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Evidence and Theory for Why the Best Example-Problem Ratio to Optimize Learning Gain Depends on Knowledge Content

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Title: Evidence and Theory for Why the Best Example-Problem Ratio to Optimize Learning Gain Depends on Knowledge Content
Language: English
Authors: Napol Rachatasumrit (ORCID 0000-0002-7183-8789), Kenneth R. Koedinger (ORCID 0000-0002-5850-4768), Paulo F. Carvalho (ORCID 0000-0002-0449-3733)
Source: International Journal of Artificial Intelligence in Education. 2025 35(6):3645-3667.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 23
Publication Date: 2025
Sponsoring Agency: National Science Foundation (NSF)
Contract Number: 1824257
2301130
Document Type: Journal Articles
Reports - Research
Descriptors: Computation, Testing, Memory, Learning Processes, Prediction, Skill Development
DOI: 10.1007/s40593-025-00511-8
ISSN: 1560-4292
1560-4306
Abstract: Many experiments have demonstrated that more practice testing and less studying of examples produces better learning whereas other experiments show the opposite, that more example study and less practice produces better learning. We present empirical and computational evidence that resolves and explains this apparent inconsistency. We show how a practice testing instructional treatment supports memory learning processes needed for verbatim fact content whereas an example-integrated instructional treatment supports inductive learning processes needed for general skill content. In an experiment comparing both instructional treatments on both types of content, we observe a cross-over interaction such that participants learn verbatim facts better from pure practice testing but learn general skills better from example-integrated practice. We use a computational learning architecture, AL, to create an executable theory that explains and predicts these results. Simulated students developed in AL interactively learn from the materials provided in the same four conditions as human learners and reproduce the same cross-over interaction. We further demonstrate that the benefits of integrated examples for general skill learning are a result of, and thus explained by, AL's inductive learning mechanisms whereas the benefit of practice for verbatim fact learning result from AL's memory learning mechanisms.
Abstractor: As Provided
Notes: https://osf.io/29wpe
Entry Date: 2026
Accession Number: EJ1500063
Database: ERIC
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  Data: <searchLink fieldCode="AR" term="%22Napol+Rachatasumrit%22">Napol Rachatasumrit</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-7183-8789">0000-0002-7183-8789</externalLink>)<br /><searchLink fieldCode="AR" term="%22Kenneth+R%2E+Koedinger%22">Kenneth R. Koedinger</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-5850-4768">0000-0002-5850-4768</externalLink>)<br /><searchLink fieldCode="AR" term="%22Paulo+F%2E+Carvalho%22">Paulo F. Carvalho</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-0449-3733">0000-0002-0449-3733</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22International+Journal+of+Artificial+Intelligence+in+Education%22"><i>International Journal of Artificial Intelligence in Education</i></searchLink>. 2025 35(6):3645-3667.
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
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  Data: Many experiments have demonstrated that more practice testing and less studying of examples produces better learning whereas other experiments show the opposite, that more example study and less practice produces better learning. We present empirical and computational evidence that resolves and explains this apparent inconsistency. We show how a practice testing instructional treatment supports memory learning processes needed for verbatim fact content whereas an example-integrated instructional treatment supports inductive learning processes needed for general skill content. In an experiment comparing both instructional treatments on both types of content, we observe a cross-over interaction such that participants learn verbatim facts better from pure practice testing but learn general skills better from example-integrated practice. We use a computational learning architecture, AL, to create an executable theory that explains and predicts these results. Simulated students developed in AL interactively learn from the materials provided in the same four conditions as human learners and reproduce the same cross-over interaction. We further demonstrate that the benefits of integrated examples for general skill learning are a result of, and thus explained by, AL's inductive learning mechanisms whereas the benefit of practice for verbatim fact learning result from AL's memory learning mechanisms.
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  Data: https://osf.io/29wpe
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