Cited by 20Intelligent Tutoring Systems and Adaptive LearningVisual and Cognitive Learning ProcessesInnovative Teaching and Learning Methods

When and Why Does Mastery Learning Work: Instructional Experiments with ACT-R “SimStudents”

MacLaren, Benjamin, Koedinger, Kenneth·2002·Lecture Notes in Computer Science

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Crossref · 10.1007/3-540-47987-2_39

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  • Providing and eliciting explanations may be critical to help learners break down or externalize the complex inference needed when processing negative feedback to fully identify all the KCs and integrative KCs in a reasoning chain and to revise any KCs that are not correct as part of that chain.

    “Providing and eliciting explanations may be critical to help learners break down or externalize the complex inference needed when processing negative feedback to fully identify all the KCs and integrative KCs in a reasoning chain and to revise any KCs that are not correct as part of that chain (cf.MacLaren & Koedinger, 2002).”

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Authors
MacLaren, B., & Koedinger, K.
Affiliations
Carnegie Mellon University (US)
Venue
Lecture Notes in Computer Science
Published
2002
Pages
355-366
ISSN
0302-9743 (ISSN-L)
OpenAlex
W2136070270
Cited by
20
References
0
Citations by year
2025: 1 · 2022: 1 · 2019: 1 · 2018: 1 · 2017: 1 · 2016: 1 · 2015: 2 · 2014: 1 · 2013: 1 · 2012: 1
FWCI
1.36
Type
conference paper
Language
en
Open access
closed
Locations
Lecture notes in computer science (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
  • Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
Keywords
learning mastery, simulated students, instructional design, skill decomposition, verbal problem solving

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