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Content Optimization of Teaching Evaluation Scale for College Teachers with Emerging of Artificial Intelligence: A Case Study
- 1 University of Macau
- 2 Xi'an Jiaotong University
- 3 Fu'jian Normal University
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Abstract
This paper uses the Teacher Evaluation Scale for Higher Education Teachers in the Context of Artificial Intelligence (AI) as the basis for problem elucidation and explores AI-induced changes in teaching and learning through the medium of evaluation. Teachers’ roles need to be more comprehensive and flexible than in the past to cope with the diversified teaching under the participation of AI; teachers need to insist on and continuously improve their humanistic qualities to answer to the higher spiritual needs of students; while using AI to assist in teaching, teachers need to keep abreast of the development, and control the limit of students’ use, to avoid the indiscriminate use of AI caused by the eyeless worship. Teaching should use science and technology to discover more methods of knowledge transfer, showing students the details of knowledge application and providing students with a platform for high-level exchanges; Learning practice cannot be replaced by AI, which should become the practice of the assistant rather than a replacement. Current evaluation scales need to be more refined and precise for teachers and teachers and provide effective measures to deal with the educational problems of AI.
Keywords
teacher evaluation, teaching relationship, artificial intelligence
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Cite this article
Cai,W.;Cui,C.;Xu,S. (2023). Content Optimization of Teaching Evaluation Scale for College Teachers with Emerging of Artificial Intelligence: A Case Study. Lecture Notes in Education Psychology and Public Media,24,38-46.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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