Book contents
- The Cambridge Handbook of Multimedia Learning
- The Cambridge Handbook of Multimedia Learning
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Preface
- Acknowledgments
- Part I Background
- Part II Theoretical Foundations
- Part III Basic Principles of Multimedia Learning
- Part IV Principles for Reducing Extraneous Processing in Multimedia Learning
- Part V Principles for Managing Essential Processing in Multimedia Learning
- Part VI Principles Based on Social and Affective Features of Multimedia Learning
- Part VII Principles Based on Generative Activity in Multimedia Learning
- 28 The Generative Activity Principle in Multimedia Learning
- 29 The Mapping Principle in Multimedia Learning
- 30 The Drawing Principle in Multimedia Learning
- 31 The Imagination Principle in Multimedia Learning
- 32 The Self-Explanation Principle in Multimedia Learning
- 33 The Guided Inquiry Principle in Multimedia Learning
- 34 The Feedback Principle in Multimedia Learning
- 35 The Learner Control Principle in Multimedia Learning
- 36 The Cognitive Load Self-Management Principle in Multimedia Learning
- Part VIII Multimedia Learning with Media
- Author Index
- Subject Index
- References
36 - The Cognitive Load Self-Management Principle in Multimedia Learning
from Part VII - Principles Based on Generative Activity in Multimedia Learning
Published online by Cambridge University Press: 19 November 2021
Book contents
- The Cambridge Handbook of Multimedia Learning
- The Cambridge Handbook of Multimedia Learning
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Preface
- Acknowledgments
- Part I Background
- Part II Theoretical Foundations
- Part III Basic Principles of Multimedia Learning
- Part IV Principles for Reducing Extraneous Processing in Multimedia Learning
- Part V Principles for Managing Essential Processing in Multimedia Learning
- Part VI Principles Based on Social and Affective Features of Multimedia Learning
- Part VII Principles Based on Generative Activity in Multimedia Learning
- 28 The Generative Activity Principle in Multimedia Learning
- 29 The Mapping Principle in Multimedia Learning
- 30 The Drawing Principle in Multimedia Learning
- 31 The Imagination Principle in Multimedia Learning
- 32 The Self-Explanation Principle in Multimedia Learning
- 33 The Guided Inquiry Principle in Multimedia Learning
- 34 The Feedback Principle in Multimedia Learning
- 35 The Learner Control Principle in Multimedia Learning
- 36 The Cognitive Load Self-Management Principle in Multimedia Learning
- Part VIII Multimedia Learning with Media
- Author Index
- Subject Index
- References
Summary
Cognitive load theory (CLT) and the cognitive theory of multimedia learning (CTML) offer empirically supported instructional solutions to the frequent problem of cognitive overload during learning from multimedia materials. Until recently, these solutions have relied completely on instructors creating high quality learning materials and learners having access to those materials. However, in practice learners frequently have to deal with digital and printed multimedia learning materials that have not been designed with any consideration of cognitive load. The self-management principle has emerged from research using the vantage point of the learner, and is based on empowering learners to apply CLT or CTML principles themselves to manage their own cognitive load. In this chapter we present the rationale for the principle, empirical evidence, and theoretical and practical implications.
Keywords
- Type
- Chapter
- Information
- The Cambridge Handbook of Multimedia Learning , pp. 430 - 436Publisher: Cambridge University PressPrint publication year: 2021
References
Agostinho, S., Tindall-Ford, S., & Bokosmaty, S. (2014). Adaptive diagrams: A research agenda to explore how learners can manipulate online diagrams to self-manage cognitive load. In Huang, W. (ed.), Handbook of Human Centric Visualization (pp. 529–550). New York: Springer.Google Scholar
Agostinho, S., Tindall-Ford, S., & Roodenrys, K. (2013). Adaptive diagrams: Handing control over to the learner to manage split-attention online. Computers and Education, 64, 52–62.Google Scholar
Ayres, P., & Sweller, J. (2014). The split-attention principle in multimedia learning. In Mayer, R. E. (ed.), The Cambridge Handbook of Multimedia Learning (2nd ed., pp. 206–226). New York: Cambridge University Press.Google Scholar
Baars, M., Wijnia, L., de Bruin, A., & Paas, F. (2020). The relation between student’s effort and monitoring judgments during learning: A meta-analysis. Educational Psychology Review, 32, 979–1002.Google Scholar
Bodemer, D., Ploetzner, R., Feuerlein, I., & Spada, H. (2004). The active integration of information during learning with dynamic and interactive visualizations. Learning and Instruction, 14(3), 325–341.Google Scholar
Chandler, P., & Sweller, J. (1992). The split‐attention effect as a factor in the design of instruction. British Journal of Educational Psychology, 62(2), 233–246.Google Scholar
Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24(1), 87–114.Google Scholar
de Bruin, A. B., & van Merriënboer, J. J. (2017). Bridging cognitive load and self-regulated learning research: A complementary approach to contemporary issues in educational research. Learning and Instruction, 51, 1–9.Google Scholar
de Koning, B. B., & Eitel, A. (2020). When seductive details do not harm learning: Further evidence for informed-use effects. Paper presented at the Meeting of the European Association for Research on Learning and Instruction (EARLI) – Special Interest Group (SIG) 2 on “Comprehension of text and graphics,” Online conference.Google Scholar
de Koning, B. B., Rop, G., & Paas, F. (2020a). Learning from split-attention materials: Effects of teaching physical and mental learning strategies. Contemporary Educational Psychology, 61, 101873.CrossRefGoogle Scholar
de Koning, B. B., Rop, G., & Paas, F. (2020b). Effects of spatial distance on the effectiveness of mental and physical integration strategies in learning from split-attention examples. Computers in Human Behavior, 110, 106379.Google Scholar
de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2009). Towards a framework for attention cueing in instructional animations: Guidelines for research and design. Educational Psychology Review, 21(2), 113–140.Google Scholar
de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2010). Learning by generating vs. receiving instructional explanations: Two approaches to enhance attention cueing in animations. Computers and Education, 55(2), 681–691.Google Scholar
Doherty-Sneddon, G., Bruce, V., Bonner, L., Longbotham, S., & Doyle, C. (2002). Development of gaze aversion as disengagement from visual information. Developmental Psychology, 38(3), 438–445.Google Scholar
Eitel, A., Bender, L., & Renkl, A. (2019a). Are seductive details seductive only when you think they are relevant? An experimental test of the moderating role of perceived relevance. Applied Cognitive Psychology, 33(1), 20–30.Google Scholar
Eitel, A., Bender, L., & Renkl, A. (2019b). Effects of informed use: A proposed extension of the self-management effect. In Tindall-Ford, S., Agostinho, S., & Sweller, J. (eds.), Advances in Cognitive Load Theory: Rethinking Teaching (pp. 168–179). London: Routledge.CrossRefGoogle Scholar
Gordon, C., Tindall-Ford, S., Agostinho, S., & Paas, F. (2016). Learning from instructor-managed and self- managed split-attention materials. Applied Cognitive Psychology, 30, 1–9.Google Scholar
Hatsidimitris, G., & Kalyuga, S. (2013). Guided self-management of transient information in animations through pacing and sequencing strategies. Educational Technology Research and Development, 61(1), 91–105.Google Scholar
Lafay, A., Thevenot, C., Castel, C., & Fayol, M. (2013). The role of fingers in number processing in young children. Frontiers in Psychology, 4, 488.CrossRefGoogle ScholarPubMed
Leahy, W., & Sweller, J. (2004). Cognitive load and the imagination effect. Applied Cognitive Psychology, 18(7), 857–875.Google Scholar
Leahy, W., & Sweller, J. (2008). The imagination effect increases with an increased intrinsic cognitive load. Applied Cognitive Psychology, 22(2), 273–283.Google Scholar
Leopold, C., & Leutner, D. (2015). Improving students’ science text comprehension through metacognitive self-regulation when applying learning strategies. Metacognition and Learning, 10(3), 313–346.Google Scholar
Mautone, P. D., & Mayer, R. E. (2001). Signaling as a cognitive guide in multimedia learning. Journal of Educational Psychology, 93(2), 377–389.CrossRefGoogle Scholar
Mayer, R. E. (1997). Multimedia learning: Are we asking the right questions? Educational Psychologist, 32, 1–19.Google Scholar
Mayer, R. E. (ed.) (2014). The Cambridge Handbook of Multimedia Learning (2nd rev ed.). New York: Cambridge University Press.CrossRefGoogle Scholar
Mayer, R. E., & Moreno, R. (1998). A cognitive theory of multimedia learning: Implications for design principles. Journal of Educational Psychology, 91(2), 358–368.Google Scholar
Mirza, F., Agostinho, S., Tindall-Ford, S., Paas, F., & Chandler, P. (2020). Self-management of cognitive load: Potential and challenges. In Tindall-Ford, S. K., Agostinho, S., & Sweller, J. (eds.), Advances in Cognitive Load Theory: Rethinking Teaching (pp. 157–167). London: Routledge.Google Scholar
Mousavi, S. Y., Low, R., & Sweller, J. (1995). Reducing cognitive load by mixing auditory and visual presentation modes. Journal of Educational Psychology, 87(2), 319–334.CrossRefGoogle Scholar
Orvis, K. A., Fisher, S. L., & Wasserman, M. E. (2009). Power to the people: Using learner control to improve trainee reactions and learning in web-based instructional environments. Journal of Applied Psychology, 94(4), 960–971.Google Scholar
Paas, F. (1992). Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive-load approach. Journal of Educational Psychology, 84(4), 429–434.Google Scholar
Paas, F., & Sweller, J. (2012). An evolutionary upgrade of cognitive load theory: Using the human motor system and collaboration to support the learning of complex cognitive tasks. Educational Psychology Review, 24(1), 27–45.Google Scholar
Paas, F., & van Merriënboer, J. J. G. (2020). Cognitive-load theory: Methods to manage working memory load in the learning of complex tasks. Current Directions in Psychological Science, 29(4), 394–398.Google Scholar
Puma, S., Matton, N., Paubel, P. V., & Tricot, A. (2018). Cognitive load theory and time considerations: Using the time-based resource sharing model. Educational Psychology Review, 30, 1199–1214.Google Scholar
Roodenrys, K., Agostinho, S., Roodenrys, S., & Chandler, P. (2012). Managing one’s own cognitive load when evidence of split attention is present. Applied Cognitive Psychology, 26(6), 878–886.Google Scholar
Sepp, S., Agostinho, S., Tindall-Ford, S., & Paas, F. (2020). Gesture-based learning with ICT: Recent developments, opportunities and considerations. In Sweller, J., Tindall-Ford, S., & Agostinho, S. (eds.), Advances in Cognitive Load Theory: Rethinking Teaching (pp. 130–141). London: Routledge.Google Scholar
Sepp, S., Howard, S. J., Tindall-Ford, S., Agostinho, S., & Paas, F. (2019). Cognitive load theory and human movement: Towards an integrated model of working memory. Educational Psychology Review, 31, 293–318.Google Scholar
Sithole, S. T. M., Chandler, P., Abeysekera, I., & Paas, F. (2017). Benefits of guided self-management of attention on learning accounting. Journal of Educational Psychology, 109(2), 220–232.Google Scholar
Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive Load Theory. New York: Springer.Google Scholar
Sweller, J., & Cooper, G. A. (1985). The use of worked examples as a substitute for problem solving in learning algebra. Cognition and Instruction, 2(1), 59–89.Google Scholar
Sweller, J., van Merrienboer, J. J. G., & Paas, F. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296.Google Scholar
Sweller, J., van Merriënboer, J. J. G., & Paas, F. (2019). Cognitive architecture and instructional design: 20 years later. Educational Psychology Review, 31, 261–292.Google Scholar
Tarmizi, R. A., & Sweller, J. (1988). Guidance during mathematical problem solving. Journal of Educational Psychology, 80(4), 424–436.Google Scholar
Tindall-Ford, S., Agostinho, S., Bokosmaty, S., Paas, F., & Chandler, P. (2015). Computer-based learning of geometry from integrated and split-attention worked examples: The power of self-management. Educational Technology and Society, 18(4), 89–99.Google Scholar
Tindall-Ford, S., Agostinho, S., & Sweller, J. (eds.) (2020). Advances in Cognitive Load Theory: Rethinking Teaching. London: Routledge.Google Scholar
Vredeveldt, A., Hitch, G. J., & Baddeley, A. D. (2011). Eyeclosure helps memory by reducing cognitive load and enhancing visualisation. Memory & Cognition, 39(7), 1253–1263.CrossRefGoogle ScholarPubMed
Zhang, S., de Koning, B., & Paas, F. (submitted). Finger pointing to self-manage cognitive load in learning from split attention examples.Google Scholar
- 3
- Cited by