Proceedings of the 2026 6th International Conference on Education, Information Management and Service Science (EIMSS 2026)

2026 6th International Conference on Education, Information Management and Service Science (EIMSS 2026)

šŸ“Kuala Lumpur, MalaysiašŸ—“ļø 3-5 July 2026
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Knowledge Internalization Mechanisms in the Feynman Technique

Authors
Yan Zhao1, *
1School of Mathematics and Computer Science, Northwest Minzu University, Lanzhou, 730030, China
*Corresponding author. Email: 576610836@qq.com
Corresponding Author
Yan Zhao
Available Online 4 September 2026.
DOI
10.2991/978-94-6239-766-8_37How to use a DOI?
Keywords
Feynman technique; Knowledge internalization; Learning by teaching; Feedback; Computer experimental education
Abstract

The Feynman technique is often summarized as learning by explaining, but this formula leaves the internal process unclear. This study analyzes a CNKI export of 238 records and retains 156 journal articles from 2017 to June 2026 in which the technique appears in the title or keywords. Descriptive counts and title-abstract-keyword coding identify six recurring dimensions: practice and transfer, knowledge reconstruction, explanation, feedback and diagnosis, collaboration, and digital or AI support. The evidence base is uneven: 93 articles propose a model, 86 report practice-based evaluation, and 42 mention quantitative or comparative evidence. The synthesis defines internalization as a six-stage cycle of selection, reconstruction, explanation, diagnosis, revision, and transfer. For computer experimental education, explanations should be linked to executable procedures, observable data, and repeatable verification.

Copyright
Ā© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2026 6th International Conference on Education, Information Management and Service Science (EIMSS 2026)
Series
Atlantis Highlights in Computer Sciences
Publication Date
4 September 2026
ISBN
978-94-6239-766-8
ISSN
2589-4900
DOI
10.2991/978-94-6239-766-8_37How to use a DOI?
Copyright
Ā© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Yan Zhao
PY  - 2026
DA  - 2026/09/04
TI  - Knowledge Internalization Mechanisms in the Feynman Technique
BT  - Proceedings of the 2026 6th International Conference on Education, Information Management and Service Science  (EIMSS 2026)
PB  - Atlantis Press
SP  - 357
EP  - 362
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6239-766-8_37
DO  - 10.2991/978-94-6239-766-8_37
ID  - Zhao2026
ER  -