Teachers who find using AI enjoyable, engaging and satisfying (intrinsic/interest value) may be more motivated to use it (theoretical argument).¶

Claim · All claims
Evidence · 1 study (2 entries) · theoretical r2 · q1
Currency · newest study 2024 · not yet checked against its sources · not reviewed by a person
Evidence quality · No study behind this claim is a peer-reviewed article with a DOI: it rests on an ERIC document (a report, conference paper or thesis). It is kept because 2 design pages cite it; treat it as a lead to check, not an established finding.

Subclaims¶

q1 i? The paper argues that when teachers find AI technologies enjoyable, engaging and satisfying, they may be more motivated to use them. → Yurt 2024 q1 i? The paper argues that designing new and innovative learning activities with AI can make teaching more enjoyable and increase teachers' intrinsic motivation to use AI. → Yurt 2024 (2)

Evidence¶

Yurt 2024¶

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

q1 · i? · theoretical · r2

Theoretical argument in the intrinsic/interest value section, with no new data: "When teachers find using AI technologies enjoyable, engaging, and satisfying, they may be more motivated" to use them.

"Teachers' intrinsic/interest values regarding the use of AI applications directly influence their motivation to use these technologies. When teachers find using AI technologies enjoyable, engaging, and satisfying, they may be more motivated to use these technologies."

Yurt 2024 (2)¶

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

q1 · i? · theoretical · r2

Theoretical argument offered as an example in the same section, with no data: teachers "can design new and innovative learning activities using AI technologies", which the paper says can raise intrinsic motivation.

"teachers can design new and innovative learning activities using AI technologies, making their teaching experiences more enjoyable and engaging. This situation can increase teachers' intrinsic motivation to use AI technologies."

Discussion¶

Related Claims¶

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• The article argues learning is a natural, enjoyable human process rather than one driven by pressure and anxiety — related
• Teachers who believe AI use will contribute to their professional success and identity (attainment value) may be more motivated to use it (theoretical argument). — related
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• 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). — related
• Teachers who perceive the challenges and barriers of using AI as high (cost) may be less motivated to use it (theoretical argument). — related
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• Effortful learning strategies posed a student motivation challenge at d.tech, which teachers addressed by explaining the underlying science directly to students — related
• In a randomised experiment, AI access raised students' enjoyment of learning (p = 0.063) with no statistically detectable effect on self-assessed knowledge or felt effectiveness — related
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• Evolutionary theory can inform more-enlightened teaching methods yielding more enjoyable and successful learning — related
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