Productive failure in learning from generation and invention activities
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The number and diversity of student-generated Representation and Solution Methods (RSMs) is a strong predictor of learning gains with PF.
“The number of RSMs generated is one of the best predictors of how much students learn from PF (Kapur and Rummel, 2012).”
From Towards the Pedagogical Steering of Large Language Models for Tutoring: A Case Study with Modeling Productive Failure (2025) · cites this paper as Kapur and Rummel, 2012
The Constituent papers section (page not provided) reports that the diversity of student-generated RSMs was significantly correlated with how much students learned from PF. It does not establish that the number of RSMs was one of the best predictors of learning. (LLM, conf=0.86)
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Cites
Kirschner, P. A., Sweller, J., & Clark, R. E. (2006) · Educational Psychologist · doi:10.1207/s15326985ep4102_1 · Cited by 6,887 · see citing works
Schmidt, R. A., & Bjork, R. A. (1992) · Psychological Science · doi:10.1111/j.1467-9280.1992.tb00029.x · Cited by 1,582 · cited 3× · see citing works
“In contrast to productive success, the concept of productive failure (PF), much as it is intuitively compelling, remains largely underdetermined and under-researched (Clifford 1984; Schmidt and Bjork 1992).”
BackgroundDesigning for Productive Failure
Kapur, M., & Bielaczyc, K. (2012) · Journal of the Learning Sciences · doi:10.1080/10508406.2011.591717 · Cited by 674 · cited 6× · see citing works
“Moreover, they shed light on the role of factors that support student generation and exploration of RSMs such as collaborative role scripts (Westermann and Rummel 2012), metacognitive prompts (Roll et al. 2012), and abilitybased group composition (Wiedmann et al. 2012).”
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Flagged first, then by citations
Research works printed but not linked: 21
- Clifford, M. M. (1984). Thoughts on a theory of constructive failure. Educational Psychologist, 19(2), 108-120.
- Kapur, M. (2008). Productive failure. Cognition and Instruction, 26(3), 379-424.
- Kapur, M. (2010). Productive failure in mathematical problem solving. Instructional Science, 38(6), 523-550.
- Kapur, M. (2011). A further study of productive failure in mathematical problem solving: Unpacking the design components. Instructional Science, 39(4), 561-579.
- Kapur, M. (2012). Productive failure in learning the concept of variance. Instructional Science. doi: 10.1007/s11251-012-9209-6. · DOI
- Kapur, M., & Kinzer, C. (2009). Productive failure in CSCL groups. International Journal of Computer- Supported Collaborative Learning, 4, 21-46.
- Kapur, M., & Rummel, N. (2009). The assistance dilemma in CSCL. In A. Dimitracopoulou, C. O'Malley, D. Suthers, & P. Reimann (Eds.), Computer Supported Collaborative Learning practices-CSCL2009 community events proceedings (Vol. 2, pp. 37-42). New Brunswick: International Society of the Learning Sciences.
- Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work. Educational Psychologist, 41(2), 75-86.
- Needham, D. R., & Begg, I. M. (1991). Problem-oriented training promotes spontaneous analogical transfer: Memory-oriented training promotes memory for training. Memory and Cognition, 19(6), 543-557.
- Puntambekar, S., & Hu ¨bscher, R. (2005). Tools for scaffolding students in complex learning environments: What have we gained and what have we missed. Educational Psychologist, 40(1), 1-12.
- Richland, L. E., Kornell, N., & Kao, L. S. (2009). The pretesting effect: Do unsuccessful retrieval attempts enhance learning? Journal of Experimental Psychology: Applied, 15(3), 243-257. doi:10.1037/ a0016496. · DOI · Paper page
- Roll, I., Holmes, N. G., Day, J., & Bonn, D. (2012). Evaluating metacognitive scaffolding in guided invention activities. Instructional Science. doi:10.1007/s11251-012-9208-7. · DOI
- Schmidt, H. G., Loyens, S. M. M., van Gog, T., & Paas, F. (2007). Problem-based learning is compatible with human cognitive architecture: Commentary on Kirschner, Sweller, and Clark (2006). Educational Psychologist, 42(2), 91-97.
- Schwartz, D. L., & Bransford, J. D. (1998). A time for telling. Cognition and Instruction, 16(4), 475-522.
- Schwartz, D. L., & Martin, T. (2004). Inventing to prepare for future learning: The hidden efficiency of encouraging original student production in statistics instruction. Cognition and Instruction, 22(2), 129-184.
- Strand-Cary, M., & Klahr, D. (2008). Developing elementary science skills: Instructional effectiveness and path independence. Cognitive Development, 23(4), 488-511. doi:10.1016/j.cogdev.2008.09.005. · DOI
- Sweller, J. (2010). What human cognitive architecture tells us about constructivism. In S. Tobias & T. M. Duffy (Eds.), Constructivist instruction: Success or failure (pp. 127-143). New York: Routledge.
- Tobias, S., & Duffy, T. M. (2009). Constructivist instruction: Success or failure. New York: Routledge.
- VanLehn, K., Siler, S., Murray, C., Yamauchi, T., & Baggett, W. B. (2003). Why do only some events cause learning during human tutoring? Cognition and Instruction, 2(3), 209-249.
- Westermann, K., & Rummel, N. (2012). Delaying instruction: Evidence from a study in a university relearning setting. Instructional Science. doi:10.1007/s11251-012-9207-8. · DOI
- Wiedmann, M., Leach, R. C., Rummel, N., & Wiley, J. (2012). Does group composition affect learning by invention? Instructional Science. doi:10.1007/s11251-012-9204-y. · DOI
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Self-citation
- Authors
- Kapur, M., & Rummel, N.
- Affiliations
- Nanyang Technological University (SG)
- Ruhr University Bochum (DE)
- Corresponding author
- Kapur, Manu
- Venue
- Instructional Science
- Published
- 2012-05-19
- Volume
- 40
- Issue
- 4
- Pages
- 645-650
- ISSN
- 0020-4277 (ISSN-L)
- 1573-1952
- OpenAlex
- W2007901903
- Cited by
- 87
- References
- 3
- Citations by year
- 2026: 8 · 2025: 9 · 2024: 4 · 2023: 3 · 2022: 4 · 2021: 4 · 2020: 8 · 2019: 11 · 2018: 9 · 2017: 3 · 2016: 6 · 2015: 10 · 2014: 4 · 2013: 3 · 2012: 1
- FWCI
- 7.72
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Instructional Science (publishedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Social Sciences › Education › Science Education and Pedagogy
- Keywords
- productive failure, generative learning, invention activity, learning versus performance, instructional design, worked examples, scaffolding, guided inquiry, cognitive load theory, long-term learning, problem-solving tasks
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