Machine Learning Based Teaching Quality Evaluation

Abstract

Teaching quality is a key metric in college teaching effect and ability evaluation. In many previous literatures, evaluation of such metric is merely depended on subjective judgment of few experts based on their experience, which leads to some false, bias or unstable results. Moreover, pure human based evaluation is expensive that is difficult to extend to large scale. With the application of information technology, much information in college teaching is recorded and stored electronically, which founds the basic of a computer-aid analysis. In this paper, we perform teaching quality evaluation within machine learning framework, focusing on learning and modeling electronic information associated with quality of teaching, to get a stable model described the substantial principles of teaching quality. Artificial Neural Network (ANN) is selected as the main model in this work. Experiment results on real data sets consisted of 4 subjects / 8 semesters show the effectiveness of the proposed method.

[Retracted] Teaching Quality Evaluation of Ideological and Political Courses in Colleges and Universities Based on Machine Learning

“…e use of rough set theory to overcome the issue of irrational index weights is one aspect of relevant research into integrating machine learning technology into teacher assessment systems [21], the introduction of decision trees to analyze teaching data [22], and an investigation into the effects of teaching quality factors using association rule algorithms. Additional research has found that artificial neural networks can be used to model education in order to evaluate it [23,24]. Peng Juping, for example, applied artificial neural network theory, developed related mathematical models, quantified the indicators in a comprehensive manner, and then constructed a Bayesian neural network model to obtain a more reasonable evaluation result [25].…”

English Teaching Evaluation Combined with End-User Computing and Neural Network

“…Artificial neural networks were used in the literature [31] to represent instructional evaluation. Studies [32] used the artificial neural network theory to evaluate ethnic colleges and universities for their teaching quality, establishing associated mathematical models, completely quantifying indicators, and building BP models to get at a more reasonable evaluation conclusion.…”