Enhancing Logical Reasoning through AI-Assisted Learning: The Mediating Role of Performance Expectancy in AI Tool Adoption
Year: 2026
Type: conference-paper
Study design: Observational Study
Abstract: Artificial intelligence (AI) is increasingly integrated into higher education, yet its role in fostering logical reasoning remains contested. While AI tools offer efficiency, clarity, and diverse perspectives that can scaffold students’ reasoning processes, concerns about dependency, misinformation, and diminished originality persist. This study investigates how facilitating conditions, performance expectancy, and usage behavior interact to shape students’ adoption of AI tools in logic education. A quantitative correlational design with mediation analysis was employed using a sample of 168 students. Facilitating conditions were conceptualized as students’ perceived responsibility to verify AI-generated content, performance expectancy as their belief that AI tools enhance argument analysis, and usage behavior as the actual application of AI in academic tasks. Results indicate that facilitating conditions significantly predict performance expectancy (β = 0.276, p < .001), which in turn strongly predicts usage behavior (β = 0.486, p < .001). Mediation analysis confirmed a significant indirect effect (β = 0.134, p < .001), with performance expectancy explaining approximately 44% of the total effect of facilitating conditions on usage behavior. These findings highlight the dual importance of structural supports and perceptual factors in promoting responsible AI integration. Facilitating conditions not only provide the necessary infrastructure but also enhance students’ confidence in AI’s educational value, which emerges as a critical driver of adoption. The study contributes to the Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT) literature by demonstrating partial mediation. Implications extend to curriculum design, institutional policy, and pedagogy, offering a framework for balanced AI adoption that strengthens reasoning while mitigating risks of dependency and diminished originality.
Institutions: Malayan Colleges Laguna, Mapúa University
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W7204564074