Exploring Prospective Teachers' Intentions for Artificial Intelligence Integration in Education: The Role of Motivation

Saved in:
Bibliographic Details
Title: Exploring Prospective Teachers' Intentions for Artificial Intelligence Integration in Education: The Role of Motivation
Language: English
Authors: Eyüp Yurt (ORCID 0000-0003-4732-6879), Ismail Kasarci (ORCID 0000-0002-4686-3106)
Source: AERA Open. 2025 11(1).
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: http://sagepub.com
Peer Reviewed: Y
Page Count: 18
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Tests/Questionnaires
Education Level: Higher Education
Postsecondary Education
Descriptors: Student Motivation, Preservice Teachers, Artificial Intelligence, Technology Integration, Intention, Value Judgment, Costs, Expectation, Gender Differences, Instructional Program Divisions, Incidence, Foreign Countries
Geographic Terms: Turkey
ISSN: 2332-8584
Abstract: Understanding motivational drivers behind prospective teachers' artificial intelligence (AI) integration intentions is critical. While prior models such as the technology acceptance model overlook motivational dynamics, this study used expectancy-value theory to assess how expectancy, attainment, utility, intrinsic value, and cost shape intentions. Data from 454 prospective teachers were analyzed via structural equation modeling using the Behavioral Intention Scale and the Questionnaire of Artificial Intelligence Use Motives. Utility value ([beta] = 0.29, p < 0.001) was the strongest predictor, followed by cost ([beta] = -0.27), intrinsic value ([beta] = 0.25), attainment ([beta] = 0.21), and expectancy ([beta] = 0.10). The model explained 62% of variance in behavioral intention. Control variables, including gender, class level, and AI usage frequency, significantly influenced intentions. Findings suggested that teacher education programs should enhance AI's perceived utility, address implementation costs, and strengthen expectancy through training to foster adoption. Emphasizing AI's practical relevance within supportive environments can bridge its potential with classroom integration.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1494435
Database: ERIC
Be the first to leave a comment!
You must be logged in first