PROFILING STUDENT BASED ON ACADEMIC PERFORMANCE: IDENTIFYING KEY CHARACTERISTICS IN AN ONLINE LEARNING ENVIRONMENT

Abstract

In the context of online education where interactions between learners and teachers are mediated through a learning management system, understanding the diverse profiles of students is crucial for improving academic outcomes and designing effective learning interventions. This study aims to identify key characteristics of students based on their academic performance within the English Language Education Study Program (ELSP) at Universitas Terbuka. It explores how students can be classified into distinct groups according to their performance in a core course within the study program. An online cross sectional survey was done to gather data on demographic, professional, and behavioral factors, such as teaching experience, digital readiness, learning styles, readiness for independent learning, as well as level of English Proficiency (EP) of the students. A sample of 20 in-service teacher students were found to meet the criteria to be included in further analyses. These students were grouped into two performance categories (High Achievers and Low Achievers) based on their scores in the Teaching English as a Foreign Language (TEFL) course, one of the core courses that was delivered in the English language. Descriptive statistics were employed to identify common characteristics that can be used to profile these groups. The most notable finding in terms of academic performance was the relationship between English proficiency (EP) and academic performance (course grades). High achievers tended to have higher EP scores, suggesting that students with stronger language skills are better equipped to handle the demands of the TEFL course. However, students in the middle EP range (A2 to B1) showed more variability in their grades, indicating that other factors such as motivation, study strategies, and digital readiness may also play important roles in determining academic outcomes. These findings offer valuable initial insights into the characteristics that may influence students’ achievement in the course, providing educators and administrators with information that can be utilized to enhance support mechanisms and tailor instructional strategies. Although based on a limited sample size, but the characteristic patterns found can add meanings to the growing body of knowledge on online education and student profiling, highlighting key factors that need to be considered to promote academic success in distance learning environments.