The application of content mining techniques to the analysis of educational evaluation research trends

Due to the mass accumulation of digital documents in nowadays research environment, related statistical or content mining methods for analyzing, organizing, and accessing information from the document collections are in great need. This research aimed to: (1) identify the core journals in the field of educational evaluation research through cross-verification of questionnaire survey and database searching; (2) find out major research topics and their evolutions by analyzing the publications in the core journals based on scientometrics methods such as citation analysis and text mining techniques. Based on the findings, the major salient research topics include principal's leadership, class size, evaluation, reform, teacher certification, opportunity to learn, retention, and voucher. And as to the issue of the evaluation methods, the studies conducted by Chen, Weiss, and Rossi are identified as newer ones than those by Cook and Compbell, which coincides with the fact shown in the evaluation theory tree (a sort of topical tree) organized by Marvin Alkin, an experienced expert in the field. Besides, with this topic trend analysis, it is also found that the number of papers dealing with the major research topics seems to be decreasing. However, all these results need to be interpreted by domain experts to reveal their true meanings. The methodology presented in this research may be applied not only to improve the efficiency of content analysis, but also to facilitate regular tracing of topic evolution, to spot the positions of important researchers in the field, and therefore to provide relevant clues or materials for further studies.