A data-driven evaluation of the grant program for excellence in learning and teaching (Pelt)

AI-leveraged insights from faculty, students, and academic metrics

Bibliographic Data

ID22167238
AuthorsAhmad Abdul-Wahhab Shahba (0000-0003-4509-8219, King Saud University), Saud Alkathiri (King Saud University), Elham Alsadoon (0000-0002-3081-7113, King Saud University), Walid Soufan (0000-0002-6273-2050, King Saud University, corresponding author)
Year2025
Volume10
Publication date2025-05-30
Open AccessYes
TypeARTICLE
VenueFrontiers in Education (JOURNAL)
Journal identifiersISSN: 2504-284X • E-ISSN: 2504-284X
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/feduc.2025.1571810
OpenAlexW4410893007
LanguageEN
References cited43

Background The landscape of higher education is evolving with an emphasis on teaching excellence and student-centered learning, driven by technological advancements and societal changes. This study aimed to comprehensively evaluate the impact of the grant Program for Excellence in Learning and Teaching (PELT) at King Saud University, the first of its kind in Saudi Arabia. Methods Using a mixed-methods approach, the research design combined quantitative and qualitative data collection and analysis techniques. Faculty and student surveys were conducted to assess the program’s impact on teaching practices, student engagement, and skills development. Additionally, student academic performance data, including self-reported PELT course grades and university-reported final exam scores, were analyzed. The study examined the influence of various factors, such as academic discipline and grant theme on the program’s outcomes. Textual feedback from faculty and students was subjected to AI-assisted thematic and sentiment analysis to uncover key themes and insights. Results The PELT program showed a positive impact on faculty’s pedagogical skills, teaching methods, and perceptions of student learning. Faculty members showed a stronger preference for the “Student Professional Development” grant theme, while students valued the “Curriculum and Course Content Development” and “Excellence in Teaching and Assessment Strategies” themes more. The student textual feedback highlighted the need for more dynamic, student-focused, and practically oriented educational approaches. The innovative use of AI-powered sentiment analysis offered valuable complementary insights into student experiences, complementing the traditional survey-based methods. The analysis of student-reported academic performance revealed that PELT course grades were slightly higher than overall GPA, with the Humanities discipline demonstrating significant positive impacts. Importantly, the university-reported score analysis further highlighted that courses emphasizing student-faculty interactions and student-professional development (T2 and T3 themes) showed significantly higher scores in the PELT group compared to the control group, while the T1 (Curriculum and Course Content Development) theme showed the opposite. Conclusion The study’s findings underscore the importance of aligning educational interventions with approaches that prioritize active learning, collaborative experiences, and authentic student-faculty interactions. Furthermore, this study provides a robust foundation for assessing the impact of faculty development programs and guiding data-driven decisions to enhance the quality of higher education

Data science · Engineering management · Excellence · Knowledge management · Mathematics education · Medical education · Political science · Clinical Reasoning and Diagnostic Skills · Computer Science · Engineering · Health and Medical Research Impacts · Innovations in Medical Education · Medicine · Psychology

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