Learning From Examples: Fostering Self-Explanations in Computer-Based Learning Environments
Abstract
Cognitive skills acquisition involves developing the ability to solve problems in knowledge-rich task domains, and is particularly important for any individual attempting to meet the challenges of our modern, knowledge-driven economy. This type of economy argues for reconceptualizing cognitive skills acquisition as a lifelong process. Research has shown that worked-out examples are the key to initial cognitive skill acquisition and, therefore, critical to lifelong learning. The extent to which learners' profit from the study of examples, however, depends on how well they explain the solutions of the examples to themselves. This paper discusses our own research on different types of computer-based learning environments that indirectly foster self-explanations by (a) fostering anticipative reasoning, (b) supporting self-explanations during the transition from example study to problem solving, and (c) supporting self-explanation activities with instructional explanations. It also discusses ways of leveraging new computer and video technologies to enhance these environments by representing problem situations and their concepts dynamically. The paper concludes by suggesting that these learning environments, if employed successfully, can encourage systematic, lifelong learning.
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Asking learners to explain to themselves aloud what they have understood from a learning task has proved to be an effective instructional method.
“Asking learners to explain to themselves aloud what they have understood from a learning task has proved to be an effective instructional method (Chi et al. 1989;Renkl 1997;Renkl and Atkinson 2002).”
From Interactivity in Video-based Models (2007) · cites this paper as Renkl and Atkinson 2002
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“Also, the research literature on selfexplanations indicates that an active engagement of learners in the learning process fosters a better integration of new knowledge with prior knowledge and higher levels of transfer (Chi et al., 1994; Renkl & Atkinson, 2002; Roy & Chi, 2005).”
BackgroundHow to Optimize Learning From Animated Models: A Review of Guidelines Based on Cognitive Load
Wouters, P., Paas, F., & van Merriënboer, J. J. G. (2008) · Review of Educational Research · doi:10.3102/0034654308320320 · Cited by 224 · see citing works
“Self-explanation has proven to be a successful approach to engaging in the active processing of learning material (Chi et al., 1989; Renkl, 1997; Renkl & Atkinson, 2002; Roy & Chi, 2005).”
BackgroundMethodThe Worked-Out Examples Principle in Multimedia Learning
Renkl, A. (2005) · Cambridge University Press eBooks · doi:10.1017/cbo9780511816819.016 · Cited by 223 · see citing works
Self-citationComputer-supported example-based learning: When instructional explanations reduce self-explanations
Schworm, S., & Renkl, A. (2006) · Comput. Educ. · doi:10.1016/j.compedu.2004.08.011 · Cited by 198 · see citing works
“In recent years, several projects have been conducted in which self-explanations during the study of worked-out examples were fostered by computer-based prompting (see also Renkl & Atkinson, 2002).”
BackgroundSelf-citationSubgoals, Context, and Worked Examples in Learning Computing Problem Solving
Morrison, B. B., Margulieux, L. E., & Guzdial, M. (2015) · Proceedings of the eleventh annual International Conference on International Computing Education Research · doi:10.1145/2787622.2787733 · Cited by 174 · see citing works
“hinder learning but is inherent in worked examples [21].”
BackgroundMargulieux, L. E., Guzdial, M., & Catrambone, R. (2012) · Proceedings of the ninth annual international conference on International computing education research · doi:10.1145/2361276.2361291 · Cited by 149 · see citing works
Interactivity in Video-based Models
Wouters, P., Tabbers, H. K., & Paas, F. (2007) · Educational Psychology Review · doi:10.1007/s10648-007-9045-4 · Cited by 145 · see citing works
“Asking learners to explain to themselves aloud what they have understood from a learning task has proved to be an effective instructional method (Chi et al. 1989; Renkl 1997; Renkl and Atkinson 2002 ).”
MethodSubgoals Help Students Solve Parsons Problems
Morrison, B. B., Margulieux, L. E., Ericson, B. J., & Guzdial, M. (2016) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/2839509.2844617 · Cited by 126 · see citing works
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Oud, J. (2009) · Reference Services Review · doi:10.1108/00907320910957206 · Cited by 110 · see citing works
“However, students often have difficulty processing the steps and creating explanations on their own, and need help understanding the concepts involved in solving the problem or example, and how the processes involved work ( Renkl and Atkinson, 2002”
BackgroundMore confusion and frustration, better learning: The impact of erroneous examples
Richey, J., Andres-Bray, J., Mogessie, M., Scruggs, R., Andres, J., Star, J., Baker, R., & McLaren, B. (2019) · Comput. Educ. · doi:10.1016/j.compedu.2019.05.012 · Cited by 87 · see citing works
“…Ward & Sweller, 1990), examples with instructional explanations (i.e., worked examples with conceptual explanations provided along with each step; Renkl, 2002), and erroneous examples (i.e., worked examples that incorporate at least one incorrect solution step; Booth, Lange, Koedinger, & Newton,…”
BackgroundImproved effectiveness of cueing by self-explanations when learning from a complex animation
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“Moreover, self-explaining forces learners to explicate their understanding, and to generate inferences, which might help them to monitor and revise their knowledge base (Renkl & Atkinson, 2002).”
BackgroundHow to sequence video modeling examples and inquiry tasks to foster scientific reasoning
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“Renkl and Atkinson (2002) explore a variety of ways in which problems and examples can be structured to indirectly encourage self-explanation.”
BackgroundVarying effects of subgoal labeled expository text in programming, chemistry, and statistics
Margulieux, L. E., Catrambone, R., & Schaeffer, L. M. (2018) · Instructional Science · doi:10.1007/s11251-018-9451-7 · Cited by 49 · see citing works
“…improve learning by highlighting the procedure used in examples (Atkinson and Derry 2000; Atkinson et al. 2003; Margulieux et al. 2016), providing organization for new information (Morrison et al. 2015), and inducing self-explanation (Catrambone 1998; Renkl and Atkinson 2002; Morrison et al. 2016).”
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Vogel-Walcutt, J. J., Fiorella, L., & Malone, N. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2013.01.038 · Cited by 47 · see citing works
“…to novices all of the steps required for solving a problem rather than requiring them to solve the problems on their own N D, P Atkinson (2002), Renkl and Atkinson (2002), see Van Gog and Rummel (2010) for a review Faded examples/ completion problems As trainees develop expertise, begin to…”
BackgroundInfluentialImproving problem solving with subgoal labels in expository text and worked examples
Margulieux, L. E., & Catrambone, R. (2015) · Learning and Instruction · doi:10.1016/j.learninstruc.2015.12.002 · Cited by 46 · see citing works
“The amount of self-explanations a typical learner makes is low (Chi et al., 1994; Wylie & Chi, 2014), but explanations can also be prompted by the design of instructional materials (Catrambone, 1998; Renkl & Atkinson, 2002).”
BackgroundInfluentialHow effective is instructional support for learning with computer simulations?
Eckhardt, M., Urhahne, D., Conrad, O., & Harms, U. (2012) · Instructional Science · doi:10.1007/s11251-012-9220-y · Cited by 48 · see citing works
“Worked-out examples can be considered to be another kind of interpretative support and have been shown to have positive effects on learning outcomes in numerous studies (e.g., Nerdel and Prechtl 2004; Renkl 2005; Renkl and Atkinson 2002).”
Completion strategy or emphasis manipulation? Task support for teaching information problem solving
Frèrejean, J., van Strien, J. L. H., Kirschner, P. A., & Brand‐Gruwel, S. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.03.048 · Cited by 43 · see citing works
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Bouvier, D. J., Lovellette, E., Matta, J., Alshaigy, B., Becker, B. A., Craig, M., Jacková, J., McCartney, R., Sanders, K., & Zarb, M. (2016) · doi:10.1145/3024906.3024912 · Cited by 47 · see citing works
“This drawback has recently led to a line of work that revisits Soloway’s idea of teaching the underlying subgoals and task structure of programs [5, 6, 7, 11, 30, 36, 39].”
BackgroundInferring Unobservable Learning Variables from Students’ Help Seeking Behavior
Arroyo, I., Murray, T., Woolf, B. P., & Beal, C. R. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-30139-4_74 · Cited by 41 · see citing works
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Margulieux, L. E., Catrambone, R., & Guzdial, M. (2016) · Computer Science Education · doi:10.1080/08993408.2016.1144429 · Cited by 40 · see citing works
“These types of comparisons promote self-explanation (e.g. by prompting students to question why two groups of steps are both characterized by the same subgoal label; Bielaczyc, Pirolli, & Brown, 1995; Renkl & Atkinson, 2002).”
BackgroundWouters, P., Paas, F., & van Merriënboer, J. J. G. (2010) · Instructional Science · doi:10.1007/s11251-008-9079-0 · Cited by 37 · see citing works
“In this respect the generation of self-explanations, in which learners try to explain the rationale of a problem solution to themselves, ha proven to be an effective instructional method (Chi et al., 1989; Renkl, 1997; Renkl & Atkinson, 2002; Roy & Chi, 2005).”
MethodAn Example Order for Cognitive Skill Acquisition
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“Their attention might be diverted away from the relevant information or focused on less important elements in the example, with the risk of a decreased learning effect (Renkl, 1999; Stark, Mandl, Gruber, & Renkl, 2002).”
BackgroundMethodEnhancing Learning from Different Visualizations by Self-Explanation Prompts
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“However, some cognitive strategies serving as instructional aids may be needed to support learning with visualizations (Mayer et al., 2005; Renkl & Atkinson, 2002).”
BackgroundSelf-citationFinding the Best Types of Guidance for Constructing Self-Explanations of Subgoals in Programming
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“By helping learners to focus on structural features of worked examples, subgoal labels are believed to reduce the extraneous cognitive load that is inherent in worked examples due to problem-specific details and can hinder learning (Renkl & Atkinson, 2002).”
BackgroundHow to sequence video modeling examples and inquiry tasks to foster scientific reasoning
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“However, studying examples can give learners an illusion of understanding (Baars et al., 2016; Baars, van Gog, de Bruin, & Paas, 2014; Renkl & Atkinson, 2002).”
BackgroundEngaging Students with Instructor Solutions in Online Programming Homework
Price, T., Williams, J. J., Solyst, J., & Marwan, S. (2020) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376857 · Cited by 22 · see citing works
“Might such benefits extend to comparing a student’s solution to that of the instructor? Another approach might be to provide an explanation of the instructor’s solution, writing out elaborations of the concepts and terms, and how they function and relate to each other, as in a worked-out example [20].”
BackgroundMorrison, B. B., Decker, A., & Margulieux, L. E. (2016) · ACM Conference on International Computing Education Research (ICER) · doi:10.1145/2960310.2960330 · Cited by 21 · see citing works
“By helping learners organize information and focus on structural features of worked examples, subgoal labels are believed to reduce the extraneous cognitive load that can hinder learning but is inherent in worked examples [32].”
BackgroundCreating a Corpus of Targeted Learning Resources with a Web-Based Open Authoring Tool
Aleahmad, T., Aleven, V., & Kraut, R. E. (2009) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2009.8 · Cited by 19 · see citing works
“Worked examples both instruct and help to foster self-explanation [13].”
BackgroundBaker, R. S., Richey, J. E., Zhang, J., Karumbaiah, S., Andres-Bray, J. M. L., Nguyen, H. A., Andres, J. M. A. L., & McLaren, B. M. (2024) · Instructional Science · doi:10.1007/s11251-024-09679-3 · Cited by 16 · see citing works
“Self-explanation activities are more common in non-game digital learning technology than in games (Bisra et al., 2018; McLaren et al., 2008; Renkl & Atkinson, 2002; Roy & Chi, 2005), but some evidence suggests that incorporating self-explanation in games may yield similar benefits.”
Open Community Authoring of Targeted Worked Example Problems
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“Pedagogically, worked-examples both instruct and help to foster self-explanation [10].”
BackgroundLiterature review on the use of e-learning tools for formative essay-type assessment
Heinrich, E., Milne, J., Crooks, T. J., Granshaw, B., & Moore, M. (2006) · Cited by 13 · see citing works
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Jennings, J., & Müldner, K. (2020) · Instructional Science · doi:10.1007/s11251-020-09520-7 · Cited by 13 · see citing works
“Students are asked to study the examples and fill in the gaps by generating the corresponding solution entries (Renkl and Atkinson 2002; Schwonke et al.”
BackgroundTHE EFFECTS OF WEB-BASED PEER REVIEW ON STUDENT WRITING
Wooley, R. S. (2007) · OhioLink ETD Center (Ohio Library and Information Network) · Cited by 12 · see citing works
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Marwan, S., & Price, T. (2022) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2022.3223577 · Cited by 11 · see citing works
“This design feature is also adapted from previous work, which shows that prompting students to selfexplain after viewing worked examples can improve their learning [44], [46].”
Morrison, B. B., Margulieux, L. E., & Decker, A. (2020) · Computer Science Education · doi:10.1080/08993408.2019.1707544 · Cited by 11 · see citing works
“Because learners are more focused on the structural features of the worked example allowing more effective organization of the information, subgoal labels may reduce the extraneous cognitive load that can hinder learning but is inherent in worked examples (Renkl & Atkinson, 2002).”
BackgroundElectronic Repositories of Marked Student Work and their Contributions to Formative Evaluation
Heinrich, E. (2004) · Educational Technology & Society · Cited by 11 · see citing works
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“As a knowledge-building activity (Chi, 2000), students' self-explaining starts from a worked example (i.e., an expert's solution to a problem) and should go beyond the provided information to create these explanations (Chi et al., 1989; Fonseca & Chi, 2011; Renkl & Atkinson, 2002).”
BackgroundInformatics-Lab: Attracting Primary School Pupils for Computer Science
Pasterk, S., Sabitzer, B., Demarle-Meusel, H., et al. (2016) · doi:10.18687/laccei2016.1.1.242 · Cited by 9 · see citing works
“D is co ve ry Solution-based learning [6] Observational learning Step-by-step instructions”
BackgroundPromoting online learning processes and outcomes via video examples and prompts
Hefter, M. H., & Berthold, K. (2023) · Interactive Learning Environments · doi:10.1080/10494820.2022.2164786 · Cited by 10 · see citing works
“After all, a plethora of research brought out example-based training interventions potentials, especially when looking for short-term learning environments to acquire initial knowledge and skills (Hoogerheide & Roelle, 2020; Renkl, 2021; Renkl & Atkinson, 2002).”
Brain-based programming continued: Effective teaching in programming courses
Sabitzer, B., & Pasterk, S. (2014) · 2022 IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie.2014.7044233 · Cited by 8 · see citing works
Using Feedback to Improve Learning: Differentiating between Correct and Erroneous Examples
Wang, M., Yang, Z., Liu, S.-Y., et al. (2015) · International Symposium on Educational Technology · doi:10.1109/iset.2015.28 · Cited by 7 · see citing works
“Therefore, the learning effect was highly associated with how well students explained [7].”
BackgroundChiu, J. L., Chen, J. K., & Linn, M. C. (2013) · Springer international handbooks of education · doi:10.1007/978-1-4419-5546-3_33 · Cited by 7 · see citing works
Improving Programming Instruction with Subgoal Labeled Instructional Text
Margulieux, L. E., & Catrambone, R. (2014) · Digital Archive @ GSU · Cited by 6 · see citing works
Interactive Video Vignettes for Teaching Science
Teese, R. B., Koenig, K. M., & Jackson, D. P. (2020) · Springer eBooks · doi:10.1007/978-3-030-33600-4_41 · Cited by 6 · see citing works
Subgoal Labeled Worked Examples Improve K-12 Teacher Performance in Computer Programming Training
Margulieux, L. E., Catrambone, R., & Guzdial, M. (2013) · Digital Archive @ GSU · Cited by 6 · see citing works
Designed for learning: A case study in rethinking teaching and learning for a large first year class
Goldacre, L., Bolt, S., & Lambiris, M. (2013) · eSpace (Curtin University) · Cited by 5 · see citing works
INFORMATICS – A CHILD’S PLAY?!
Sabitzer, B., Pasterk, S., & Reçi, E. (2014) · Cited by 5 · see citing works
Eckhardt, M., Urhahne, D., & Harms, U. (2018) · Education Sciences · doi:10.3390/educsci8030094 · Cited by 7 · see citing works
“In numerous studies, worked-out examples show positive effects on knowledge acquisition (e.g., [62–67]), especially for novice learners.”
BackgroundHow to optimize cognitive load for learning from animated models
Wouters, P. (2007) · DSpace (Open University in the Netherlands) · Cited by 5 · see citing works
Research Methods in Multimedia Learning
Jarodzka, H. M. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108894333.006 · Cited by 4 · see citing works
Addressing efficiency and quality of marking in essay assessment with e-learning support
Heinrich, E. (2006) · Journal of Open Flexible and Distance Learning · Cited by 3 · see citing works
Development and Assessment of Self-explaining Skills in College Chemistry Instruction
Villalta‐Cerdas, A. (2014) · Digital Commons - University of South Florida (University of South Florida) · Cited by 3 · see citing works
Bauersfeld, J. L., & Gold, B. (2025) · Instructional Science · doi:10.1007/s11251-025-09738-3 · Cited by 2 · see citing works
“For instance, research has shown that training aimed at supporting elaboration during self-explanation (Stark et al., 2002), as well as the use of prompts requiring learners to respond before advancing to the next step (Renkl & Atkinson, 2002), can significantly enhance learning outcomes.”
Open community authoring of worked example problems
Aleahmad, T., Aleven, V., & Kraut, R. E. (2008) · International Conference of Learning Sciences · Cited by 2 · see citing works
Effects of Instruction-Supported Learning with Worked Examples in Quantitative Method Training
Wagner, K., Klein, M., Klopp, E., Puhl, T., & Stark, R. (2013) · Higher Education Studies · doi:10.5539/hes.v3n3p1 · Cited by 2 · see citing works
“It has mainly been applied in well-structured domains (a comprehensive review on the subject is provided by Atkinson et al., 2000; q.v. Hilbert & Renkl, 2008; Reimann, 1997; Renkl, 2001a; Renkl & Atkinson, 2002; Stark, 1999; 2000; 2001 for further results).”
MethodTekınarslan, E. (2014) · Cited by 2 · see citing works
HCI in K12 Computer Science Education – Using HCI as a Topic and a Didactic Tool
Bollin, A., Pasterk, S., Kesselbacher, M., et al. (2021) · doi:10.1145/3464385.3464717 · Cited by 2 · see citing works
“This includes solution-based learning; [31] observational learning; step-by-step instructions and tasks; video”
BackgroundDhlamini, J. J. (2012) · Unisa Institutional Repository (University of South Africa) · Cited by 2 · see citing works
Byers, A. (2010) · VTechWorks (Virginia Tech) · Cited by 2 · see citing works
La lectura digital: requerimientos cognitivos y ayudas para la comprensión
Acuña, S. R., & Aymes, G. L. (2015) · Cited by 1 · see citing works
Huang, X. (2007) · Cited by 1 · see citing works
Erişti, S. D. B., & Belet, Ş. D. (2010) · DergiPark (Istanbul University) · doi:10.17569/tojqi.60271 · Cited by 1 · see citing works
Algarni, A. (2013) · Research Online (University of Wollongong) · Cited by 1 · see citing works
Effectiveness of Artistic Interaction through Video Conferencing
Erişti, S. D. B. (2011) · DergiPark (Istanbul University) · doi:10.17569/tojqi.13390
“In addition, video-conferencing systems allow transmitting interaction and different experiences between different educational settings with the help of rich communication tools (Motamedi, 2001; Renkl & Atkinson, 2002;Greenberg & Nilssen, 2005).”
BackgroundFakultät, P., & Humanwissenschaften, E. (2015)
Investigating the Use of Anchoring for Promoting Design Thinking.
Dasgupta, C. (2018)
Mayer, R. E., & Fiorella, L. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108894333.002 · Cited by 1 · see citing works
Pädagogische Psychologie des Erwachsenenalters
Spörer, N., & Brunstein, J. C. (2006) · Springer eBooks · doi:10.1007/3-540-37637-2_50
- Authors
- Renkl, A., & Atkinson, R. K.
- ORCID
- Renkl, Alexander
- Venue
- Interactive Learning Environments
- Publisher
- Informa UK Limited
- Published
- 2002-08
- Volume
- 10
- Issue
- 2
- Pages
- 105-119
- ISSN
- 1049-4820 (ISSN-L)
- 1744-5191
- OpenAlex
- W2019387838
- Cited by
- 74
- References
- 0
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 3 · 2022: 1 · 2021: 3 · 2020: 4 · 2019: 1 · 2018: 5 · 2017: 2 · 2016: 6 · 2015: 6 · 2014: 6 · 2013: 9 · 2012: 3
- FWCI
- 1.92
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Interactive Learning Environments (publishedVersion)
- FreiDok plus (Universitätsbibliothek Freiburg) (submittedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Keywords
- self-explanation, worked examples, computer-based learning environments, instructional explanations, problem solving, lifelong learning, video-based learning
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