Self-explanation
Renkl describes self-explanations as explanations provided by learners and mainly directed to themselves[1]. In a review of cognitive load theory in pharmacy education, self-explanation is listed among activities said to promote germane load and to strengthen schema construction and deep learning[2].
Key points
- In one study of 55 university students learning facts about the cardiovascular system, the self-explanation group significantly outperformed an elaborative interrogation group and a repetition group on cued recall and recognition[3].
- In work on worked examples, successful learners are described as having studied the examples for longer and explained them more actively to themselves[4].
- In a survey of 730 medical students in Berlin, self-explanation was one of the three techniques used most[5].
- Studying worked examples is described as losing effectiveness with increasing expertise[1].
What self-explanation involves
In the same description, self-explanations contain information that is not directly given in the learning materials and refer to solution steps and the reasons for them[1]. In one study, university students learned facts about the cardiovascular system, and the self-explanation group explained what the facts meant to them and how they related to their prior knowledge[3]. A worked example is described as a step-by-step demonstration of how to perform a task or solve a problem[6].
What the research describes
Elaborative interrogation, in which participants answered "why" the facts made sense, was no more effective than repetition in that study[3]. Self-explanations are described as "important and necessary"[4]. In the Berlin survey, self-explanation was classed as a moderate-utility technique[5].
Self-explanation with worked examples
Worked examples are described as able to increase germane load when prompts for self-explanations are used[7]. Fading out steps in a worked example is described as triggering self-explanation, meaning the learners' own explanations of the reasons for the given solution steps[8]. Renkl suggests that prompts, a help system and/or training be used to facilitate learners' self-explanations[1]. One account states that learners "should be guided to actively self-explain worked-out examples"[1].
Limits
As learners gain expertise, worked examples lose effectiveness because of the expertise reversal effect, and faded worked examples are described as addressing this by structuring the learners' transition to problem-solving[9]. Further limitations of the classical worked-example method include "focusing on one single correct solution and on algorithmic skill domains"[1]. Addressing restrictions of this kind in multimedia learning environments is described as an area of active research[1].
Sources
- C Renkl, Alexander (2014-07-28), "The Worked Examples Principle in Multimedia Learning" , in Mayer, Richard E. (ed.), The Cambridge Handbook of Multimedia Learning (2 ed.), Cambridge University Press, pp. 391– 412, doi : 10.1017/cbo9781139547369.020 , ISBN 978-1-139-54736-9 , retrieved 2026-03-09 cambridge.org
- A Islam MA, Yang S, Kim L, Talukder RM. Applying Cognitive Load Theory to Best Practices in Pharmacy Education: A Narrative Review. Am J Pharm Educ. 2026. doi:10.1016/j.ajpe.2026.102060
- B O'Reilly T, Symons S, MacLatchy-Gaudet H. A Comparison of Self-Explanation and Elaborative Interrogation. Contemp Educ Psychol. 1998. doi:10.1006/ceps.1997.0977
- B Chi, M. T.; Bassok, M.; Lewis, M. W.; Reimann, P.; Glaser, R. (1989). "Self-explanations: How students study and use examples in learning to solve problems" . Cognitive Science . 13 (2): 145– 182. doi : 10.1207/s15516709cog1302_1 . doi.org
- B Franz A, Oberst S, Peters H, Berger R, Behrend R. How do medical students learn conceptual knowledge? High-, moderate- and low-utility learning techniques and perceived learning difficulties. BMC Med Educ. 2022. doi:10.1186/s12909-022-03283-0
- C Clark, R. C.; Nguyen, F.; Sweller, J. (2006). Efficiency in learning: evidence-based guidelines to manage cognitive load . San Francisco: Pfeiffer. ISBN 9780787982065 .
- B Paas, F.; Renkl, A.; Sweller, J. (2003). "Cognitive load theory and instructional design: Recent developments". Educational Psychologist . 38 (1): 1– 4. doi : 10.1207/S15326985EP3801_1 . ISSN 0046-1520 . OCLC 4893972493 . S2CID 8107220 . doi.org
- B Renkl, A.; Atkinson, R. K.; Große, C. S. (2004). "How fading worked solution steps works–a cognitive load perspective". Instructional Science . 32 ( 1– 2): 59– 82. doi : 10.1023/B:TRUC.0000021815.74806.f6 . ISSN 0020-4277 . S2CID 56832624 . doi.org
- B Salden, R. J. C. M.; Aleven, V.; Schwonke, R.; Renkl, A. (May 2010). "The expertise reversal effect and worked examples in tutored problem solving" . Instructional Science . 38 (3): 289– 307. doi : 10.1007/s11251-009-9107-8 . JSTOR 23372797 . S2CID 53333474 . jstor.org