherence effect in multimedia learning: The case for minimizing irrelevant sounds in the design of multimedia instructional messages. Journal of Educational Psychology, 92(1), 117–125.
Najjar, L. (1998). Principles of educational multi-media user interface design. Human Factors, 40(2), 311–323.
Pane , J. F., Corbett , A. T., & John , B. E. (1996). Assessing dynamics in computer-based instruction., Proceedings of ACM CHI'96 Conference on Human Factors in Computing Systems. Vancouver.
Price , S. J. (2002). Diagram representation: The cognitive basis for understanding animation in education (Technical Report CSRP 553): School of Computing and Cognitive Sciences, University of Sussex.
Reimann, P. (2003). Multimedia learning: beyond modality. Learning and Instruction, 13(2), 245–252.
Rieber, L. P. (1990). Animation in Computer-Based Instruction. Educational Technology Research and Development, 38(1), 77–86.
Roberts, M. J., Gilmore, D. J., & Wood, D. J. (1997). Individual differences and strategy selection in reasoning. British Journal of Psychology, 88, 473–492.
Robson, C.(2002) Real world research. Oxford: Blackwell Publishing.
Romero , P., du Boulay , B., Lutz , R., & Cox , R. (2003). The effects of graphical and textual visualisations in multi-representational debugging environments., Proceedings of 2003 IEEE Symposia on Human Centric Computing Languages and Environments.
Roth, W.-M., & Bowen, G. M. (2001). Professionals read graphs: A semiotic analysis. Journal for Research in Mathematics Education, 32, 159–194.
Rouet, J.-F. & Passerault, J.-M. (1999). Analyzing learner-hypermedia interaction: An overview of online methods. Instructional Science, 27(3/4), 201–219.
Schnotz, W. (2001). Sign systems, technologies and the acquisition of knowledge. In J.-F. Rouet, J. J. Levonen & A. Biardeau (Eds.), Multimedia learning: Cognitive and instructional Issues (pp. 9–30). Amsterdam: Pergamon.
Schoenfeld, A. H., Smith, J. P., & Arcavi, A. (1993). Learning: The microgenetic analysis of one student's evolving understanding of a complex subject matter domain. In R. Glaser (Ed.), Advances in instructional psychology (Vol. volume 4). Hillsdale, NJ: LEA.
Seufert, T. (2003). Supporting coherence formation in learning from multiple representations. Learning and Instruction, 13(2), 227–237.
Snow, R. E., & Yalow, E. (1982). Education and intelligence. In R. J. Stenberg (Ed.), A handbook of human intelligence (pp. 493–585). Cambridge: Cambridge University Press.
Siegler, R. S. (1995). How does change occur: A microgenetic study of number conservation. Cognitive Psychology, 25, 225–273.
Stern, E., Aprea, C., & Ebner, H. G. (2003). Improving cross-content transfer in text processing by means of active graphical representation. Learning and Instruction, 13(2), 191–203.
Sweller, J., van Merrienboer, J. J. G., & Paas, F. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296...
Tabachneck-Schijf, H. J. M., Leonardo, A. M., & Simon, H. A. (1997). CaMeRa: A computational model of multiple representations. Cognitive Science, 21(3), 305–350.
Tabbers, H. K., Martens, R. L., & Van Merriënboer, J. J. G. (2001). The modality effect in multimedia instructions. In J. D. Moore & K. Stenning (Eds.), Proceedings of the 23rd annual conference of the Cognitive Science Society (pp. 1024–1029). Mahwah, NJ: Lawrence Erlbaum Associates.
Tsui, C. -Y. & Treagust, D. F. (2003). Genetics reasoning with multiple external representations. Research in Science Education, 33, 111–135.
Van Someren, M. W., & Tabbers, H. (1998). The role of prior knowledge qualitative knowledge in inductive learning. In M. W. Van Someren, P. Reimann, H. P. A. Boshuizen, & T. de Jong (Eds.), Learning with multiple representations (pp. 102–119). Amsterdam: Pergamon.
Waldrip, B. G., & Prain, V. (2004, April). Enhancing learning through using multi-modal representations of concepts. A paper presented at the Annual Meeting of the American Educational Research Association, San Diego.
Winn, B. (1987). Charts, graphs and diagrams in educational materials. In D. M. Willows & H. A. Houghton (Eds.), The psychology of illustration: I. Basic research (pp. 152–198). New York: Springer.
Yerushalmy, M. (1991). Student perceptions of aspects of algebraic function using multiple representation software. Journal of Computer Assisted Learning, 7, 42–57.
Zahn, C., Barquero, B., &, S. (2004). Learning with hyperlinked videos – design criteria and efficient strategies for using audiovisual hypermedia. Learning and Instruction, 14(3), 275–291.
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Ainsworth, S. (2008). How Should We Evaluate Multimedia Learning Environments?. In: Rouet, JF., Lowe, R., Schnotz, W. (eds) Understanding Multimedia Documents. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-73337-1_13
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