Cluster Analysis to Compare Learner Characteristics in English Courses of General Education - Supawan, Pornsin; Charuchinda, Intira (มนุษยสังคมสาร (มสส.) คณะมนุษยศาสตร์และสังคมศาสตร์ มหาวิทยาลัยราชภัฏบุรีรัมย์, 2023)
Understanding learner characteristics can guide educators in providing appropriate support to meet individual needs which can lead to learning achievement. This research aimed: 1) to cluster students by grades earned from English courses of General Education (GE) at a government university using cluster analysis, and 2) to compare the learner characteristics across different achievement levels by focusing on four learner characteristics, i.e. (1) motivation and attitudes, (2) student engagement, (3) test preparation and test taking behaviours, and (4) Classroom participation. A sample of 400 individuals was derived through cluster sampling. The research instrument was a questionnaire. The data were statistically analyzed by using frequency, mean, standard deviation, K-means cluster analysis, MANOVA, ANOVA, and Bonferroni. The findings were as follows. 1) Using K-means cluster analysis to cluster student achievement levels as indicated by grade point averages of the two GE English courses, it found three clusters: high achievers, moderate achievers, and low achievers. 2) Concerning comparisons of learner characteristics, it found that motivation and attitudes, learning engagement, and test preparation and test taking behaviours of the high achievers were significantly higher than those of the moderate and low ones. However, it found no statistically significant difference between the learner characteristics of the moderate achievers and those of the low ones. Remarkably, statistically significant differences in classroom participation of all the three clusters were not found.