An Extension of the Levenshtein Distance for Learning Process Analysis in Constructive Learning and an Evaluation of its Effectiveness

In this study, we propose an applied extension of the Levenshtein distance for analyzing learning logs in constructive programming learning. By incorporating the influence of blank and dummy cards—which conventional distance metrics fail to adequately capture—our method enables a more detailed evaluation of the quality of learners’ trial-and-error processes and the presence or absence of logical thinking. This approach clarifies the distinction between exhaustive trial behaviors and logically constructed problem-solving, thereby contributing to learning support systems that can provide more personalized and appropriate feedback.

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Publication Details

Journal
IIAI Letters on Business and Decision Science
Published
2025-01-01
DOI
https://doi.org/10.52731/lbds.v005.474
Primary Topic
Spreadsheets and End-User Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

An Extension of the Levenshtein Distance for Learning Process Analysis in Constructive Learning and an Evaluation of its Effectiveness

Kazuo Yagami, Shimpei Matsumoto, Natsumi Tanabe
IIAI Letters on Business and Decision Science
Spreadsheets and End-User Computing
article

An Extension of the Levenshtein Distance for Learning Process Analysis in Constructive Learning and an Evaluation of its Effectiveness

Kazuo Yagami, Shimpei Matsumoto, Natsumi Tanabe
article en

Abstract

In this study, we propose an applied extension of the Levenshtein distance for analyzing learning logs in constructive programming learning. By incorporating the influence of blank and dummy cards—which conventional distance metrics fail to adequately capture—our method enables a more detailed evaluation of the quality of learners’ trial-and-error processes and the presence or absence of logical thinking. This approach clarifies the distinction between exhaustive trial behaviors and logically constructed problem-solving, thereby contributing to learning support systems that can provide more personalized and appropriate feedback.

IIAI Letters on Business and Decision ScienceVol. 5
Hiroshima Institute of Technology (JP)
Japan Society for the Promotion of Science
Openalex Percentile: Top 66%
Spreadsheets and End-User Computing
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