Identifying At-Risk Factors of a College Course in Blended Mode and a Case Study

Abstract

A framework was proposed to identify the at-risk factors of college courses in blended mode, offering suggestions for continuous improvement. An indicator system concerning teaching quality characteristics was constructed based on context, input, process, and product (CIPP) model. Subsequently, the group Analytic Hierarchy Process (AHP) algorithm was employed to assign weights to each indicator. Notably, the approach for assessing the consistency of the judgment matrix was improved, with a focus on preserving the initial judgments of the experts to the greatest extent. Finally, results were computed using a fuzzy comprehensive evaluation. Continuous improvements were suggested to enhance the teaching quality of the course and improve student learning outcomes. A typical case study was presented to illustrate the detailed process of the proposed framework. The evaluation results demonstrate its potential as a new tool for understanding blended teaching mode and enhancing learning outcomes across various college courses.