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Artificial Intelligence Acceptance in Science Teaching: A Path Analysis Using the UTAUT Model

Year: 2025

Type: article

Abstract: The study aimed to examine the acceptance of artificial intelligence (AI) in science teaching using Unified Theory of Acceptance and Use of Technology (UTAUT) model.This study used a quantitative, non-experimental survey design and involved 345 secondary teacher who were teaching science across Sabah.The structural model elucidated that independent variablenamely, perfomance expectancy, effort expectancy, social influences, facilities conditionexerted a statistically significant and positive influence on intention to use AI in science teaching.The results indicated that facilities condition is the dominant predictive factor.Collectively, this model effectively accounted for 78.9% of the variance in the intention of science teachers in Sabah to adopt AI.The study offers insights to enhance AI acceptance among science teachers in Sabah, fostering innovation in education.

Source: International Journal of Academic Research in Business and Social Sciences

DOI: 10.6007/ijarbss/v15-i11/26928

Authors: Aminah Jekri, Crispina Gregory K Han, Nur Farha Shaafi

Institution: Universiti of Malaysia Sabah

Language: English

Topic: Technology Adoption and User Behaviour

Subfield: Information Systems and Management

Field: Decision Sciences

Domain: Social Sciences

SDG: Quality education

Open Access status: diamond

OpenAlex ID: W4416101551