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  • Cited by 7
  • Print publication year: 2010
  • Online publication date: June 2012

4 - Individual Differences and Cognitive Load Theory

Summary

The previous chapters discussed sources of cognitive load that are a result of the difficulty of the materials, the design of instruction, and the amount of mental effort invested by learners to process the new information. As outlined in these chapters, the major cause of cognitive load effects is the limited capacity of working memory. In this chapter, we discuss how individual differences relate to the level of cognitive load that a particular learner experiences.

Individual differences in learner characteristics take many different forms, ranging from preferences for learning from different presentation formats (e.g., verbal, pictorial) or modalities (auditory, visual, haptic) and preferences for learning under different environmental conditions (e.g., lighting, noise level, or physical position) to cognitive styles (e.g., field dependency/independency), cognitive abilities (e.g., verbal, spatial ability), and intelligence (Carroll, 1993; Jonassen & Grabowski, 1993). The influence of individual differences on learning has been studied for several decades as aptitude-treatment interactions (ATIs; Cronbach & Snow, 1977; Leutner, 1992; Lohman, 1986; Mayer, Stiehl, & Greeno, 1975; Plass, Chun, Mayer, & Leutner, 1998; Shute, 1992; Snow, 1989, 1994; Snow & Lohman, 1984, 1989). Aptitude-treatment interactions occur when different instructional treatment conditions result in differential learning outcomes depending on student aptitudes, in other words, when the effect of a given treatment is moderated by a given aptitude. Different aptitudes may influence learning in specific instructional environments, and the impact of a particular aptitude on a particular condition may only be observed for a particular type of learning outcome.

References
Anderson, J. R., Corbett, A. T., Fincham, J. M., Hoffman, D., & Pelletier, R. (1992). General principles for an intelligent tutoring architecture. In Shute, V. & Regian, W. (Eds.), Cognitive approaches to automated instruction (pp. 81–106). Hillsdale, NJ: Erlbaum.
Atkinson, R. K., Derry, S. J., Renkl, A., & Wortham, D. W. (2000). Learning from examples: Instructional principles from the worked example research. Review of Educational Research, 70, 181–214.
Ayres, P. (2005). Impact of reducing intrinsic cognitive load on learning in a mathematical domain. Applied Cognitive Psychology, 20, 287–298.
Azevedo, R., & Cromley, J. G. (2004). Does training on self-regulated learning facilitate students' learning with hypermedia? Journal of Educational Psychology, 96(3), 523–535.
Azevedo, R., Cromley, J. G., & Seibert, D. (2004). Does adaptive scaffolding facilitate students' ability to regulate their learning with hypermedia? Contemporary Educational Psychology, 29(3), 344–370.
Baddeley, A. D. (1986). Working memory. New York: Oxford University Press.
Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.
Baumeister, R. F., Heatherton, T. F., & Tice, D. M. (1994). Losing control: How and why people fail at self-regulation. San Diego, CA: Academic Press.
Beishuizen, J. J., & Stoutjesdijk, E. T. (1999). Study strategies in a computer assisted study environment. Learning and Instruction, 9, 281–301.
Biemiller, A., Shany, M., Inglis, A., & Meichenbaum, D. (1998). Factors influencing children's acquisition and demonstration of self-regulation on academic tasks. In Schunk, D. H., & Zimmerman, B. J. (Eds.), Self-regulated learning: From teaching to self-reflective practice (pp. 203–224). New York: Guilford Publications.
Carroll, J. (1993). Human cognitive abilities. New York: Cambridge University Press.
Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8, 293–332.
Chang, Y. K., Plass, J. L., & Homer, B. D. (2008). Development and Validation of a Behavioral Measure of Metacognitive Processes (BMMP). Featured Research presentation at the annual convention of the Association for Educational Communication and Technology (AECT) in October, 2008 in Orlando, FL.
Chi, M. T. H., Siler, S., & Jeong, H. (2004). Can tutors monitor students' understanding accurately? Cognition and Instruction, 22, 363–387.
Cooper, G., & Sweller, J. (1987). Effects of schema acquisition and rule automation on mathematical problem-solving transfer. Journal of Educational Psychology, 79(4), 347–362.
Cronbach, L. J., & Snow, R. E. (1977). Aptitudes and instructional methods: A handbook for research on interaction. New York: Irvington Publishers.
Bruin, A. B. H., Schmidt, H. G., & Rikers, R. M. J. P. (2005). The role of basic science knowledge and clinical knowledge in diagnostic reasoning: A structural equation modeling approach [Report]. Academic Medicine, 80(8), 765–773.
Eom, W., & Reister, R. A. (2000). The effects of self-regulation and instructional control on performance and motivation in computer-based instruction. International Journal of Instructional Media, 27(3), 247–260.
Eteläpelto, A. (1993). Metacognition and the expertise of computer program comprehension. Scandinavian Journal of Educational Research, 37(3), 243–254.
Goldstein, M., Bretan, I., Sallnäs, E.-L., & Björk, H. (1999). Navigational abilities in audial voice-controlled dialogue structures. Behaviour & Information Technology, 18(2), 83–95.
Graesser, A. C., McNamara, D. S., & VanLehn, K. (2005). Scaffolding deep comprehension strategies through Point&Query, AutoTutor, and iSTART. Educational Psychologist, 40(4), 225–234.
Griffin, T. (2002). Supporting students with low self-regulation through problem-based learning techniques in online education. Unpublished doctoral dissertation, New York University.
Gyselinck, V., Cornoldi, C., Dubois, V., Beni, R., & Ehrlich, M.-F. (2002). Visuospatial memory and phonological loop in learning from multimedia. Applied Cognitive Psychology, 16, 665–685.
Hegarty, M., Shah, P., & Miyake, A. (2000). Constraints on using the dual-task methodology to specify the degree of central executive involvement in cognitive tasks. Memory & Cognition, 28(3), 376–385.
Hegarty, M., & Waller, D. A. (2005). Individual differences in spatial abilities. In Shah, P., & Miyake, A. (Eds.), The Cambridge handbook of visuospatial thinking (pp. 121–169). New York: Cambridge University Press.
Hmelo, C., Nagarajan, A., & Day, R. (2000). Effects of high and low prior knowledge on construction of a joint problem space. The Journal of Experimental Education, 69, 36–56.
Homer, B. D., Plass, J. L., & Blake, L. (2006). The effects of video on cognitive load and social presence in multimedia-learning. Manuscript submitted for publication.
Jonassen, D. H., & Grabowski, B. L. (1993). Handbook of individual differences, learning, and instruction. Hillsdale, NJ: Erlbaum.
Kalyuga, S. (2005). Prior knowledge principle in multimedia learning. In Mayer, R. (Ed.), Cambridge handbook of multimedia learning (pp. 325–337). New York: Cambridge University Press.
Kalyuga, S. (2006a). Instructing and testing advanced learners: A cognitive load approach. Hauppauge, NY: Nova Science Publishers.
Kalyuga, S. (2006b). Rapid cognitive assessment of learners' knowledge structures. Learning & Instruction, 16, 1–11.
Kalyuga, S. (2007). Expertise reversal effect and its implications for learner-tailored instruction. Educational Psychology Review, 19, 509–539.
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.
Kalyuga, S., Plass, J. L., Homer, B., Milne, C., & Jordan, T. (2007). Managing cognitive load in computer-based simulations for science education. Paper presented at the UNSW Cognitive Load Theory Conference, 24–26 March 2007 in Sydney, Australia.
Kalyuga, S., & Sweller, J. (2004). Measuring knowledge to optimize cognitive load factors during instruction. Journal of Educational Psychology, 96, 558–568.
Kalyuga, S., & Sweller, J. (2005). Rapid dynamic assessment of expertise to improve the efficiency of adaptive e-learning. Educational Technology Research and Development, 53, 83–93.
Kanfer, R., & Ackerman, P. L. (1989). Motivation and cognitive abilities: An integrative aptitude-treatment interaction approach to skill acquisition. Journal of Applied Psychology, 74(4), 657–690.
Lee, H., Plass, J. L., & Homer, B. D. (2006). Optimizing cognitive load for learning from computer-based science simulations. Journal of Educational Psychology, 89, 902–913.
Leopold, C., den Elzen-Rump, V., & Leutner, D. (2007). Self-regulated learning from science texts. In Prenzel, M. (Ed.), Studies on the educational quality of schools. The final report on the DFG Priority Programme (pp. 21–53). Münster, Germany: Waxmann.
Leutner, D. (1992). Adaptive Lehrsysteme. Instruktionspsychologische Grundlagen und experimentelle Analysen [Adaptive learning systems, instructional psychology foundations and experimental analyses]. Weinheim, Germany: PVU.
Leutner, D. (2004). Instructional-design principles for adaptivity in open learning environments. In Seel, N. M. & Dijkstra, S. (Eds.), Curriculum, plans, and processes in instructional design: International perspectives (pp. 289–308). Mahwah, NJ: Erlbaum.
Leutner, D., Leopold, C., & den Elzen-Rump, V. (2007). Self-regulated learning with a text-highlighting strategy: A training experiment. Zeitschrift für Psychologie/Journal of Psychology, 215(3), 174–182.
Leutner, D., & Plass, J. L. (1998). Measuring learning styles with questionnaires versus direct observation of preferential choice behavior in authentic learning situations: The Visualizer/Verbalizer Behavior Observation Scale (VV–BOS). Computers in Human Behavior, 14, 543–557.
Lohman, D. F. (1979). Spatial ability: A review and reanalysis of the correlational literature (Stanford University Technical Report No. 8). Stanford, CA: Aptitudes Research Project.
Lohman, D. F. (1986). Predicting mathemathanic effects in the teaching of higher-order thinking skills. Educational Psychologist, 21, 191–208.
Mayer, R. E. (2001). Multimedia learning. New York: Cambridge University Press.
Mayer, R., & Gallini, J. (1990). When is an illustration worth ten thousand words? Journal of Educational Psychology, 82, 715–726.
Mayer, R., Mautone, P., & Prothero, W. (2002). Pictorial aids for learning by doing in a multimedia geology simulation game. Journal of Educational Psychology, 94, 171–185.
Mayer, R. E., & Sims, V. K. (1994). For whom is a picture worth a thousand words? Extensions of a dual-coding theory of multimedia learning. Journal of Educational Psychology, 86, 389–401.
Mayer, R., 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.
McNamara, D., Kintsch, E., Songer, N. B., & Kintsch, W. (1996). Are good texts always better? Interactions of text coherence, Background knowledge, and levels of understanding in learning from text. Cognition and Instruction, 14, 1–43.
Miyake, A., & Shah, P. (1999). Models of working memory: Mechanisms of active maintenance and executive control. New York: Cambridge University Press.
Moreno, R. (2002). Who learns best with multiple representations? Cognitive theory predictions on individual differences in multimedia learning. World Conference on Educational Multimedia, Hypermedia and Telecommunications 2002(1), 1380–1385.
Moreno, R., & Durán, R. (2004). Do multiple representations need explanations? The role of verbal guidance and individual differences in multimedia mathematics learning. Journal of Educational Psychology, 96, 492–503.
Moreno, R., & Plass, J. L. (2006, April). Individual differences in learning with verbal and visual representations. Paper presented at the Technology and Learning Symposium, New York.
Morgan, M. (1985). Self-monitoring of attained subgoals in private study. Journal of Educational Psychology, 77(6), 623–630.
Muraven, M., Tice, D. M., & Baumeister, R. F. (1998). Self-control as a limited resource: Regulatory depletion patterns. Journal of Personality and Social Psychology, 74(3), 774–789.
Nückles, M., Wittwer, J., & Renkl, A. (2005). Information about a layperson's knowledge supports experts in giving effective and efficient online advice to laypersons. Journal of Experimental Psychology: Applied, 11, 219–236.
Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2009). Learning Styles: Concepts and Evidence. Psychological Science in the Public Interest, 9(3), 105–119.
Pintrich, P. R., & Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82, 33–40.
Plass, J. L., Chun, D. M., Mayer, R. E., & Leutner, D. (1998). Supporting visual and verbal learning preferences in a second-language multimedia learning environment. Journal of Educational Psychology, 90, 25–36.
Plass, J. L., Chun, D. M., Mayer, R. E., & Leutner, D. (2003). Cognitive load in reading a foreign language text with multimedia aids and the influence of verbal and spatial abilities. Computers in Human Behavior, 19, 221–243.
Pollock, E., Chandler, J., & Sweller, J. (2002). Assimilating complex information. Learning and Instruction, 12, 61–86.
Putnam, R. T. (1987). Structuring and adjusting content for students: A study of live and simulated tutoring of addition. American Educational Research Journal, 24, 13–48.
Renkl, A. (2005, August). Finding and fixing errors in worked examples: Can this foster learning outcomes? Paper presented at the 11th Biennial Conference of the European Association for Research in Learning and Instruction, Nicosia, Cyprus.
Renkl, A., & Atkinson, R. K. (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., & Staley, R. (2002). From example study to problem solving: Smooth transitions help learning. Journal of Experimental Education, 70, 293–315.
Schoenfeld, A. H. (1987). What's all the fuss about metacognition? In Schoenfeld, A. H. (Ed.), Cognitive science and mathematics education (pp. 189–215). Hillsdale, NJ: Erlbaum.
Shaft, T. M. (1995). Helping programmers understand computer programs: The use of metacognition. Data Base Advances, 26, 25–46.
Shah, P., & Miyake, A. (1996). The separability of working memory resources for spatial thinking and language processing: An individual differences approach. Journal of Experimental Psychology: General, 125(1), 4–27.
Shute, V. J. (1992). Aptitude-treatment interactions and cognitive skill diagnosis. In Regian, J. W. & Shute, V. J. (Eds.), Cognitive approaches to automated instruction (pp. 15–47). Hillsdale, NJ: Erlbaum.
Shute, V., & Towle, B. (2003). Adaptive e-learning. Educational Psychologist, 38, 105–114.
Snow, R. E. (1989). Aptitude-treatment interaction as a framework for research on individual differences in learning. In Ackerman, P. L., Sternberg, R. J., & Glaser, R. (Eds.), Learning and individual differences. Advances in theory and research (pp. 13–59). New York: Freeman.
Snow, R. (1994). Abilities in academic tasks. In Sternberg, R. & Wagner, R. (Eds.), Mind in context: Interactionist perspectives on human intelligence (pp. 3–37). Cambridge, MA: Cambridge University Press.
Snow, R., & Lohman, D. (1984). Toward a theory of cognitive aptitude for learning from instruction. Journal of Educational Psychology, 76, 347–376.
Snow, R. E., & Lohman, D. F. (1989). Implications of cognitive psychology for educational measurement. In Linn, R. (Ed.), Educational measurement (pp. 263–331). New York: Macmillan.
Sweller, J. (2005). The redundancy principle in multimedia learning. In Mayer, R. (Ed.), Cambridge handbook of multimedia learning (pp. 159–167). New York: Cambridge.
Sweller, J., Chandler, P., Tierney, P., & Cooper, M. (1990). Cognitive load and selective attention as factors in the structuring of technical material. Journal of Experimental Psychology: General, 119, 176–192.
Tarmizi, R., & Sweller, J. (1988). Guidance during mathematical problem solving. Journal of Educational Psychology, 80, 424–436.
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., 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.
Vohs, K. D., & Heatherton, T. F. (2000). Self-regulatory failure: A resource-depletion approach. Psychological Science, 11(3), 249–254.
Waller, D. (2000). Individual differences in spatial learning from computer-simulated environments. Journal of Experimental Psychology: Applied, 6, 307–321.
Ward, M., & Sweller, J. (1990). Structuring effective worked examples. Cognition and Instruction, 7, 1–39.
White, B., & Frederiksen, J. (2005). A theoretical framework and approach for fostering metacognitive development. Educational Psychologist, 40(4), 211–223.
Winne, P. H. (2001). Self-regulated learning viewed from models of information processing. In Zimmerman, B. J. & Schunk, D. H. (Eds.), Self-regulated learning and academic achievement: Theoretical perspectives (2nd ed., pp. 153–189). Mahwah, NJ: Erlbaum.
Yang, Y. C. (1993). The effects of self-regulatory learning skills and type of instructional control on learning from computer-based instruction. International Journal of Instructional Media, 20, 235–241.
Zimmerman, B. J. (1998). Developing self-fulfilling cycles of academic regulation: An analysis of exemplary instructional models. In Schunk, D. H. & Zimmerman, B. J. (Eds.), Self-regulated learning: From teaching to self-reflective practice (pp. 1–19). New York: Guilford.
Zimmerman, B. J., & Kitsantas, A. (1999). Acquiring writing revision skill: Shifting from process to outcome self-regulatory goals. Journal of Educational Psychology, 91, 241–250.
Zimmerman, B. J., & Schunk, D. H. (Eds.). (2001). Self-regulated learning and academic achievement: Theoretical perspectives (2nd ed). Mahwah, NJ: Erlbaum.