A Technology Acceptance Model-Based Regression Analysis of Teachers' Perception and Utilization of Generative Artificial Intelligence Tools in Lesson Design and Assessment
Year: 2026
Type: conference-paper
Study design: Observational Study
Abstract: This paper investigated teachers' perception and utilization of generative artificial-intelligence (AI) tools in lesson design and assessment within Philippine higher-education institutions. The study adopted the Technology Acceptance Model (TAM) to examine how perceived usefulness, ease of use, attitude toward use, and ethical concerns influence the actual use of generative AI in instructional contexts. A descriptive-correlational design was employed, and data were collected from 384 faculty members through a validated self-administered online questionnaire. Descriptive statistics, Pearson correlation, and multiple regression were applied for analysis. Results indicated that teachers generally agreed on the usefulness and ethical integration of AI tools and strongly agreed on their utilization for teaching and assessment tasks. Lesson design and assessment were positively affected. Regression analysis revealed that perception and utilization significantly predicted lesson outcomes, explaining 86.6% of the variance. These findings highlight that teachers' beliefs and confidence in AI strongly drive effective pedagogical integration.
Institutions: UCSI University, National University, NU Lipa
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W7202286334