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ZENODO
Article . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
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AI in education: Unlocking college student engagement in the digital learning era

Authors: Geroche, Joefrey B.; Guay, Farra Jean G.;

AI in education: Unlocking college student engagement in the digital learning era

Abstract

This study investigated the relationships between independent variables Instructor Knowledge, Instructor Support, Ease of Access, Availability of AI Resources, Perceived Value, and Institutional Response and their impact on college student engagement in AI-driven educational contexts. Using a quantitative design, the study gathered data from 572 college students at universities in the Philippines through a structured Likert scale questionnaire on their perceptions and experiences of AI in education. Analysis through multiple regression revealed that Instructor Knowledge did not significantly influence engagement, suggesting that mere expertise may not suffice without strong interpersonal relationships. In contrast, strong Instructor Support positively correlated with student engagement, emphasizing the critical role that encouragement and guidance play in fostering student involvement. Although Ease of Access to AI tools approached significance, the availability of resources negatively correlated with engagement, indicating that an abundance of choices may overwhelm students and lead to disengagement. The Perceived Value of student feedback is positively related to engagement, underscoring the importance of institutions acknowledging and acting on student input to enhance their educational experiences. Furthermore, timely Institutional Response significantly promoted engagement by fostering transparent communication between students and institutions. These results imply that to enhance student engagement effectively, educational institutions should focus on strengthening instructor support, simplifying access to AI tools, curating resources thoughtfully, and actively responding to student feedback. This study offers important insights into AI-enhanced education, highlighting factors that can boost engagement, inform teaching practices, and influence future learning environments. By addressing these elements, institutions can create a more interactive and supportive educational experience for students in a digital learning landscape.

Related Organizations
Keywords

Instructor support, Student engagement, Multiple regression analysis, Accessibility, AI in education, Quantitative research, Feedback

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average
Green