Analysis of Changes in Learning Objectives for Educational Evaluation Courses Using Text Mining

This study analyzes the changes in “Educational Evaluation” courses offered at four-year universities over the past 10 years (2013-2022) using text analysis techniques. Keyword frequency analysis and network analysis were performed on “learning objectives” included in 677 lecture syllabi from 17 universities. The main findings are as follows. First, according to TF-IDF-based keyword frequency analysis, the terms “method”, “understanding”, “theory”, “relevance”, and “knowledge” were identified as the most important terms throughout the period. Second, as a result of the network analysis, five communities were identified throughout the period: ① understanding and application of evaluation methods and procedures, relevant concepts,and principles; ② foundation theories and skills cultivation related to school contexts and experiences; ③ basic knowledge and qualifications required for prospective teachers; ④ test item development and reliability analysis; and ⑤ emerging issues in evaluation and the development of individual evaluation perspectives. Third, according to the results of keyword networks categorized by course opening years and primary evaluation methods, different numbers of communities were detected for each course group. On the basis of these results, we discussed the implications for the future operation of “Educational Evaluation” courses in teacher education.