Research Article
Mobile Teaching Quality Evaluation Model of Industry-University-Research Education Based on Data Mining
@INPROCEEDINGS{10.1007/978-3-031-28867-8_23, author={Yanbin Tang}, title={Mobile Teaching Quality Evaluation Model of Industry-University-Research Education Based on Data Mining}, proceedings={Advanced Hybrid Information Processing. 6th EAI International Conference, ADHIP 2022, Changsha, China, September 29-30, 2022, Proceedings, Part II}, proceedings_a={ADHIP PART 2}, year={2023}, month={3}, keywords={Data mining Industry-University-Research education Mobile teaching Teaching quality evaluation}, doi={10.1007/978-3-031-28867-8_23} }- Yanbin Tang
Year: 2023
Mobile Teaching Quality Evaluation Model of Industry-University-Research Education Based on Data Mining
ADHIP PART 2
Springer
DOI: 10.1007/978-3-031-28867-8_23
Abstract
Teaching quality is the main indicator for evaluating teaching level. But it is affected by a number of contributing variables. To address existing issues in teaching quality evaluation and boost the accuracy of teaching quality evaluation, a data mining-based teaching quality assessment model is developed. To begin, this model investigates and analyzes the relevant literature on the present evaluation of teaching quality, generate evaluation indicators of factors affecting teaching quality, and gathers data on teaching quality influencing factors. And creates research samples for evaluating teaching quality at schools of higher education as well as determines the grade of educational effectiveness through specialists. And applies data mining technology to train study samples, forming the model of university teaching quality assessment. Analyzes the superiority of the college and university teaching quality model using real instances. The results reveal that data mining can represent the disparities in quality of instruction grades in universities and produce high accuracy quality of instruction assessment results.
