Identifying Students’ Behavioral Online Learning Patterns Through Learning Analytics: a Case of Universitas Terbuka

EasyChair Preprint 8534

Abstract

Universitas Terbuka (UT) is a university in Indonesia that implements open and distance education system. As a distance education institution, UT’s students are learning independently using pre-produced learning materials. As one of its support services, UT provides online-tutorials with which students can interact with tutors and other students in the same tutorial classes. The online-tutorial is designed asynchronously using Moodle-based LMS, which automatically records all students’ learning activities and thus provide rich data of learning analytics. This paper reports the results of study on learning analytics to see students’ online learning behavioral patterns and their correlations with students’ performances. The study is explorative and correlational in nature. The population of the study is all students who registered for online-tutorials in 2019 in all courses offered by four faculties at UT. The results of the analysis show that in general, the trend of student participations in online-tutorial decrease as the semester progresses. The correlational analysis results show that there are positive significant relationships between students’ performance in tutorial and examination, tutorial and final course score, as well as between students’ performance in the examination and final course score. The analysis also found significant differences in students’ final course performance in a different course category, which indicates that course size does have an impact on students’ performance. The analysis also indicates that course size significantly correlates to students’ performance. The results of this research imply that course size is one of the effects that need to be considered in the learning model. In this case, the course size as namely a random-effect in statistical modeling. The involvement of random-effects in modeling needs to be considered.

Keyphrases: Moodle, Random effect, Universitas Terbuka, course size, learning analytics

@booklet{EasyChair:8534,
  author    = {Dewi Juliah Ratnaningsih and Tian Belawati and Kristanti Ambar Puspitasari and Mery Noviyanti},
  title     = {Identifying Students’ Behavioral Online Learning Patterns Through Learning Analytics: a Case of Universitas Terbuka},
  howpublished = {EasyChair Preprint 8534},
  year      = {EasyChair, 2022}}