Affiliations: [a] Institute of Vocational Education, Tongji University, Shanghai, China
| [b] School of Economics and Management, Tongji University, Shanghai, China
Correspondence:
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Corresponding author. Jianjun Zhang, School of Economics and Management, Tongji University, Shanghai, China. E-mail: [email protected].
Abstract: In the Big-data Era, the construction of precise personalized learning evaluation system forms an important part of analyzing learners’ learning behavior and predicting precise personalized learning performance. The CIPP evaluation model is introduced into the precise personalized learning evaluation, and 3 first-level indicators, 9 second-level indicators and 25 third-level indicators are designed to evaluate the learning process in terms of pre-class preview, in-class teaching and after-class consolidation. And then through the application of questionnaire survey, AHP method and fuzzy comprehensive evaluation method, the indicators are condensed and weighted, and the corresponding fuzzy comprehensive judgment matrix is figured out. Finally, a learning evaluation system for the whole process of precise personalized learning is constructed. An empirical study based on the learning behavior data of a certain number of online learners is carried out to test the value and feasibility of this learning evaluation system.
