Skip to main content Accessibility help
  • Get access
    Check if you have access via personal or institutional login
  • Cited by 54
  • Print publication year: 2005
  • Online publication date: June 2012

21 - Prior Knowledge Principle in Multimedia Learning



This chapter summarizes research and theory concerned with the effects of learner prior knowledge on multimedia learning principles. In many situations, design principles that help low-knowledge learners may not help or even hinder high-knowledge learners. The main theoretical issue associated with the prior knowledge principle concerns the integration in working memory of instructional information with information held in long-term memory. The major implication for instructional design is the need to tailor instructional formats and procedures to changing levels of expertise. Essential future research directions include identifying instructional procedures that are optimal for different levels of expertise and developing viable instruments of cognitive diagnosis of schematic knowledge structures suitable for real-time online evaluation of learner progress.

What Is the Prior Knowledge Principle?

Design principles for multimedia learning environments depend on the prior knowledge of the learner: design principles that help low-knowledge learners may not help or even hinder high-knowledge learners. Many multimedia design recommendations do not explicitly refer to learner knowledge levels, although most of them have only been tested in experiments with learners who had limited experience in the relevant domain. Could the same recommendation be applied to more experienced learners? Experienced or high-knowledge learners are considered learners who have substantial previously acquired knowledge in a specific domain and who are involved in learning relatively new, more advanced information in this domain. The evidence suggests that multimedia design recommendations for such learners should be different, sometimes contrary to recommendations for novice learners.

Carney, R. N., & Levin, J. R. (2002). Pictorial illustrations still improve students' learning from text. Educational Psychology Review, 14, 5–26
Chi, M. T. H., Feltovich, P., & Glaser, R. (1981). Categorisation and representation of physics problems by experts and novices. Cognitive Science, 5, 121–152
Chi, M. T. H., & Glaser, R. (1985). Problem solving ability. In Sternberg, R. (Ed.), Human abilities: An information processing approach, (pp. 227–250). San Francisco: Freeman
Chi, M. T. H., Glaser, R., & Farr, M. J. (Eds.). (1988). The nature of expertise. Hillsdale, NJ: Erlbaum
Cooper, G., Tindall-Ford, S., Chandler, P., & Sweller, J. (2001). Learning by imagining procedures and concepts. Journal of Experimental Psychology: Applied, 7, 68–82
Cronbach, L. J., & Snow, R. E. (1977). Aptitudes and instructional methods: A handbook for research on interaction. New York: Irvington Publishers
Ericsson, K. A., & Kintsch, W. (1995). Long-term working memory. Psychological Review, 102, 211–245
Ericsson, K. A., & Smith, J. (Eds.). (1991). Toward a general theory of expertise. Cambridge, UK: Cambridge University Press
Hegarty, M., Quilici, J., Narayanan, N. H., Holmquist, S., & Moreno, R. (1999). Multimedia instruction: Lessons from evaluation of a theory-based design. Journal of Educational Multimedia and Hypermedia, 8, 119–150
Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003). Expertise reversal effect. Educational Psychologist, 38, 23–31
Kalyuga, S., Chandler, P., & Sweller, J. (1998). Levels of expertise and instructional design. Human Factors, 40, 1–17
Kalyuga, S., Chandler, P., & Sweller, J. (2000). Incorporating learner experience into the design of multimedia instruction. Journal of Educational Psychology, 92, 126–136
Kalyuga, S., Chandler, P., & Sweller, J. (2001). Learner experience and efficiency of instructional guidance. Educational Psychology, 21, 5–23
Kalyuga, S., Chandler, P., Tuovinen, J., & Sweller, J. (2001). When problem solving is superior to studying worked examples. Journal of Educational Psychology, 93, 579–588
Kozma, R. B. (1991). Learning with media. Review of Educational Research, 61, 179–211
Levie, W., & Lentz, R. (1982). Effects of text illustrations: A review of research. Educational Communication and Technology Journal, 30, 195–232
Lohman, D. F. (1986). Predicting mathemathanic effects in the teaching of higher-order thinking skills. Educational Psychologist, 21, 191–208
Lowe, R. K. (1993). Constructing a mental representation from an abstract technical diagram. Learning and Instruction, 3, 157–179
Mayer, R. E. (1989). Models for understanding. Review of Educational Research, 59, 43–64
Mayer, R. E. (1993). Comprehension of graphics in texts: An overview. Learning and Instruction, 3, 239–245
Mayer, R. E. (1999). Research-based principles for the design of instructional messages. The case of multimedia explanations. Document Design, 1, 7–20
Mayer, R. E. (2001). Multimedia learning. New York: Cambridge University Press
Mayer, R., & Chandler, P. (2001). When learning is just a click away: Does simple user interaction foster deeper understanding of multimedia messages?Journal of Educational Psychology, 93, 390–397
Mayer, R., & Gallini, J. (1990). When is an illustration worth ten thousand words? Journal of Educational Psychology, 82, 715–726
Mayer, R. E., Steinhoff, K., Bower, G., & Mars, R. (1995). A generative theory of textbook design: Using annotated illustrations to foster meaningful learning of science text. Educational Technology Research and Development, 43, 31–43
Mayer, R., Stiehl, C., & Greeno, J. (1975). Acquisition of understanding and skill in relation to subjects' preparation and meaningfulness of instruction. Journal of Educational Psychology, 67, 331–350
Ollerenshaw, A., Aidman, E., & Kidd, G. (1997). Is an illustration always worth ten thousand words? Effects of prior knowledge, learning style, and multimedia illustrations on text comprehension. International Journal of Instructional Media, 24, 227–238
Pollock, E., Chandler, P., & Sweller, J. (2002). Assimilating complex information. Learning and Instruction, 12, 61–86
Reimann, P., & Chi, M. T. H. (1989). Human expertise. In Gilhooly, K. J. (Ed.), Human and machine problem solving (pp. 161–191. New York: Plenum Press
Renkl, A. (1997). Learning from worked-out examples: A study on individual differences. Cognitive Science, 21, 1–29
Renkl, A., & Atkinson, R. (2003). Structuring the transition from example study to problem solving in cognitive skills acquisition: A cognitive load perspective. Educational Psychologist, 38, 15–22
Renkl, A., Atkinson, R. K., & Maier, U. H. (2000). From studying examples to solving problems: Fading worked-out solution steps helps learning. In Gleitman, L. & Joshi, A. K. (Eds.), Proceeding of the 22nd Annual Conference of the Cognitive Science Society (pp. 393–398). Mahwah, NJ: Erlbaum
Renkl, A., Atkinson, R., Maier, U., & Staley, R. (2002). From example study to problem solving: Smooth transitions help learning. Journal of Experimental Education, 70, 293–315
Schnotz, W. (2002). Towards an integrated view of learning from text and visual displays. Educational Psychology Review, 14, 101–120
Schnotz, W., Picard, E., & Hron, A. (1993). How do successful and unsuccessful learners use text and graphics?Learning and Instruction, 3, 181–199
Snow, R., & Lohman, D. (1984). Toward a theory of cognitive aptitude for learning from instruction. Journal of Educational Psychology, 76, 347–376
Sternberg, R. J., & Frensch, P. A. (Eds.). (1991). Complex problem solving: Principles and mechanisms. Hillsdale, NJ: Erlbaum
Sweller, J. (2003). Evolution of human cognitive architecture. In Ross, B. (Ed.), The Psychology of Learning and Motivation, Vol. 43 (pp. 215–266). San Diego: Academic Press
Tuovinen, J., & Sweller, J. (1999). A comparison of cognitive load associated with discovery learning and worked examples. Journal of Educational Psychology, 91, 334–341
Merriënboer, J. J. G. (1990). Strategies for programming instruction in high school: Program completion vs. program generation. Journal of Educational Computing Research, 6, 265–287
Merriënboer, J. J. G., & Croock, M. B. M. (1992). Strategies for computer-based programming instruction: Program completion vs. program generation. Journal of Educational Computing Research, 8, 365–394
Merriënboer, J. J. G., Kirschner, P. A., & Kester, L. (2003). Taking the load off a learner's mind: Instructional design principles for complex learning. Educational Psychologist, 38, 5–13
Merriënboer, J. J. G., & Paas, F. G. W. C. (1989). Automation and schema acquisition in learning elementary computer programming: Implications for the design of practice. Computers in Human Behavior, 6, 273–289
Verdi, M. P., & Kulhavy, R. W. (2002). Learning with maps and texts: An overview. Educational Psychology Review, 14, 27–46