Deep Learning-Based Research on the Comprehensive Evaluation System for College Faculty Competence

The purpose of this work is to develop a set of comprehensive assessment criteria for the professionalism of college professors using a deep learning model. The importance of college instructors’ professionalism has grown as higher education has continued to improve. Traditional evaluation techniques sometimes only include subjective judgments or single indicators, making it challenging to accurately and impartially represent the whole quality of instructors. In order to provide a more thorough, impartial, and accurate assessment system for college professors, this research uses deep learning technology. In the research, instructors’ professionalism is thoroughly modeled and assessed by using a multi-level neural network structure. In comparison to conventional assessment techniques, the complete evaluation system based on deep learning can more accurately capture the prospective traits and skills of instructors and provide universities recommendations for hiring, preparing, and motivating new teachers.