Construction of computer-aided teaching effect evaluation index system in the development of PCK for physical education teachers

With the rapid advancement of information technology, education, particularly Computer-Assisted Instruction (CAI), has undergone significant transformation. CAI improves teaching efficiency, enhances educational content, and promotes student-teacher interaction while fostering students’ autonomous learning abilities. Despite its widespread adoption, the effectiveness of CAI varies depending on the implementation context. Evaluating CAI’s impact has become a critical challenge in educational reform. This study developed a comprehensive evaluation framework to assess the effectiveness of Computer-Assisted Instruction (CAI) by integrating the Analytic Hierarchy Process (AHP) with Fuzzy Comprehensive Evaluation (FCE) methods, providing a multidimensional approach for understanding technology-enhanced physical education teaching methods. The evaluation system covers multiple dimensions, including the teaching process, student learning outcomes, and resource availability. Using AHP, the importance of each factor is weighted, and the FCE method quantifies the data to derive an overall effectiveness score. The research highlights the need for a comprehensive evaluation system as previous studies often rely on qualitative analysis or single metrics. By adopting a multidimensional, quantitative approach, this study offers a more robust and scientifically grounded method for assessing CAI. The findings suggest that while CAI is effective in enhancing teaching outcomes, its success is contingent on resource availability and the technical capabilities of both teachers and students. This research provides valuable insights for educators and policymakers aiming to optimize CAI implementations and enhance the quality of education through better technological integration.

Authors

Institutions

Publication Details

Journal
Journal of Computational Methods in Sciences and Engineering
Published
2025-10-22
DOI
https://doi.org/10.1177/14727978251391319
Primary Topic
Educational Technology and Pedagogy
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Construction of computer-aided teaching effect evaluation index system in the development of PCK for physical education teachers

Juncai Zhi, Yongsong Huang, Q. J. Yao, Ruijie Zhang
Journal of Computational Methods in Sciences and Engineering
Educational Technology and Pedagogy
article

Construction of computer-aided teaching effect evaluation index system in the development of PCK for physical education teachers

Juncai Zhi, Yongsong Huang, Q. J. Yao, Ruijie Zhang
article en

Abstract

With the rapid advancement of information technology, education, particularly Computer-Assisted Instruction (CAI), has undergone significant transformation. CAI improves teaching efficiency, enhances educational content, and promotes student-teacher interaction while fostering students’ autonomous learning abilities. Despite its widespread adoption, the effectiveness of CAI varies depending on the implementation context. Evaluating CAI’s impact has become a critical challenge in educational reform. This study developed a comprehensive evaluation framework to assess the effectiveness of Computer-Assisted Instruction (CAI) by integrating the Analytic Hierarchy Process (AHP) with Fuzzy Comprehensive Evaluation (FCE) methods, providing a multidimensional approach for understanding technology-enhanced physical education teaching methods. The evaluation system covers multiple dimensions, including the teaching process, student learning outcomes, and resource availability. Using AHP, the importance of each factor is weighted, and the FCE method quantifies the data to derive an overall effectiveness score. The research highlights the need for a comprehensive evaluation system as previous studies often rely on qualitative analysis or single metrics. By adopting a multidimensional, quantitative approach, this study offers a more robust and scientifically grounded method for assessing CAI. The findings suggest that while CAI is effective in enhancing teaching outcomes, its success is contingent on resource availability and the technical capabilities of both teachers and students. This research provides valuable insights for educators and policymakers aiming to optimize CAI implementations and enhance the quality of education through better technological integration.

Journal of Computational Methods in Sciences and Engineering
Tangshan Normal University (CN), Baoding University (CN), Hezhou University (CN), Hebei Normal University (CN)
Openalex Percentile: Top 84%
Educational Technology and Pedagogy
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.