Evaluation of the Teaching Effect in the Context of Collective Lesson Preparation

Now in the field of education, the pedagogy of learning from the experience of expert teachers which is participated by multiple parties and emphasizes on practicality has received the attention of field scholars, and they also began to attach importance to the cooperative features and scenarios of the Collective Lesson Preparation (CLP) of teachers and the effect of teaching reflection after practice. In order to realize sustainable and effective development of the CLP methodology, it’s necessary to accurately evaluate the effect of teaching reflection of college teachers based on CLP, therefore, this paper aims to probe deep into this research topic. At first, this paper analyzed the features of CLP in actual cases, attained the connotations corresponding to these features, and gave a diagram showing the instruction and supervision mechanism of CLP. Then, referring to existing literatures and theoretical frameworks, this paper designed an Evaluation Index System (EIS) for the teaching reflection effect evaluation of college teachers based on CLP, and introduced a Back Propagation Neural Network (BPNN) into the prediction of teaching reflection effect evaluation of college teachers; after that, this paper employed Particle Swarm Optimization (PSO) to optimize the initial weight and threshold of the network, so as to improve the performance of the prediction model; at last, experimental results proved the effectiveness of the proposed model.