How do online learning intentions lead to learning outcomes? The mediating effect of the autotelic dimension of flow in a MOOC

Chaker, Rawad; Bouchet, François; Bachelet, Rémi

doi:10.1016/j.chb.2022.107306

Cited by 13 publications

(12 citation statements)

References 64 publications

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“…When students feel they can control their emotions, positive results can encourage increased interest in further learning (Moors et al, 2013). The socially driven intention is a major factor to be considered in an online learning environment (Chaker et al, 2022). Students with good mental health show significantly greater perceived learning outcomes than their peers (Wei et al, 2023).…”

Section: Figure 4: Students Motivation Chartmentioning

confidence: 99%

The Southeast Asian Conference on Education 2024: Official Conference Proceedings

2024

SEACE Official Conference Proceedings

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This practitioner research in education paper is based on the experiences of two English language educators taking part in a collaborative online international learning project, otherwise known as COIL. Synchronous and asynchronous teaching methods were used for English language learners to meet and work with students from other countries. The collaboration took place virtually between two institutions of higher education, located on different sides of the globe, namely Mexico and Singapore. Students met to work in groups on a project, in an authentic situation to practice the target language. The experience provided students with intercultural and transnational learning through interaction, collaboration and taking ownership of their learning. With little or no experience of taking part in COIL projects, the practitioners investigated three key questions: 1. What are the benefits to students of taking part in international collaboration? 2. What are the challenges of such a project? 3. How do students cope with misunderstandings resulting from cultural and ethnic differences? Data was collected through the analysis of written online learning logs using thematic coding to create a survey given to participating students at the end of the project. The benefits, as well as the challenges, are considered followed by recommendations based on first-hand experiences and reflections to offer a practical reference for colleagues and educators who may wish to explore the feasibility of taking part in such a project.

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Section: Figure 4: Students Motivation Chartmentioning

confidence: 99%

The Southeast Asian Conference on Education 2024: Official Conference Proceedings

2024

SEACE Official Conference Proceedings

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“…The sample size of 331 is more than the minimum size of 200 required for SEM analysis; thus, normality should be tested because it is one of the basic assumptions required to carry out SEM analysis (Kline, 2011). Multivariate normality was supported by comparison results, and Mardia's coefficient (Mardia, 1970) were used to test this situation, and the coefficient should be smaller than the formula p Â (p þ 2), where p is the number of observed variables (Bollen, 1989;Chen, 2016). Thus, 457.975 in this study, was below the computed result of 575 from the formula p Â (p þ 2), and the test result showed that the data were normally distributed.…”

Section: Normality Testmentioning

confidence: 99%

What makes learners enhance learning outcomes in MOOCs? Exploring the roles of gamification and personalization

Cheng

2023

ITSE

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Purpose The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to explore whether gamification and personalization as environmental stimuli to learners’ learning engagement (LE) can affect their learning persistence (LP) in massive open online courses (MOOCs) and, in turn, their learning outcomes in MOOCs. Design/methodology/approach Sample data for this study were collected from learners who had experience in taking gamified MOOCs provided by the MOOCs platform launched by a well-known university in Taiwan, and 331 usable questionnaires were analyzed using structural equation modeling. Findings This study demonstrated that learners’ perceived gamification and personalization in MOOCs positively influenced their cognitive LE and emotional LE elicited by MOOCs, which jointly explained their LP in MOOCs and, in turn, enhanced their learning outcomes. The results support all proposed hypotheses and the research model, respectively, explaining 82.3% and 65.1% of the variance in learners’ LP in MOOCs and learning outcomes. Originality/value This study uses the S-O-R model as a theoretical base to construct learners’ learning outcomes in MOOCs as a series of the psychological process, which is influenced by gamification and personalization. Noteworthily, while the S-O-R model has been extensively used in prior studies, there is a dearth of evidence on the antecedents of learners’ learning outcomes in the context of MOOCs, which is very scarce in the S-O-R view. Hence, this study enriches the research for MOOCs adoption and learning outcomes into an invaluable context.

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“…Lew et al [14] built a model of sustained users' use and examined its correlation with users' intention to use, combining with the Theory of Planned Behavior (TPB) of perceived behavioral control [45], the perceived usefulness and perceived ease of use in the Technology Acceptance Model (TAM) [46], self-efficacy in Social Cognitive Theory (SCT) [47] and enjoyment in Motivation Theory [48]. In a study on users' willingness to learn online, Chaker et al [15] discovered that the mind flow dimension was a key mediator based on Mind Flow Theory [49] and social intention; to investigate users' opinions regarding the usage of online education, Xu et al [16] combined perceived value and TAM from the teachers' perspective. To investigate the characteristics influencing users' desire to utilize desktop webinars for online learning, Lakhal & Khechine [50] expanded the Unified Theory of Acceptance and Use of Technology (UTAUT) created by Venkatesh et al [51].…”

Section: The Use Of Pertinent Theories In Online Classesmentioning

confidence: 99%

“…At the same time, the research on online class APPs in previous papers is primarily carried out through quantitative analysis [14][15][16][17], while through this method, how a certain factor or theory can influence users' willingness to use can be explained, but it cannot prove that users will pay attention to this element when using the software. The questionnaire scale of the original theoretical model may not be entirely suitable for the evaluation of online class APPs, and typical single research approaches have several disadvantages.…”

Section: Introductionmentioning

confidence: 99%

How to Promote Online Education through Educational Software—An Analytical Study of Factor Analysis and Structural Equation Modeling with Chinese Users as an Example

Wang

Jiang

2022

Systems

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Online learning has emerged as a fresh method to successfully prevent teacher and student gatherings as well as the propagation of viruses in the context of the ongoing influence of the COVID-19. A problem deserving of consideration is how to increase users’ desire to participate in online learning through online class APPs, identify the variables that affect users’ use of them, and create a useful assessment scale. In this study, user ratings from 68 students who had used an online class APP were collected using the combination of qualitative and quantitative research, and 200 online questionnaires were sent out to complement the interview findings, based on which 328 assessment questionnaires were gathered and 23 valid items were obtained. The influencing elements that had an impact on users’ online learning experiences were identified using factor analysis, and the relationships among the components were investigated using structural equation modeling. Perceived benefits are the main influencing factors, subjective norms and functional quality are the direct factors influencing users’ perceived benefits, and self-efficacy is influenced by subjective norms while promoting the perception of functional quality. The factors influencing users’ use of online class APPs are ultimately identified as perceived benefits, functional quality and self-efficacy. In order to facilitate users’ online learning, user psychological traits, social ties and software functions should be integrated into a cohesive system while designing online class APPs.

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How do online learning intentions lead to learning outcomes? The mediating effect of the autotelic dimension of flow in a MOOC

Cited by 13 publications

References 64 publications

The Southeast Asian Conference on Education 2024: Official Conference Proceedings

The Southeast Asian Conference on Education 2024: Official Conference Proceedings

What makes learners enhance learning outcomes in MOOCs? Exploring the roles of gamification and personalization

How to Promote Online Education through Educational Software—An Analytical Study of Factor Analysis and Structural Equation Modeling with Chinese Users as an Example

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