Advancing the Design of Self-Explanation Prompts for Complex Problem-Solving

Hyun Joo, Jinju Lee, Dongsik Kim

Abstract


This research investigated the effects of focus (inference vs. inference followed by integration) and level (low vs. middle vs. high) in self-explanation prompts on both cognitive load and learning outcomes. To achieve this goal, a 2*3 experiment design was employed. A total of 199 South Korean high school students were randomly assigned to one of six conditions. The two-way MANOVA was used to analyse the effects of the self-explanation prompts on learning outcomes. Results showed that there was an interaction effect between focus and level of self-explanation prompts on delayed conceptual knowledge, suggesting that the focus of self-explanation prompts could be varied depending on their level. Second, learners who were given a high level of prompts scored higher on the immediate conceptual knowledge test than those who received a low level of prompts. A two-way ANOVA was conducted to analyse the effects of the self-explanation prompts on cognitive load and showed no significant interaction effect. However, there was a main effect in the level of the prompt that a high level of self-explanation prompts imposed a lower cognitive load compared to a low level of prompts. In sum, the design and development of self-explanation prompts should consider both focus and level, especially to improve complex problem-solving skills.

https://doi.org/10.26803/ijlter.19.11.6


Keywords


cognitive load; complex problem-solving; conceptual knowledge; procedural knowledge; self-explanation prompts

Full Text:

PDF

References


Atkinson, R. K., Renkl, A., & Merrill, M. M. (2003). Transitioning from studying examples to solving problems: Effects of self-explanation prompts and fading worked-out steps. Journal of Educational Psychology, 95(4), 774-783. doi:10.1037/0022-0663.95.4.774

Barbieri, C. A., Miller-Cotto, D., & Booth, J. L. (2019). Lessening the load of misconceptions: Design-based principles for algebra learning. Journal of the Learning Sciences, 28(3), 381-417. doi:10.1080/10508406.2019.1573428

Berthold, K., Eysink, T. H., & Renkl, A. (2009). Assisting self-explanation prompts are more effective than open prompts when learning with multiple representations. Instructional Science, 37(4), 345-363. doi:10.1007/s11251- 008-9051-z

Berthold, K., & Renkl, A. (2009). Instructional aids to support a conceptual understanding of multiple representations. Journal of Educational Psychology, 101(1), 70-80. doi:10.1037/a0013247

Berthold, K., Röder, H., Knörzer, D., Kessler, W., & Renkl, A. (2011). The double-edged effects of explanation prompts. Computers in Human Behavior, 27(1), 69-75. doi:10.1016/j.chb.2010.05.025.

Bisra, K., Liu, Q., Nesbit, J. C., Salimi, F., & Winne, P. H. (2018). Inducing self-explanation: A meta-analysis. Educational Psychology Review, 30, 703-725. doi:10.1007/s10648-018-9434-x

Chen, X., Mitrovic, A. T., & Matthews, M. (2019). Learning from worked examples, erroneous examples and problem solving: Towards adaptive selection of learning activities. IEEE Transactions on Learning Technologies, 13(1), 135-149. doi:10.1109/TLT.2019.2896080

Chi, M. T. H. (2000). Self-explaining expository texts: The dual processes of generating inferences and repairing mental models. In R. Glaser (Ed.), Advances in Instructional Psychology (pp. 161-238). Hillsdale, NJ: Lawrence Erlbaum Associates.

Chi, M. T. H., de Leeuw, N., Chiu, M. H., & LaVancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18(3), 439-477. doi:10.1016/0364-0213(94)90016-7

Chiu, J. L., & Chi, M. T. H. (2014). Supporting self-explanation in the classroom. In V. A. Benasi, C. E. Overson, & C. M. Hakala (Eds.), Applying Science of Learning in Education: Infusing Psychological Science into the Curriculum (pp. 91–103). Washington, DC: Division 2, American Psychological Association.

Conati, C., & VanLehn, K. (2000). Toward computer-based support of meta-cognitive skills: A computational framework to coach self-explanation. International Journal of Artificial Intelligence in Education (IJAIED), 11, 389-415.

DeCaro, M. S., & Rittle-Johnson, B. (2012). Exploring mathematics problems prepares children to learn from instruction. Journal of Experimental Child Psychology, 113(4), 552–568. doi:10.1016/j.jecp.2012.06.009

De Koning, B. B., Tabbers, H. K., Rikers, R. M., & Paas, F. (2011). Attention cueing in an instructional animation: The role of presentation speed. Computers in Human Behavior, 27(1), 41-45. doi:10.1016/j.chb.2010.05.010

de Jong, T., & Ferguson-Hessler, M. G. (1996). Types and qualities of knowledge. Educational psychologist, 31(2), 105-113. doi:10.1207/s15326985ep3102_2

Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14(1), 4–58. doi:10.1177/1529100612453266

Durkin, K. & Rittle-Johnson, B. (2012). The effectiveness of using incorrect examples to support learning about decimal magnitude. Learning and Instruction, 22(3), 206–214. doi:10.1016/j.learninstruc.2011.11.001

Fabic, G. V. F., Mitrovic, A., & Neshatian, K. (2019). Evaluation of Parsons problems with menu-based self-explanation prompts in a mobile python tutor. International Journal of Artificial Intelligence in Education, 29(4), 507-535. doi:10.1007/s40593-019-00192-0

Fiorella, L. & Mayer, R. E. (2015). Learning as a generative activity: Eight learning strategies that promote understanding. New York: Cambridge University Press.

Fonseca, B. A., & Chi, M. T. H. (2010). Instruction based on self-explanation. In R. Mayer & P. Alexander (Eds.), The Handbook of Research on Learning and Instruction (pp. 296–321). New York: Routledge Press.

Gadgil, S., Nokes-Malach, T. J., & Chi, M. T. (2012). Effectiveness of holistic mental model confrontation in driving conceptual change. Learning and Instruction, 22(1), 47–61. doi:10.1016/j.learninstruc2011.06 .002

Ginns, P., & Leppink, J. (2019). Special issue on cognitive load theory: Editorial. Educational Psychology Review, 31, 255–259 doi:10.1007/s10648-019-09474-4

Hahs-Vaughn, D. (2017). Applied Multivariate Statistical Concepts. New York, NY: Routledge.

Hefter, M. H., & Berthold, K. (2020). Preparing learners to self-explain video examples: Text or video introduction?. Computers in Human Behavior. Advanced online publication. doi:10.1016/j.chb.2020.106404

Hoogerheide, V., Deijkers, L., Loyens, S. M., Heijltjes, A., & van Gog, T. (2016). Gaining from explaining: Learning improves from explaining to fictitious others on video, not from writing to them. Contemporary Educational Psychology, 44â€45, 95–106. doi:10.1016/j.cedpsych.2016.02.005

Jonassen, D. H. (2000). Toward a design theory of problem solving. Educational Technology Research & Development, 48(4), 63–85. doi:10.1007/BF02300500

Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003). The expertise reversal effect. Educational Psychologist, 38(1), 23-31. doi:10.1207/S15326985EP3801_4

King, A. (1990). Enhancing peer interaction and learning in the classroom through reciprocal questioning. American Educational Research Journal, 27(4), 664-687. doi:10.3102/00028312027004664

Leppink, J., Broers, N. J., Imbos, T., van der Vleuten, C. P., & Berger, M. P. (2012). Self-explanation in the domain of statistics: an expertise reversal effect. Higher Education, 63(6), 771-785. doi:10.1007/s10734-011-9476-1

Lin, L., & Atkinson, R. K. (2013). Enhancing learning from different visualizations by self-explanation prompts. Journal of Educational Computing Research, 49(1), 83-110. doi:83-110. 10.2190/EC.49.1.d

Lin, L., Atkinson, R. K., Savenye, W. C., & Nelson, B. C. (2016). Effects of visual cues and self-explanation prompts: empirical evidence in a multimedia environment. Interactive Learning Environments, 24(4), 799-813. doi:10.1080/10494820.2014.924531

Lombrozo, T. (2006). The structure and function of explanations. TRENDS in Cognitive Science, 10(10), 464–470. doi:10.1016/j. tics.2006.08.004

McCormick, R. (1997). Conceptual and procedural knowledge. International Journal of Technology and Design Education, 7(1-2), 141-159.

McEldoon, K. L., Durkin, K. L., & Rittle-Johnson, B. (2013). Is self-explanation worth the time? A comparison to additional practice. British Journal of Educational Psychology, 83(4), 615–632. doi:10.1111/j.2044-8279.2012.02083.x

Miller-Cotto, D., & Auxter, A. E. (2019). Testing the ecological validity of faded worked examples in algebra. Educational Psychology, 1-15. doi:10.1080/01443410.2019.1646411

Morrison, J. R., Bol, L., Ross, S. M., & Watson, G. S. (2015). Paraphrasing and prediction with self-explanation as generative strategies for learning science principles in a simulation. Educational Technology Research and Development, 63(6), 861-882. doi:10.1007/s11423-015-9397-2

Neubrand, C., & Harms, U. (2017). Tackling the difficulties in learning evolution: Effects of adaptive self-explanation prompts. Journal of Biological Education, 51(4), 336-348. doi:10.1080/00219266.2016.1233129

Nokes, T. J., Hausmann, R. G. M., VanLehn, K., & Gershman, S. (2011). Testing the instructional fit hypothesis: The case of self-explanation prompts. Instructional Science, 39(5), 645-666. doi:10.1007/s11251-010-9151-4

O’Neil, H. F., Chung, G. K. W. K., Kerr, D., Vendlinski, T. P., Buschang, R. E., & Mayer, R. E. (2014). Adding self-explanation prompts to an educational computer game. Computers in Human Behavior, 30, 23–28. doi:10.1016/j.chb.2013.07.025

Paas, F., & Ayres, P. (2014). Cognitive load theory: A broader view on the role of memory in learning and education. Educational Psychology Review, 26(2), 191-195. doi:10.1007/s10648-014-9263-5

Paas, F., & Van Merriënboer, J. J. G. (1994). Instructional control of cognitive load in the training of complex cognitive tasks. Educational Psychology Review, 6(4), 351-371. doi:10.1007/BF02213420

Rau, M. A., Aleven, V., & Rummel, N. (2015). Successful learning with multiple graphical representations and self-explanation prompts. Journal of Educational Psychology, 107(1), 30-46. doi:10.1037/a0037211

Renkl, A. (2014). Toward an instructionally oriented theory of exampleâ€based learning. Cognitive Science, 38(1), 1-37. doi:10.1111/cogs.12086

Renkl, A., & Atkinson, R. K. (2003). Structuring the transition from example study to problem solving in cognitive skill acquisition: A cognitive load perspective. Educational Psychologist, 38(1), 15-22. doi:10.1207/S15326985EP3801_3

Renkl, A., & Eitel, A. (2019). Self-explaining: Learning about principles and their application. In J. Dunlosky & K. Rawson (Eds.), Cambridge Handbook of Cognition and Education (pp. 528–549). Cambridge University Press.

Rittle-Johnson, B., & Loehr, A. M. (2017). Eliciting explanations: Constraints on when self-explanation aids learning. Psychonomic Bulletin & Review, 24(5), 1501-1510. doi:10.3758/s13423-016-1079-5

Rittle-Johnson, B., Loehr, A. M., & Durkin, K. (2017). Promoting self-explanation to improve mathematics learning: A meta-analysis and instructional design principles. ZDM, 49(4), 599-611.

Rittle-Johnson, B., & Schneider, M. (2015). Developing conceptual and procedural knowledge of mathematics. In R. C. Kadosh & A. Dowker (Eds.), Oxford Handbook of Numerical Cognition (pp. 1102–1118). Oxford: Oxford University Press.

Roy, M., & Chi, M. T. H. (2005). The self-explanation principle in multimedia learning. In R. Mayer (Ed.), Cambridge Handbook of Multimedia Learning (pp. 271–286). New York, NY: Cambridge University Press.

Si, J., Kim, D., & Na, C. (2014). Adaptive instruction to learner expertise with bimodal process-oriented worked-out examples. Journal of Educational Technology & Society, 17(1), 259-271. Retrieved from http://www.jstor.org/stable/jeductech

soci.17.1.259

Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive load theory. New York: Springer.

Van Gog, T., Paas, F., & Van Merriënboer, J. J. (2004). Process-oriented worked examples: Improving transfer performance through enhanced understanding. Instructional Science, 32(1), 83-98. doi:10.1023/B:TRUC.0000021810.70784.b0

Wang, Z., & Adesope, O. (2017). Do focused self-explanation prompts overcome seductive details? A multimedia study. Journal of Educational Technology & Society, 20(4), 47-57. Retrieved from http://www.jstor: stable/26229204

Wittrock, M. C. (1989). Generative processes of comprehension. Educational Psychologist, 24(4), 345–376. doi:10.1207/s15326985ep2404_2

Wylie, R., & Chi, M. T. H. (2014). The self-explanation principle in multimedia learning. In R. E. Mayer (Ed.), The Cambridge Handbook of Multimedia Learning (2nd ed., pp. 413–432). New York: Cambridge University Press.

Yeh, Y.-F., Chen, M.-C., Hung, P.-H., & Hwang, G.-J. (2010). Optimal self-explanation prompt design in dynamic multi-representational learning environments. Computers & Education, 54(4), 1089–1100. doi:10.1016/j.compedu.2009.10.013


Refbacks

  • There are currently no refbacks.


e-ISSN: 1694-2116

p-ISSN: 1694-2493