Dropout is not always a failure! Exploration on the prior knowledge and learning behaviors of MOOC learners

Massive open online courses (MOOCs) are highly beneficial to the public. However, much research demonstrated low completion numbers of MOOC learners. Several factors have been identified as influential factors in the success of MOOC learners. However, a few studies examined the extent to which prior...

Full description

Bibliographic Details
Published in:JOURNAL OF COMPUTERS IN EDUCATION
Main Authors: Matcha, Wannisa; Natthaphatwirata, Rusada; Uzir, Nora'ayu Ahmad; Gasevic, Dragan
Format: Article; Early Access
Language:English
Published: SPRINGER HEIDELBERG 2024
Subjects:
Online Access:https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001350457700001
author Matcha
Wannisa; Natthaphatwirata
Rusada; Uzir
Nora'ayu Ahmad; Gasevic
Dragan
spellingShingle Matcha
Wannisa; Natthaphatwirata
Rusada; Uzir
Nora'ayu Ahmad; Gasevic
Dragan
Dropout is not always a failure! Exploration on the prior knowledge and learning behaviors of MOOC learners
Education & Educational Research
author_facet Matcha
Wannisa; Natthaphatwirata
Rusada; Uzir
Nora'ayu Ahmad; Gasevic
Dragan
author_sort Matcha
spelling Matcha, Wannisa; Natthaphatwirata, Rusada; Uzir, Nora'ayu Ahmad; Gasevic, Dragan
Dropout is not always a failure! Exploration on the prior knowledge and learning behaviors of MOOC learners
JOURNAL OF COMPUTERS IN EDUCATION
English
Article; Early Access
Massive open online courses (MOOCs) are highly beneficial to the public. However, much research demonstrated low completion numbers of MOOC learners. Several factors have been identified as influential factors in the success of MOOC learners. However, a few studies examined the extent to which prior knowledge is associated with completion rates, learning outcomes, and patterns of student engagement. Hence, this paper aims to examine the relationships between prior knowledge, knowledge gains, and engagement patterns of MOOC learners. Specifically, this study used data mining techniques based on the patterns of learning performance. The Kruskal-Wallis test was used to examine the differences in terms of performance among the detected clusters. Process mining was then used to explore the learning process. The results demonstrated that five groups of learners were identified based on the patterns of their performance calculated from the score obtained from pre-tests (prior knowledge) and post-tests (learning gains) for each of the five topics, namely, Dropout, Stable, Progress, Late dropout, and Post attempt groups. Among the five groups, two of them exhibited different dropout behaviours, namely a) those who dropped out after scoring highly on the pre-test in the first topic in the MOOC and b) those who received relatively low scores in both pre- and post-tests on each topic they studied. This offers a novel insight into MOOC research while indicating that dropout may not be always associated with a lack of success. The study also demonstrated differences in the learning strategies that were adopted by different groups of learners. The key implication of this research is that the introduction of pre-tests as a priming strategy in MOOC design can have strong implications for decision-making related to learning and teaching.
SPRINGER HEIDELBERG
2197-9987
2197-9995
2024


10.1007/s40692-024-00340-z
Education & Educational Research

WOS:001350457700001
https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001350457700001
title Dropout is not always a failure! Exploration on the prior knowledge and learning behaviors of MOOC learners
title_short Dropout is not always a failure! Exploration on the prior knowledge and learning behaviors of MOOC learners
title_full Dropout is not always a failure! Exploration on the prior knowledge and learning behaviors of MOOC learners
title_fullStr Dropout is not always a failure! Exploration on the prior knowledge and learning behaviors of MOOC learners
title_full_unstemmed Dropout is not always a failure! Exploration on the prior knowledge and learning behaviors of MOOC learners
title_sort Dropout is not always a failure! Exploration on the prior knowledge and learning behaviors of MOOC learners
container_title JOURNAL OF COMPUTERS IN EDUCATION
language English
format Article; Early Access
description Massive open online courses (MOOCs) are highly beneficial to the public. However, much research demonstrated low completion numbers of MOOC learners. Several factors have been identified as influential factors in the success of MOOC learners. However, a few studies examined the extent to which prior knowledge is associated with completion rates, learning outcomes, and patterns of student engagement. Hence, this paper aims to examine the relationships between prior knowledge, knowledge gains, and engagement patterns of MOOC learners. Specifically, this study used data mining techniques based on the patterns of learning performance. The Kruskal-Wallis test was used to examine the differences in terms of performance among the detected clusters. Process mining was then used to explore the learning process. The results demonstrated that five groups of learners were identified based on the patterns of their performance calculated from the score obtained from pre-tests (prior knowledge) and post-tests (learning gains) for each of the five topics, namely, Dropout, Stable, Progress, Late dropout, and Post attempt groups. Among the five groups, two of them exhibited different dropout behaviours, namely a) those who dropped out after scoring highly on the pre-test in the first topic in the MOOC and b) those who received relatively low scores in both pre- and post-tests on each topic they studied. This offers a novel insight into MOOC research while indicating that dropout may not be always associated with a lack of success. The study also demonstrated differences in the learning strategies that were adopted by different groups of learners. The key implication of this research is that the introduction of pre-tests as a priming strategy in MOOC design can have strong implications for decision-making related to learning and teaching.
publisher SPRINGER HEIDELBERG
issn 2197-9987
2197-9995
publishDate 2024
container_volume
container_issue
doi_str_mv 10.1007/s40692-024-00340-z
topic Education & Educational Research
topic_facet Education & Educational Research
accesstype
id WOS:001350457700001
url https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001350457700001
record_format wos
collection Web of Science (WoS)
_version_ 1818940499453542400