Adoption, completion and continuance of MOOCs: a longitudinal study of students’ behavioural intentions

Gupta, Kriti Priya; Maurya, Harshit

doi:10.1080/0144929x.2020.1829054

Cited by 33 publications

(33 citation statements)

References 67 publications

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“…Other most employed frameworks involve uses and gratifications theory (U&G) (Zhang et al, 2022 ), Diffusion of Innovation Theory (DOI), Unified Theory of Acceptance and Use of Technology (UTAUT) (Taghizadeh et al, 2021 ), and Theory of Planned Behavior (TPB) (Dalvi-Esfahani et al, 2020 ). Stimulus-Organism-Response (SOR) model (Shao & Chen, 2021 ), Technology-User-Environment (TUE) framework (Gupta & Maurya, 2021 ), and Information Success System (ISS) (San-Martin et al, 2020 ) framework are also leveraged.…”

Section: Theoretical Background and Literature Reviewmentioning

confidence: 99%

“…Anchored on instructor related, course related, and system related factors, Liu and Pu ( 2021 ) further validated the effects of the factors under these three dimensions. While Gupta and Maurya ( 2021 ) were from the aspects of technological context, user context, environment context factors. And Reparaz et al ( 2020 ) were based on human and context factors.…”

Section: Theoretical Background and Literature Reviewmentioning

confidence: 99%

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Understanding the impact of quality elements on MOOCs continuance intention

Shang

Wenfei

2022

Educ Inf Technol

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Online learning has captured much attention, while given for high dropout rate, continuance of MOOCs is now a most concerned critical topic in both research and practical field. From teaching-based quality and platform-based quality perspectives, this study aims to investigate the impact of quality elements on continuance intention based on Expectation Confirmation Model, Task Technology Fit, flow theory and trust. We conducted our research through online questionnaire from July to September in 2020 and collected 555 valid responses which were mainly from university students who had already participated in MOOCs. A Partial Least Square Structural Equation Model approach is employed to test the research model. The results show that teaching-based quality will increase both students’ task technology fit and confirmation, and platform-based quality can improve the confirmation and perceived value about learning in MOOCs. Task technology fit, confirmation and perceived value will further facilitate the using experience and enhance trust and satisfaction. This research comprehensively illustrates the importance of quality relevant to teaching and platforms on continuance intention of MOOCs.

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Section: Theoretical Background and Literature Reviewmentioning

confidence: 99%

Section: Theoretical Background and Literature Reviewmentioning

confidence: 99%

Understanding the impact of quality elements on MOOCs continuance intention

Shang

Wenfei

2022

Educ Inf Technol

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“…Moreover, the learners' behaviour towards completing courses specifically within the context of MOOCs, needs further investigation (Paton et al, 2018). Although several researchers have examined the initial adoption intention of MOOCs (Sun et al, 2018;Lung-Guang, 2019;Gupta, 2019;Mohan et al, 2010), but the completion intention of MOOCs, which is a major concern amongst MOOC developers, has not been given ample attention by researchers (Gupta and Maurya, 2020).…”

Section: Introductionmentioning

confidence: 99%

Understanding learners' completion intention of massive open online courses (MOOCs): role of personality traits and personal innovativeness

Gupta

2021

IJEM

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PurposeThe present study investigates the influence of five personality traits based on the Big Five model, i.e. extraversion, neuroticism, conscientiousness, agreeableness and openness to experience and personal innovativeness on learners' intention to complete MOOCs.Design/methodology/approachThe proposed model was empirically tested using cross-sectional design. The primary data were gathered through a survey of 515 students at five higher educational institutions in the National Capital Region of Delhi, India. Structural equation modelling was used to test the hypothesized relationships in the proposed model.FindingsThe study has found significant associations between the personality traits, personal innovativeness and MOOC completion intention. The findings indicate that extraversion, conscientiousness, agreeableness, openness to experience and personal innovativeness have significant positive effects whereas neuroticism has no significant effect on MOOCs continuance intention. Personal innovativeness has been found to mediate the relationships between all the personality traits and MOOCs completion intention of learners.Practical implicationsOur findings can potentially address the issue of drop-out rates of MOOCs in developing countries such as India. The findings of the study are helpful for MOOCs providers and other stakeholders. The MOOC developers should develop courses with wide scope so as to accommodate learners with different personality profiles. Additionally, during the enrolment process, MOOC providers can identify the students' attributes through personality tests. This will help in customizing the study material and teaching pedagogy as per the needs of the students.Originality/valueThe study contributes to the growing area of research in MOOCs usage by exploring the influence of personality traits on learners' behaviour towards completing MOOCs. Since the learners' intention to complete MOOCs is a major concern for MOOC developers, hence the present study makes a worthwhile contribution as it is a relatively under-researched area.

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“…A positive relationship between online learning readiness has been confirmed in various contexts, such as in open online course (Gupta and Maurya 2020 ), self-service technology (Lin and Chang 2011 ; Tuyet and Tuan 2020 ) and internet banking (Alghamdi et al 2018 ). Hence, the third hypothesis is:…”

Section: Literature Reviewmentioning

confidence: 96%

Do Science and Social Science Differ? Multi-Group Analysis (MGA) of the Willingness to Continue Online Learning

et al. 2022

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Without proper preparation by higher institutions, the COVID-19 pandemic has forced the world to rely on online learning. Even students of social science and science are looking for different knowledge and skills. Currently, both groups rely on the same method to gather knowledge for future undertakings. Given the uncertainty regarding the resolution of COVID-19, which has driven students to continue using online learning, the current study aims to identify the factors of willingness to continue online learning among social science and pure science students by extending the use of expectation-confirmation theory. Applying a purposive sampling method, 2,215 questionnaires were collected among undergraduate students from Universiti Malaysia Terengganu (UMT) using an online survey. Current study found that expectation and confirmation positively affect satisfaction. Attitude, satisfaction and readiness were found to have a positive relationship with willingness to continue online learning. Meanwhile, self-efficacy was found unsupported hypothesis for the direct effect. For multigroup analysis, readiness was found to have a significant difference between students of social science and pure science. The findings of this research enrich the literature about online learning, especially in the COVID-19 setting. Moreover, this work is useful for higher education institutions seeking to design a better strategy that allows students to return to campus.

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Adoption, completion and continuance of MOOCs: a longitudinal study of students’ behavioural intentions

Cited by 33 publications

References 67 publications

Understanding the impact of quality elements on MOOCs continuance intention

Understanding the impact of quality elements on MOOCs continuance intention

Understanding learners' completion intention of massive open online courses (MOOCs): role of personality traits and personal innovativeness

Do Science and Social Science Differ? Multi-Group Analysis (MGA) of the Willingness to Continue Online Learning

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