Research Status and Prospect of Teaching Evaluation in the Context of Big Data

-- CiteSpace-based visual analysis

Abstract

In order to investigate the research status and future development trend of teaching evaluation in the context of big data, this paper takes 325 papers in the Chinese database of China Knowledge Network from 2013 to 2022 as the research samples, and analyzes the co-citation network and keyword co-occurrence network of the collected literature with the help of CiteSpace software to explore the development trend, research overview and current research hotspots in this field. The study found that (1) in terms of the annual number of papers issued, the research on teaching evaluation in the context of big data is in an upward trend from 2013 to 2020, and reaches the climax of papers issued in 2020. (2) From the analysis results of core authors as well as author institution networks, there are connections among relevant authors that can promote the development of the field, but in general, communication and cooperation among scholars need to be further strengthened to lead to the emergence of more cohesive research teams. And there are few institutions studying teaching evaluation in the context of big data, but there is no cooperative relationship among various institutions. (3) From the analysis results of research hotspots, the research hotspots of teaching evaluation in the context of big data are mainly focused on big data, teaching evaluation, teaching mode, artificial intelligence, smart classroom, precise teaching and so on. (4) The frontier research on teaching evaluation in the context of big data mainly focuses on big data, information technology, smart classroom, mooc, and evaluation system.