An effective metacognitive strategy: learning by doing and explaining with a computer‐based Cognitive Tutor
Abstract
Recent studies have shown that self‐explanation is an effective metacognitive strategy, but how can it be leveraged to improve students' learning in actual classrooms? How do instructional treatments that emphasizes self‐explanation affect students' learning, as compared to other instructional treatments? We investigated whether self‐explanation can be scaffolded effectively in a classroom environment using a Cognitive Tutor, which is intelligent instructional software that supports guided learning by doing. In two classroom experiments, we found that students who explained their steps during problem‐solving practice with a Cognitive Tutor learned with greater understanding compared to students who did not explain steps. The explainers better explained their solutions steps and were more successful on transfer problems. We interpret these results as follows: By engaging in explanation, students acquired better‐integrated visual and verbal declarative knowledge and acquired less shallow procedural knowledge. The research demonstrates that the benefits of self‐explanation can be achieved in a relatively simple computer‐based approach that scales well for classroom use.
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A mathematical model of Aleven and Koedinger's data provides evidence that non-verbal procedural and verbal declarative knowledge of the same content can co-exist and that different mixtures of such knowledge can yield identifiable patterns of performance across multiple assessments.
“A mathematical model of their data provides evidence that non-verbal procedural and verbal declarative knowledge of the same content can co-exist and that different mixtures of such knowledge can yield identifiable patterns of performance across multiple assessments.”
From The Knowledge‐Learning‐Instruction Framework: Bridging the Science‐Practice Chasm to Enhance Robust Student Learning (2012) · cites this paper as Aleven and Koedinger (2002)
Aleven and Koedinger (2002) provide evidence of non-verbal procedural knowledge in geometry students who were more correct on making geometric inferences than on matched explanation items.
“Aleven and Koedinger (2002) provide evidence of non-verbal procedural knowledge in the performance of geometry students who were more correct on making geometric inferences than they were on matched explanation items.”
From The Knowledge‐Learning‐Instruction Framework: Bridging the Science‐Practice Chasm to Enhance Robust Student Learning (2012) · cites this paper as Aleven and Koedinger (2002)
Adding prompts for self-explanation to tutored problem solving practice, without adding extra instructional time, produced greater explanation ability and conceptual transfer to novel problems while maintaining performance on isomorphic problems.
“They found that adding prompts for self-explanation to tutored problem solving practice (without adding extra instructional time) produced greater explanation ability and conceptual transfer to novel problems while maintaining performance on isomorphic problems.”
From The Knowledge‐Learning‐Instruction Framework: Bridging the Science‐Practice Chasm to Enhance Robust Student Learning (2012) · cites this paper as Aleven and Koedinger (2002)
Much research on self-explanation indicates that prompting students to provide verbal explanations of actions, whether their own or ones given in a worked example, can often aid robust learning.
“Much research on “self-explanation” indicates that prompting students to provide verbal explanations of actions (whether their own or ones given in a worked example) can often aid robust learning (Aleven & Koedinger, 2002;Chi et al., 1994;Graesser, McNamara, & VanLehn, 2005;Hausmann & VanLehn, 2007).”
From The Knowledge‐Learning‐Instruction Framework: Bridging the Science‐Practice Chasm to Enhance Robust Student Learning (2012) · cites this paper as Aleven & Koedinger, 2002
In geometry, many students implicitly induce a rule that when angles look equal in a diagram, they are equal.
“In geometry, many students (implicitly) induce a rule that when angles look equal in a diagram, they are equal (Aleven & Koedinger, 2002).”
From The Knowledge‐Learning‐Instruction Framework: Bridging the Science‐Practice Chasm to Enhance Robust Student Learning (2012) · cites this paper as Aleven & Koedinger, 2002
Non-verbal induction can lead to a situation in which students can correctly perform mathematics that they cannot explain.
“Non-verbal induction can lead to a situation in which students can correctly perform mathematics (e.g., find a correct angle in a geometry problem by subtracting from 180°) that they cannot explain (e.g., indicating that the target and given angle form a line; Aleven & Koedinger, 2002).”
From The Knowledge‐Learning‐Instruction Framework: Bridging the Science‐Practice Chasm to Enhance Robust Student Learning (2012) · cites this paper as Aleven & Koedinger, 2002
Integrated variable-variable KCs to be learned in both non-verbal procedural and verbal declarative form imply instruction that prompts for self-explanations.
“Integrated variable-variable KCs to be learned in both non-verbal procedural and verbal declarative form (e.g., math and science principles) imply instruction that prompts for selfexplanations (Aleven & Koedinger, 2002).”
From The Knowledge‐Learning‐Instruction Framework: Bridging the Science‐Practice Chasm to Enhance Robust Student Learning (2012) · cites this paper as Aleven & Koedinger, 2002
Prompting students to self-explain each step of a worked example or each line of a text usually causes higher learning gains than having them study the material without such prompting.
“When students are given a worked example or text to study, prompting them to self-explain each step of the worked example or each line of the text usually causes higher learning gains than having them study the material without such prompting (e.g., Aleven & Koedinger, 2002;Chi, de Leeuw, Chiu, & LaVancher, 1994;Renkl, Stark, Gruber, & Mandl, 1998), but exceptions are discussed below.”
From The Knowledge‐Learning‐Instruction Framework: Bridging the Science‐Practice Chasm to Enhance Robust Student Learning (2012) · cites this paper as Aleven & Koedinger, 2002
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- Authors
- Aleven, V. A. W. M. M., & Koedinger, K. R.
- Affiliations
- Carnegie Mellon University (US)
- Corresponding author
- Aleven, Vincent A.W.M.M.
- Venue
- Cognitive Science
- Publisher
- Wiley
- Published
- 2002-03
- Volume
- 26
- Issue
- 2
- Pages
- 147-179
- ISSN
- 0364-0213 (ISSN-L)
- 1551-6709
- OpenAlex
- W2104882621
- Cited by
- 895
- References
- 1
- Citations by year
- 2026: 13 · 2025: 29 · 2024: 31 · 2023: 34 · 2022: 25 · 2021: 39 · 2020: 30 · 2019: 30 · 2018: 42 · 2017: 47 · 2016: 42 · 2015: 53 · 2014: 43 · 2013: 59 · 2012: 60
- FWCI
- 31.49
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Cognitive Science (publishedVersion)
- 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, metacognition, cognitive tutors, intelligent tutoring systems, hands-on learning, problem solving, transfer of learning, declarative knowledge, procedural knowledge, scaffolding, classroom teaching
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