Expectancy-Value Framework for Teachers' Motivation to Use AI Applications

Theory · All theories
Evidence · 9 claims (8 for, 1 against) · 5 studies (2 associational, 1 causal, 1 qualitative, 1 theoretical), q1–q3 · 0 of 5 report an effect size · 9 claims rest on one study

Description

A theoretical application of Expectancy-Value Theory to why teachers do or do not adopt AI applications in education. The paper holds that "teachers' motivation to use AI technologies in the classroom is shaped by their beliefs about how successfully they can use these technologies (expectancy)" and by their perceptions of the technologies' significance (value), with value split into attainment, utility, intrinsic/interest value, and cost.

Design Implications

Context

Requirements

• The value component is treated as four subcomponents: "attainment value, utility value, intrinsic/interest value, and cost", each examined for its impact on teachers' motivation to use AI applications.

Constraints

• The paper is a theoretical examination and reports no data; it proposes that future research examine the specific factors influencing teachers' expectancy and value components, and that "longitudinal studies can provide valuable insights into how teachers' motivations to use AI technologies evolve over time".

Target Learners

• In-service teachers considering the use of AI applications in their classrooms

Target Learning Objectives

• Adoption and effective classroom use of AI applications by teachers
• Design of educational policies and teacher training programs for AI integration

Claims

• Teacher Expectancy Beliefs Shape Motivation To Use Ai [+W]
• Teacher Attainment Value Increases Motivation To Use Ai [+W]
• Teacher Utility Value Increases Motivation To Use Ai [+W]
• Teacher Intrinsic Interest Value Increases Motivation To Use Ai [+W]
• Teacher Perceived Cost Reduces Motivation To Use Ai [+W]
• Teacher confidence fully mediates the relationship between institutional support and attitudes toward AI adoption [+W]
• Teacher confidence strongly predicts favorable attitudes toward AI adoption, while the direct effect of support on attitudes is not significant [+W]
• Educators report affective costs of AI-related grading, including derealisation, exhaustion, and burnout [-W]
• Teachers rate AI-interaction training as useful and relevant and report positive adoption intentions [+W]

The evidence by question

• Do teachers who are more confident they can use AI well (expectancy) hold more favourable attitudes towards it and use it more? Teachers' expectancy beliefs about successfully using AI applications shape their motivation to use them (theoretical argument). [+W]
• Do teachers who see AI as useful, enjoyable or important to their work intend to use it more, and does that intention become use? Teachers who believe AI will help them reach professional goals and improve students' learning outcomes (utility value) may be more motivated to use it (theoretical argument). [+W]
• Do perceived costs and risks of AI (effort, output quality, threats to students' thinking) hold teachers back from using it? Teachers who perceive the challenges and barriers of using AI as high (cost) may be less motivated to use it (theoretical argument). [+W]

Related Theories

• Expectancy Value Theory
• Motivation
• Technology Integration
• Self Efficacy Theory

Examples

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Key Sources

• Yurt, E. (2024). Theoretical Examination of Teachers' Motivations for Using Artificial Intelligence Applications in Education: Expectancy-Value Theory Perspective. In M. S. Ozturk, A. Kaban, & M. Unal (Eds.), Proceedings of ICSES 2024-- International Conference on Studies in Education and Social Sciences (pp. 149-158), Istanbul, Turkiye. ISTES. https://eric.ed.gov/?id=ED673212

Page metadata

Field	Value
type	theory
title	Expectancy-Value Framework for Teachers' Motivation to Use AI Applications
description	A theoretical application of Expectancy-Value Theory to why teachers do or do not adopt AI applications in education.
status	review
canonical	True
generated	by claude/unspecified on 2026-09-24
trust	unverified — no one has confirmed this page's content
sources	1 — yurt-2024

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