基于离散Hopfield神经网络的高校教师教学能力评价研究

Research on the Evaluation of University Teachers' Teaching Ability Based on Discrete Hopfield Neural Network

教学能力在高校发展中占据核心地位,对高校教师教学能力的评价研究对高校自身的完善具有重要的指导意义。针对当前高校教师教学能力评价体系存在影响因素繁多、关联复杂、公正性缺失等诸多问题,基于我国高校的教学特点,构建高校教学能力综合评价指标体系;在引入隐性评价指标反馈机制的基础上,阐述基于离散Hopfield神经网络的高校教学能力评价模型的基本思想及步骤。

Teachers＇ teaching ability plays a crucial role in the development of university; research on evaluation of teaching ability has the important guidance significance to the university self-improvement. As the current evaluation system consists of many disadvantages including many influential factors, complicated relationship and lack of fairness, proposes a comprehensive evaluation index system for teacher＇s teaching ability of university on the basis of the teaching characteristics of universities. Then, on the basis of introducing the feedback mechanism of recessive evaluation index, expounds the basic idea and steps of the evaluation model of university teaching ability based on discrete Hop- field neural network.