Jul 2026· Asian Journal of Education and Social Studies· Vol 52, pp. 1002-1012· 0 citations
TL;DR
The findings indicate that the integrated model was accompanied by improved attainment, performance, and satisfaction across the two cohorts, however, because the evaluation involved successive cohorts from one course and did not include individual-level statistical testing, the results should be interpreted as course-specific descriptive evidence.
Abstract
This study developed and evaluated an integrated teaching model for Computer Control Technology within the framework of New Engineering Education. A descriptive comparison was conducted between two consecutive cohorts of third-year mechatronic engineering students at Tianjin University of Technology during the first semesters of the 2024–2025 and 2025–2026 academic years. Each cohort comprised 72 students and was taught by the same instructor under consistent course hours, assessment weights, examination difficulty, and marking standards. The course was reorganised into basic, advanced, and integrated modules, with outcome-based objectives aligned with project- and case-based learning, virtual simulation, embedded implementation, physical verification, debugging, and engineering communication. Learning-outcome attainment, course-performance indicators, and student-satisfaction ratings were compared descriptively. Mean learning-outcome attainment increased from 0.70 to 0.86, while the overall course score increased from 77.7 to 89.3. The excellent rate rose from 12.5% to 27.8%, and the pass rate increased from 87.5% to 97.2%. Mean student satisfaction increased from 3.61 to 4.39, with the largest relative gain observed for virtual simulation support. The findings indicate that the integrated model was accompanied by improved attainment, performance, and satisfaction across the two cohorts. However, because the evaluation involved successive cohorts from one course and did not include individual-level statistical testing, the results should be interpreted as course-specific descriptive evidence.
The effectiveness of the proposed framework was evaluated through Course Outcome (CO) and Program Outcome (PO) attainment analysis, performance-based assessment rubrics, and machine learning classification models. The results demonstrated improved attainment of key COs and POs related to problem-solving, system design,...
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