Supports to Raise Teachers' Expectancy and Value and Lower Cost for AI Use¶

Strategy · All strategies
Evidence · no claims cited

Description¶

A set of support measures the paper recommends for teachers adopting AI applications, repeated across its expectancy, value and cost sections. They include "providing teachers with sufficient training and support in using AI technologies, offering professional development opportunities, and recognizing their successes in using technology", showing benefits and successful examples, providing resources, and creating a community where teachers share experiences and learn from each other.

Design Implications¶

Context¶

Requirements¶

• Training and support in using AI technologies, plus professional development opportunities, as the paper recommends for expectancy and cost.
• Showing teachers "the potential benefits and successful examples of AI technologies in education" to raise attainment and utility values.
• Providing resources and support for using AI applications.
• "creating a community where teachers can share their experiences and learn from each other".

Constraints¶

• These are recommendations derived from theory; the paper does not test whether any of them raise teachers' expectancy or value.

Target Learners¶

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

Target Learning Goals¶

• Higher expectancy and value, and lower perceived cost, for using AI applications in teaching

Related Strategies¶

• Professional Development
• Professional Learning Communities
• Technology Integration
• Expectancy Value Framework For Teacher Ai Use Motivation
• Support faculty AI literacy through needs assessment, targeted training, teaching resources, and communities of practice
• Embed AI policy literacy, peer-led communities of practice, and shared AI resources into professional development

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