Text mining on English subject-specific descriptions of tenth-graders in general high schools

The purpose of this study was to analyze English subject-specific descriptions through text mining, examine their alignment to the curriculum achievement standards, and ultimately support students’ educational growth. We collected English subject-specific descriptions for 1,030 tenth-graders from general high schools in City A, and keywords and contexts were extracted using TF, TF-IDF, phi coefficient analysis, and trigram analysis. The results revealed that the subject-specific descriptions frequently neglected the following aspects of learning and instruction in curriculum achievement standards: familiar and general themes, conversation and listening skills, language use across different types of information, and proper email writing. Although descriptions are intended to reflect students’ actual achievement levels, those for lower achievement levels (i.e., D and E) were often overstated. Improvements are necessary to ensure closer alignment between the descriptions and the curriculum achievement standards, with particular emphasis on the accurate representation of lower achievement levels. Based on the findings, we discussed potential improvement strategies for educational authorities to consider and implement.