Economics students‘ motivational orientations, self-regulated learning and academic engagement in higher education: a structural equation modelling approach

dc.contributor.authorArthur, Francis
dc.date.accessioned2026-05-28T15:32:06Z
dc.date.issued2024-07
dc.descriptionxx, 417 :,ill
dc.description.abstractIn the dynamic landscape of higher education, understanding the factors that influence Economics students' self-regulated learning and academic engagement is paramount. This study delves into the intricate interplay between Economics students' motivational orientations, self-regulated learning strategies, and their academic engagement using a Structural Equation Modelling (SEM) approach. The study was quantitative research that adopted a descriptive cross-sectional census design. In all, 452 undergraduate Economics students were involved in the study. Motivational orientations, self-regulated learning, academic engagement and academic support scales were adapted as the data collection instruments. Both descriptive (frequency and percentages, mean and standard deviation) and inferential statistics were used to analyse the data that were obtained. The study found that the Economics students had high motivational orientations, self-regulated learning and academic engagement. The study also revealed no statistically significant differences in self-regulated learning and academic engagement based on gender and academic level. Again, it was found that academic self-efficacy, task value orientation, mastery approach and performance-avoidance goal orientations had significant influence on Economics students‘ self-regulated learning. Finally, it was revealed that the lecturer‘s academic support negatively moderated the positive relationship between self-regulated learning and academic engagement. It was recommended that curriculum developers and Economics educators should design Economics curricula that challenge higher education students intellectually while providing opportunities for independent learning and problem solving.
dc.identifier.issn23105496
dc.identifier.urihttps://uir.ucc.edu.gh/handle/123456789/1244
dc.language.isoen_US
dc.publisherUniversity of Cape Coast
dc.subjectAcademic engagement Agentic engagement Artificial neural network Economics Higher education Motivational orientations Self-regulated learning Structural equation modelling
dc.titleEconomics students‘ motivational orientations, self-regulated learning and academic engagement in higher education: a structural equation modelling approach
dc.typeThesis

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