A meta-analysis of learners' continuance intention toward online education platforms

被引：13

作者：

Dai, Jian ^{[1
]}

Zhang, Xing ^{[2
]}

Wang, Chengliang ^{[3
]}

机构：

[1] Zhejiang Univ Technol, Sch Management, Hangzhou, Peoples R China

[2] Cent China Normal Univ, Fac Artificial Intelligence Educ, Wuhan, Peoples R China

[3] East China Normal Univ, Fac Educ, Dept Educ Informat Technol, Shanghai, Peoples R China

来源：

EDUCATION AND INFORMATION TECHNOLOGIES | 2024年 / 29卷 / 16期

关键词：

Online education platform; Continuance intention; Influencing factor; Learner; Meta-analysis; INFORMATION-SYSTEMS CONTINUANCE; TECHNOLOGY ACCEPTANCE MODEL; EXPECTATION-CONFIRMATION; USER ACCEPTANCE; LEARNING-SYSTEM; EXTENSION; SUCCESS; BEHAVIOR; SATISFACTION; VALIDITY;

D O I：

10.1007/s10639-024-12654-7

中图分类号：

G40 [教育学];

学科分类号：

040101 ; 120403 ;

摘要：

The extant research on the factors influencing online education platform learners' continuance intention has yielded inconsistent results, which necessitates a thorough review and reanalysis of relevant literature. Therefore, this study combines different theoretical models and conducts a meta-analysis on 219 articles obtained from Web of Science, Scopus, and Engineer Village. The results show that variables from the expectation-confirmation model of continued IT usage, information system success model, theory of planned behavior, and flow theory are highly significant in driving learners' continuance intention. Among them, attitude (r = 0.603), perceived usefulness (r = 0.526), and satisfaction (r = 0.606) are strongly correlated with continuance intention. This study provides valuable insights for understanding the determinants of learners' continuance intention toward online education platforms. We also expected that the disclosure of effect sizes of influencing factors can provide scientific and convincing guidelines for platform developers, educators, and policymakers.

引用

页码：21833 / 21868

页数：36

共 118 条

[1] Covid-19 pandemic and online learning: the challenges and opportunities
Adedoyin, Olasile Babatunde
Soykan, Emrah
[J]. INTERACTIVE LEARNING ENVIRONMENTS, 2023, 31 (02) : 863 - 875
[2] THE THEORY OF PLANNED BEHAVIOR
AJZEN, I
[J]. ORGANIZATIONAL BEHAVIOR AND HUMAN DECISION PROCESSES, 1991, 50 (02) : 179 - 211
[3] Ajzen I., 1980, Understanding Attitudes and Predicting Social Behavior
[4] Extending the Technology Acceptance Model (TAM) to Predict University Students' Intentions to Use Metaverse-Based Learning Platforms
Al-Adwan, Ahmad Samed
Li, Na
Al-Adwan, Amer
Abbasi, Ghazanfar Ali
Albelbis, Nour Awni
Habibi, Akhmad
[J]. EDUCATION AND INFORMATION TECHNOLOGIES, 2023, 28 (11) : 15381 - 15413
[5] Al-Baghdadi PSA., 2023, MULTIDISCIPLINARY J, V11, P4
[6] Analysis of the essential factors affecting of intention to use of mobile learning applications: A comparison between universities adopters and non-adopters
Almaiah, Mohammed Amin
Al Mulhem, Ahmed
[J]. EDUCATION AND INFORMATION TECHNOLOGIES, 2019, 24 (02) : 1433 - 1468
[7] College professor perceptions of effective professor characteristics: A cross-cultural study
Alshare, Khaled A.
Al-Sholi, Hana Y.
Shadid, Ola R.
Moqbel, Murad
[J]. JOURNAL OF EDUCATION FOR BUSINESS, 2024, 99 (04) : 237 - 252
[8] Developing online learning resources: Big data, social networks, and cloud computing to support pervasive knowledge
Anshari, Muhammad
Alas, Yabit
Guan, Lim Sei
[J]. EDUCATION AND INFORMATION TECHNOLOGIES, 2016, 21 (06) : 1663 - 1677
[9] Ecological aspects of online learning in higher education: a qualitative multi-level exploration in a developing country
Arifeen, Shehla R. R.
[J]. EDUCATION AND INFORMATION TECHNOLOGIES, 2023, 28 (07) : 8195 - 8217
[10] Understanding continuance intentions of physicians with electronic medical records (EMR): An expectancy-confirmation perspective
Ayanso, Anteneh
Herath, Tejaswini C.
O'Brien, Nicole
[J]. DECISION SUPPORT SYSTEMS, 2015, 77 : 112 - 122

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