Open AccessStudents' Online Distance Learning Readiness for Mathematics and Statistics Courses
Author(s) -
Bushra Abdul Halim,
Siti Nursyahira Zainudin,
Siti Fairus Fuzi,
Siti Ramizah Jama,
Nurul Emyza Zahidi,
Nordianah Jusoh @ Hussain,
Wan Hartini Wan Hassan
Publication year - 2022
Publication title -
jurnal intelek
Language(s) - English
Resource type - Journals
eISSN - 2682-9223
pISSN - 1675-9885
DOI - 10.24191/ji.v17i1.15853
Subject(s) - distance education , mathematics education , descriptive statistics , multivariate analysis of variance , the internet , statistics , e learning , statistics education , psychology , computer science , mathematics , educational technology , world wide web
In early January 2020, the whole world including Malaysia was threatened by the outbreak of coronavirus (Covid-19) pandemic. In Malaysia, phases of Movement Control Order (MCO) were enforced to curb the spread of Covid-19 pandemic, and because of that, educational institutions were affected where learning must be continued by modifying face-to-face learning in campus to remote Online Distance Learning (ODL) at home for all the courses offered. This study investigates any significant difference between students’ ODL readiness dimensions for mathematics/statistics courses and the influence of students’ ODL readiness dimensions on mathematics/statistics performance. This research referred to five dimensions from the Online Learning Readiness Scale (OLRS); computer and internet self-efficacy, self-directed learning, learner control, motivation for learning, and online communication self-efficacy to measure students’ ODL readiness. Data were collected from 511 students in Universiti Teknologi MARA Melaka Branch of academic session March – July 2020 who took mathematics/statistics courses online. The statistical analyses used for this study were One-way repeated analysis of variance, one-way multivariate analysis of variance (one-way MANOVA) and multiple regression analysis. Results revealed that students taking statistics course showed higher readiness scores in computer and internet self-efficacy, and self-directed learning than students taking mathematics course. The results also show that students’ mathematics/statistics performance was influenced by self-directed learning in ODL. As a conclusion, students taking statistics course were more prepared and performed better in learning through ODL than students taking mathematics course.