The English Proficiency Test (EPrT) is a prediction test for English as a Foreign Language (TOEFL), which is a prerequisite for graduation at XYZ University. The Language Center provides a course for EPrT preparation. The course posttest data shows that only 74% of students met the graduation prerequisites. This study aims to develop an English course design based on the students’ English skill cluster. This study uses the K-Means clustering approach to classify the students based on English skills. The respondents are 397 students who joined the EPrT preparation course in October and November 2018. The 397 students are distributed into 3 clusters, which are 174 students in cluster 1, 116 students in cluster 2, and 107 students in cluster 3. Cluster 1 consists of students with the score below average. Cluster 2 consists of students with the total score above average, but the components score is below average. Cluster 3 consists of students with pre-test total score below average, but the post-test score are above average. Therefore, the EPrT preparation course is suggested to have different levels, instead of one level as now. The course materials are designed to be suitable for students’ initial English skills at each level.
An Unsupervised Fuzzy Clustering Approach for Early Screening of COVID-19 from Radiological Images
