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| Construction and Empirical Analysis of Data-Driven Precision Blended Instruction Model |
| WANG Weina
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| School of Science, Jilin Institute of Chemical Technology, Jilin 132022, China |
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Abstract To deepen the integration and development of big data technology in the field of higher education, the research takes the promotion of the reform of higher education and high-quality education as the core engine, and takes advantage of the data of the whole process of students' learning and the theory of precision teaching, hybrid teaching and data-driven theories. Based on the above considerations, a data-driven precision blended learning model is constructed. The model integrates the advantages of "online" and "offline" teaching. Starting from the four parts: teaching objectives, pre-class preparation, teaching process, and teaching evaluation and prediction, it focuses on the operational framework and implementation path of precise blended learning to achieve intelligent, personalized, refined and scientific blended learning. In the practical verification of the "Advanced Mathematics" course in higher vocational education, comparing blended learning with traditional teaching methods from multiple dimensions such as teaching effectiveness, learning ability, and academic performance, it is shown that the effectiveness and superiority of precise blended learning mode can promote the high-quality development of higher vocational education comprehensively.
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Published: 25 April 2024
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