Satisfaction with online distance learning: evaluating the attention, relevance, confidence, and satisfaction (ARCS) model / Nurul Hidayana Mohd Noor
COVID-19 has turned Malaysia's educational setting at all levels from conventional classrooms to a full-fledged online distance learning (ODL) environment. Thus, examining student satisfaction with the ODL post-pandemic is crucial and needs to be examined. By applying the Attention, Relevance,...
Saved in:
Main Author: | |
---|---|
Format: | Book Section |
Language: | English |
Published: |
Universiti Teknologi MARA Cawangan Kedah
2023
|
Subjects: | |
Online Access: | https://ir.uitm.edu.my/id/eprint/81233/1/81233.pdf https://ir.uitm.edu.my/id/eprint/81233/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Universiti Teknologi Mara |
Language: | English |
id |
my.uitm.ir.81233 |
---|---|
record_format |
eprints |
spelling |
my.uitm.ir.812332023-08-21T00:02:24Z https://ir.uitm.edu.my/id/eprint/81233/ Satisfaction with online distance learning: evaluating the attention, relevance, confidence, and satisfaction (ARCS) model / Nurul Hidayana Mohd Noor Mohd Noor, Nurul Hidayana Learning ability Kindergarten Educational productivity COVID-19 has turned Malaysia's educational setting at all levels from conventional classrooms to a full-fledged online distance learning (ODL) environment. Thus, examining student satisfaction with the ODL post-pandemic is crucial and needs to be examined. By applying the Attention, Relevance, Confidence, and Satisfaction (ARCS) motivation model, this study aimed to explore how attention, relevance, and confidence can predict student satisfaction with online learning. Employing convenience sampling, the data were collected from undergraduate students of the Universiti Teknologi MARA (UiTM) Seremban 3 Campus, Malaysia. Based on Krejcie and Morgan's (1970) table for determining sample size for a given population (N=5000), 381 samples were selected, and a final valid of 268 students participated in this study. Correlational results have proved that all independent variables were significantly influencing student satisfaction. The study also found that relevance emerged as a significant predictor of student satisfaction with online learning. This study suggests that universities and educators must employ strategies to enhance students' online learning satisfaction. This research is essential since it provides evaluation results to the universities, which the results could be used to promote higher-quality learning and education. Universiti Teknologi MARA Cawangan Kedah 2023 Book Section NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/81233/1/81233.pdf Satisfaction with online distance learning: evaluating the attention, relevance, confidence, and satisfaction (ARCS) model / Nurul Hidayana Mohd Noor. (2023) In: Journal of Creative Practices in Language Learning and Teaching. Universiti Teknologi MARA Cawangan Kedah, pp. 1-13. (Submitted) |
institution |
Universiti Teknologi Mara |
building |
Tun Abdul Razak Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknologi Mara |
content_source |
UiTM Institutional Repository |
url_provider |
http://ir.uitm.edu.my/ |
language |
English |
topic |
Learning ability Kindergarten Educational productivity |
spellingShingle |
Learning ability Kindergarten Educational productivity Mohd Noor, Nurul Hidayana Satisfaction with online distance learning: evaluating the attention, relevance, confidence, and satisfaction (ARCS) model / Nurul Hidayana Mohd Noor |
description |
COVID-19 has turned Malaysia's educational setting at all levels from conventional classrooms to a full-fledged online distance learning (ODL) environment. Thus, examining student satisfaction with the ODL post-pandemic is crucial and needs to be examined. By applying the Attention, Relevance, Confidence, and Satisfaction (ARCS) motivation model, this study aimed to explore how attention, relevance, and confidence can predict student satisfaction with online learning. Employing convenience sampling, the data were collected from undergraduate students of the Universiti Teknologi MARA (UiTM) Seremban 3 Campus, Malaysia. Based on Krejcie and Morgan's (1970) table for determining sample size for a given population (N=5000), 381 samples were selected, and a final valid of 268 students participated in this study. Correlational results have proved that all independent variables were significantly influencing student satisfaction. The study also found that relevance emerged as a significant predictor of student satisfaction with online learning. This study suggests that universities and educators must employ strategies to enhance students' online learning satisfaction. This research is essential since it provides evaluation results to the universities, which the results could be used to promote higher-quality learning and education. |
format |
Book Section |
author |
Mohd Noor, Nurul Hidayana |
author_facet |
Mohd Noor, Nurul Hidayana |
author_sort |
Mohd Noor, Nurul Hidayana |
title |
Satisfaction with online distance learning: evaluating the attention, relevance, confidence, and satisfaction (ARCS) model / Nurul Hidayana Mohd Noor |
title_short |
Satisfaction with online distance learning: evaluating the attention, relevance, confidence, and satisfaction (ARCS) model / Nurul Hidayana Mohd Noor |
title_full |
Satisfaction with online distance learning: evaluating the attention, relevance, confidence, and satisfaction (ARCS) model / Nurul Hidayana Mohd Noor |
title_fullStr |
Satisfaction with online distance learning: evaluating the attention, relevance, confidence, and satisfaction (ARCS) model / Nurul Hidayana Mohd Noor |
title_full_unstemmed |
Satisfaction with online distance learning: evaluating the attention, relevance, confidence, and satisfaction (ARCS) model / Nurul Hidayana Mohd Noor |
title_sort |
satisfaction with online distance learning: evaluating the attention, relevance, confidence, and satisfaction (arcs) model / nurul hidayana mohd noor |
publisher |
Universiti Teknologi MARA Cawangan Kedah |
publishDate |
2023 |
url |
https://ir.uitm.edu.my/id/eprint/81233/1/81233.pdf https://ir.uitm.edu.my/id/eprint/81233/ |
_version_ |
1775626410585489408 |