Content area

Abstract

The growing integration of generative artificial intelligence (GenAI) tools in higher education has potential to transform learning experiences. However, empirical research comparing GenAI-supported learning with traditional instruction lags behind these developments. This study addresses this gap through a controlled experiment involving 96 undergraduate computer science students in a Database Management course. Participants experienced either GenAI-supported or traditional instructions while learning the same concept. Data were collected through questionnaires, quizzes, and interviews. Analyses were grounded in self-determination theory (SDT), which posits that effective learning environments support autonomy, competence, and relatedness. Quantitative findings revealed significantly more positive learning experiences with GenAI tools, particularly enhancing autonomy through personalized pacing and increased accessibility. Competence was supported, reflected in shorter study times with no significant achievement differences between approaches. Students performed better on moderately difficult questions using GenAI, indicating that GenAI may bolster conceptual understanding. However, interviews with 11 participants revealed limitations in supporting relatedness. While students appreciated GenAI’s efficiency and availability, they preferred instructor-led sessions for emotional engagement and support with complex problems. This study contributes to the theoretical extension of SDT in technology-mediated learning contexts and offers practical guidance for optimal GenAI integration.

Details

1009240
Title
Blending Generative AI and Instructor-Led Learning: Empirical Insights on Student Motivation, Learning Experience, and Academic Performance in Higher Education
Author
Dizza, Beimel 1 ; Amzalag Meital 2 ; Zviel-Girshin Rina 1 ; Voloch Nadav 1 

 Faculty of Engineering, Ruppin Academic Center, Emek Hefer 4025000, Israel; [email protected] (R.Z.-G.); [email protected] (N.V.), The Center for Research in Technological and Engineering Education, Ruppin Academic Center, Emek Hefer 4025000, Israel 
 Faculty of Instructional Technologies, Holon Institute of Technology, Holon 5810201, Israel; [email protected], The Center for Research in Technological and Engineering Education, Ruppin Academic Center, Emek Hefer 4025000, Israel 
Publication title
Volume
15
Issue
11
First page
1480
Number of pages
19
Publication year
2025
Publication date
2025
Publisher
MDPI AG
Place of publication
Basel
Country of publication
Switzerland
Publication subject
e-ISSN
22277102
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-11-04
Milestone dates
2025-09-12 (Received); 2025-10-28 (Accepted)
Publication history
 
 
   First posting date
04 Nov 2025
ProQuest document ID
3275510585
Document URL
https://www.proquest.com/scholarly-journals/blending-generative-ai-instructor-led-learning/docview/3275510585/se-2?accountid=208611
Copyright
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-11-28
Database
2 databases
  • Coronavirus Research Database
  • ProQuest One Academic