Building a structural model of motivational regulation and learning engagement for undergraduate and graduate students in higher education

Yun, Heoncheol; Park, Sanghoon

doi:10.1080/03075079.2018.1510910

Cited by 29 publications

(24 citation statements)

References 39 publications

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“…For example, the literature suggested the importance of getting around the technological anxiety [92] caused by online classes, the feeling of belonging to an academic community [93,94] and feedback [63], which are new vectors for students and teachers, and also for teaching institutions. In addition, it is crucial to recognize students and teachers' remarkable adaptation to this new form of class, where physical presence was replaced by technology [95][96][97], altering the student/teacher relationship considerably [59,98,99]. Resilience was the key to this teaching typology during the pandemic, irrespective of whether teachers have the competences inherent to online teaching [57,[100][101][102].…”

Section: Bibliometric Analysismentioning

confidence: 99%

COVID-19 and Disruption in Management and Education Academics: Bibliometric Mapping and Analysis

2020

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COVID-19, What to do now? This issue has had devastating effects in all domains of society worldwide. Lockdowns, the lack of freedom and social distancing meant the closure of a country’s entire activity. Having effects at all levels, beside incalculable ones in health, it is argued that scientific activity in education, business, economics and management suffered some of the most drastic impacts of this pandemic. This study aims to map the scientific literature in these areas in the context of COVID-19 and analyze its content through bibliometrics, which made it possible to highlight the scarcity of studies on the topic, namely empirical studies on the effects of this pandemic on scientific research and teaching/education. The results show there is a lack of peer-reviewed publications on this topic, with the studies covered (93) via the threads used revealing only 28 articles coming within the proposed objective. The bibliometrics corroborates that shortage. Finally, the contributions and implications for theory and practice are presented, followed by the limitations and suggestions for future research.

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Section: Bibliometric Analysismentioning

confidence: 99%

COVID-19 and Disruption in Management and Education Academics: Bibliometric Mapping and Analysis

2020

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“…More specifically, a well-developed interest of the learner, who self-regulates learning, supports for active participation in such a problem-solving task through a critical thinking learning process [ 19 , 20 ]. Importantly, the goal orientation MRSs were significant predictors to predict students’ learning engagement in completing learning tasks [ 21 ]. Thus, the effective use of different MRSs is crucial to students so as to enhance the appropriate use of CLSs for supporting cognitive learning in online learning environments.…”

Section: Discussionmentioning

confidence: 99%

Exploring the structural relationships between medical students’ motivational regulation, cognitive learning, and academic performance in online learning

Yun¹,

Kim²,

Chung³

2021

Korean J Med Educ

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Purpose The purpose of this study was to investigate the effect of motivational regulation strategies (MRSs) on cognitive learning and academic performance. Methods The participants were a total of 510 pre-medical and medical students. Survey instruments assessed the use of MRSs and cognitive learning strategies. Students’ grade point averages were used for academic performance. Structural equation modeling was used to analyze data, using Mplus ver. 7.4 (Muthén & Muthén, Los Angeles, USA). Results Confirming the measurement model validity, the results of structural model indicated the followings: (1) MRSs had a significant impact on cognitive learning, while these strategies negatively affected academic performance; (2) cognitive learning significantly influenced academic performance and mediated the effect of MRSs on academic performance; and (3) only academic levels had a significant effect on cognitive learning. Conclusion The findings from this study confirmed that MRSs were highly influential to predicting students’ cognitive learning which affects their better learning performance. Thus, instructional design and practice to support learning motivation is needed to promote cognitive learning and training programs to practice the effective methods of using MRSs in learning need to be provided.

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“…The fact that all three variables have been significantly raised underscores the pedagogical potency of TBML to deal with disengagement and attrition issue reported among university students (Shah & Cheng, 2019). Yun and Park (2020) contend that environmental factors, interest elevation, goal orientation and behavioral enforcement are associated with emotional and cognitive engagement in higher education. To this end, the present study has portrayed how mobile collaborative learning grounded in literacy practices serve as the catalyst to students' performativity and outcome in language learning (Kukulska-Hulme & Lee, 2020; Rambe & Bere, 2013).…”

Section: Rq 4: Significant Correlations Exist Between Tei Ole and Efl...mentioning

confidence: 96%

An Experiment on Mobile Learning to Leverage EFL Learners’ Engagement, Emotional Intelligence, and Learning Motivation

Imamyartha¹,

Wahjuningsih²,

Areta³

et al. 2021

The Journal of AsiaTEFL

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Research has acknowledged Mobile-assisted language learning (MALL) as one efficacious method for leveraging language proficiency across skills and components, leaving the investigation on language learners' motivation and emotional intelligence of peripheral focus, albeit being essential drives for academic success. This study seeks to fill the gaping void by investigating the impact of team-based mobile learning (TBML) as an instructional framework to leverage EFL learners' online learning engagement (OLE), trait emotional intelligence (TEI), and EFL learning motivation. This instructional framework involves a mobile instant messenger (MIM), Telegram, to support collaborative learning both within and beyond class hours. Employing a quasi-experimental approach, the study involved 475 undergraduate students at an Indonesian state university across majors, including nursing, management, science education, and non-formal education, with ages ranging from 18 to 22 years. The findings corroborate significant increment in the abovementioned dimensions resulting from TBML, as opposed to the unworthy increase associated with computer-based LMS. Moderate positive correlations also exist among three pertinent variables. Implications suggest how TBML accords English learners with the authentic learning community armed with myriads discourse resources to empower their multidimensional engagement in meaningful literacy practices.

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Building a structural model of motivational regulation and learning engagement for undergraduate and graduate students in higher education

Cited by 29 publications

References 39 publications

COVID-19 and Disruption in Management and Education Academics: Bibliometric Mapping and Analysis

COVID-19 and Disruption in Management and Education Academics: Bibliometric Mapping and Analysis

Exploring the structural relationships between medical students’ motivational regulation, cognitive learning, and academic performance in online learning

An Experiment on Mobile Learning to Leverage EFL Learners’ Engagement, Emotional Intelligence, and Learning Motivation

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