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Congratulations Deelip Mhaske, who successfully defended his dissertation proposal on June 23, 2026.
The title of Deelip's dissertation is, "ARTIFICIAL INTELLIGENCE ADOPTION AND STUDENT PERFORMANCE IN U.S. EDUCATION: A UTAUT META-ANALYSIS."
The abstract of this study follows:
Overview of Problem:The rapid adoption of AI technologies in U.S. K–12 and higher education has created opportunities to improve student learning and performance. However, there is limited consolidated evidence regarding the effectiveness of AI applications, the factors influencing their adoption, and their impact on educational outcomes such as academic achievement, engagement, retention, and critical thinking. This study addresses the need to better understand how AI technologies affect student performance and what conditions support successful implementation.
Research Purpose: The purpose of this study is to examine the role of AI technologies in student performance across U.S. K–12 and higher education settings from 2021–2026. Guided by the Unified Theory of Acceptance and Use of Technology (UTAUT), the study seeks to identify the types of AI applications used, evaluate their effects on student outcomes, and explore the facilitators and barriers influencing AI adoption and use in educational environments.
Research Design: This study employs a quantitative meta-analysis research design. Existing empirical studies published between 2021 and 2026 are systematically reviewed and synthesized to evaluate the overall impact of AI technologies on student performance and technology acceptance factors.
Sample: The sample consists of peer-reviewed research studies conducted in U.S. K–12 schools and higher education institutions between 2021 and 2026 that examine AI technologies and student performance outcomes.
Data Collection: Data are collected through a systematic review of academic databases, including peer-reviewed journal articles, conference proceedings, and relevant scholarly publications. Extracted data include AI application type, educational setting, sample characteristics, UTAUT variables, and reported student performance outcomes.
DISSERTATION CHAIR: Dr. Peter F. Troiano
COMMITTEE MEMBERS: Dr. Nora C.R. Broege Dr. Gerald Ardito
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