Yaoting Chen
Papers
1
Total Citations
6
H-Index
1
About
Yaoting Chen is a rising scholar at the intersection of artificial intelligence in education (AIED), technical education, and motivational psychology. Their most-cited work, "Integrating Motivation Theory into the AIED Curriculum for Technical Education," examines how curriculum design—specifically the integration of motivational frameworks—can significantly enhance learning outcomes and sustain learners’ intentions to pursue AI studies. This research further explores the moderating role of computer self-efficacy, offering nuanced insights into how individual differences shape educational technology effectiveness. With 6 citations on a recent 2025 publication, Chen’s work is gaining traction for addressing a critical gap: moving beyond simply deploying AI tools to strategically designing curricula that foster both competence and continued engagement. By bridging motivation theory with technical pedagogy, Chen provides actionable frameworks for educators and instructional designers aiming to improve AI literacy and retention in technical fields. Their contributions are particularly relevant as AI education expands globally, highlighting the need for evidence-based, learner-centered approaches. Chen’s research promises to shape how future technical curricula are built—not just to teach AI, but to inspire lifelong learning in it.
Research Focus
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Top Papers
- 1