Year: 2025
Type: conference-paper
Abstract: With the continuous progress of digital education construction, the reform of higher education has gradually entered the deep water area. In this process, the evaluation of teachers' teaching ability is not only related to the teaching quality of the school, but also a powerful engine to promote teachers' professional development. However, there are many shortcomings in the scientific, accurate and adaptive evaluation methods of teachers' teaching ability adopted in colleges and universities at this stage, which are difficult to meet the practical application needs of colleges and universities. This paper will analyze the current situation, deeply explore the feasibility of text data mining analysis technology in this field, and put forward a set of teachers' teaching ability analysis model based on multiple evaluation, in order to provide new methods and new ideas for the evaluation of teachers' teaching ability in colleges and universities. Practice has proved that the model processes unstructured data such as students' teaching evaluation texts and teachers' teaching logs through Word2Vec and LDA models, and mines the potential information in them to provide a more comprehensive basis for evaluation. At the same time, the fuzzy comprehensive evaluation method is used to calculate the set of multiple evaluation scores, so as to comprehensively and objectively reflect teachers' teaching ability and provide strong support for teachers' professional development and teaching management in colleges and universities.
Authors: Liying Yan, Yu Li
Institution: Weifang Engineering Vocational College
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
OpenAlex ID: W4413985064