Research pick: Evaluating higher education in China - "Evaluation of teaching effectiveness in higher education based on social networks"

A new approach to the evaluation of teaching effectiveness in universities has been introduced in the International Journal of Networking and Virtual Organisations. In response to the various reforms and economic advancements in China, higher education has experienced some profound transformations in recent years. It is growing rapidly and university enrolment, once accessible only to the elite is transitioning towards mass education. Thus evaluation tools are increasingly important so that society can rely on good, solid education.

The new technique uses a social network to obtain a more comprehensive assessment than was previously possible. According to the researchers, Xiyang Li of Hunan City University Hunan and Quanzhong Yang of Luoyang Polytechnic, China, their method could provide universities with a systematic tool for evaluating instructional practices and so potentially improving educational quality.

The team first looked at the ways in which teaching effectiveness is currently judged with the aim of understanding what factors are used in evaluation. From this starting point, the researchers have established a set of principles to guide the creation of a new evaluation system.

To help in this process, they have used various computational techniques, including calculating something called “entropy matching degree.” This measurement helps gauge how well different factors align or correspond. Additionally, they utilize the Support Vector Machine (SVM) algorithm, a computer program designed to develop a solid evaluation framework. This helps in organizing and analyzing data to accurately assess the quality of teaching. Then, by building a social network, they can look at how the different factors are perceived by different groups of people within education.

This network-driven approach generates evaluation results with a confidence level of 99%, says the team, and with minimal entropy matching errors, which suggests it could be a practical approach to educational evaluation.

Li, X. and Yang, Q. (2024) ‘Evaluation of teaching effectiveness in higher education based on social networks’, Int. J. Networking and Virtual Organisations, Vol. 30, No. 1, pp.1–14.