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Leveraging learning experience design: digital media approaches to influence motivational traits that support student learning behaviors in undergraduate online courses

Higher education may benefit from investigating alternative evidence-based methods of online learning to understand students’ learning behaviors while considering students’ social cognitive motivational traits. Researchers conducted an in situ design-based research (DBR) study to investigate learner...

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Detalles Bibliográficos
Autores principales: Wong, Joseph T., Hughes, Bradley S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9552131/
https://www.ncbi.nlm.nih.gov/pubmed/36249913
http://dx.doi.org/10.1007/s12528-022-09342-1
Descripción
Sumario:Higher education may benefit from investigating alternative evidence-based methods of online learning to understand students’ learning behaviors while considering students’ social cognitive motivational traits. Researchers conducted an in situ design-based research (DBR) study to investigate learner experience design (LXD) methods, deploying approaches of asynchronous video, course dashboards, and enhanced user experience. This mixed-methods study (N = 181) assessed associations of students’ social cognitive motivational traits (self-efficacy, task-value, self-regulation) influencing their learning behaviors (engagement, elaboration, critical thinking) resulting from LXD. Social cognitive motivational traits were positively predictive of learning behaviors. As motivational factors increased, students’ course engagement, usage of elaboration, and critical thinking skills increased. Self-efficacy, task-value, and self-regulation explained 31% of the variance of engagement, 47% of the explained variance of critical thinking skills, and 57% of the explained variance in the usage of elaboration. As a predictor, task-value beliefs increased the proportion of explained variance in each model significantly, above self-efficacy and self-regulation. Qualitative content analysis corroborated these findings, explaining how LXD efforts contributed to motivations, learning behaviors, and learning experience. Results suggest that mechanisms underpinning LXD and students’ learning behaviors are likely the result of dynamically catalyzing social cognitive motivational factors. The discussion concludes with the LXD affordances that explain the positive influences in students’ social cognitive motivational traits and learning behaviors, while also considering constraints for future iterations.