Abstract
More and more attention paid to the teaching quality of college, the assessment of the teaching quality is of great importance. Traditional teaching evaluation methods have a lot of deficiencies, not identifying what factors are really bound up with the quality of teaching. This paper applies the improved Apriori algorithm QApriori based on data mining technology to teaching evaluation model. On the foundation of data mining definition, mining processes, common data mining methods-Apriori and its improved algorithm-QApriori, this thesis emphasizes study on QApriori in the teaching evaluation model. Through the analysis of data mining, we have come to what factors are mainly related with the teaching quality, which will be very important to teaching and education policy-makers.
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© 2014 Springer Science+Business Media Dordrecht
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Qu, H., Li, X. (2014). Application of Data Mining in the Assessment of Teaching Quality. In: Li, S., Jin, Q., Jiang, X., Park, J. (eds) Frontier and Future Development of Information Technology in Medicine and Education. Lecture Notes in Electrical Engineering, vol 269. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7618-0_212
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DOI: https://doi.org/10.1007/978-94-007-7618-0_212
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