| Abstract |
| This study reconceptualizes university course evaluation as a composite signal reflecting students’ academic experiences and emotional states and examines the applicability of this perspective to academic dropout management. Course evaluation scores and dropout rates at D University were collected and analyzed over a three-year period (2022-2024). An importance-performance analysis was then employed to classify departments into four quadrants and identify distinct patterns of academic dropout risk. The results indicate a statistically significant negative correlation between course evaluation scores and dropout rates across all academic years, reflecting a meaningful association between students’ perceptions of instruction quality and academic persistence. The classification further reveals distinct characteristics for each quadrant, implying that dropout risk emerges through different combinations of factors both related and unrelated to instruction. Departments with high course evaluation scores and low dropout rates represent stable cases that can serve as exemplary models for institutional dissemination. These departments appeared to be influenced primarily by factors such as students’ overall academic burden or difficulties adapting to university life. Meanwhile, departments exhibiting low course evaluation scores and high dropout rates require comprehensive institutional interventions encompassing teaching practices, departmental management, and student support systems. In contrast, departments with both low course evaluation scores and relatively low dropout rates indicated that improving teaching and learning processes could effectively prevent increases in academic attrition. These findings demonstrate that course evaluation data can function as a practical diagnostic tool for identifying department-level dropout risk and designing differentiated intervention strategies without the need for complex learning analytics. By extending the interpretive scope of course evaluations beyond instructional assessment, this paper offers actionable implications for enhancing student retention strategies and advancing data-informed academic management in higher education. |
|
|
| Key Words |
| 강의평가, 중도 탈락률, IPA형 연계 분석, 학업 중단, 관리 전략 방향, Course Evaluation, Dropout Rate, IPA-Type Linkage Analysis, Dropout, Management Strategic Direction |
|
|
 |
|
