Biography
Shiyan Jiang is a learning scientist and interdisciplinary researcher whose work lies at the intersection of artificial intelligence (AI), education, and identity. Her research focuses on two interconnected strands: supporting teachers from diverse disciplinary backgrounds to integrate AI across subjects and designing AI tools that meaningfully enhance teaching and learning. Across both strands, she explores how learners negotiate their sense of self in relation to disciplinary knowledge, digital tools—especially AI—and future possibilities. Through design-based research, she aims to create learning experiences where learners not only acquire new knowledge but also envision themselves in new roles—as critical thinkers, creators, and informed participants in an AI-driven world.
Research Interests and Current Projects
Currently funded research includes:
- StoryQII (High school AI education; 2023–2026; NSF): Collaborative Research: DTI: Integrating Language-Based AI Across the Curriculum to Create Diverse Pathways to AI-Rich Careers
- i-SAIL (Middle school AI education; 2024–2028; NSF): Investigation of Students’ Learning, Interest, and Career Aspirations in an Integrated Science and Artificial Intelligence Learning Environment
- ElementaryAI (Elementary AI education): Leveraging AI Innovation to Enhance School-Wide Literacy Through Active Learning in Montgomery County, NC, Elementary Schools
- CTI (AI tool for math learning; 2024–2027; NSF): Learning by Teaching with Constructive Tutee Inquiry for Robust Learning in Algebra
- Youth-Led Measurement Initiatives: Quantifying and Advocating for More Welcoming Middle School Learning Environments (Middle school data science education; 2025-2026; Spencer Vison Grant)
Previously funded research includes:
- StoryQI (High school AI education; 2020–2024; NSF): Narrative Modeling with StoryQ: Integrating Mathematics, Language Arts, and Computing to Create Pathways to Artificial Intelligence Careers
- Playbook (Middle school data science education; 2023–2024; New Venture Fund): Institutional Opportunities to Belong: A Playbook for Putting Middle Schoolers’ Policy Insights into Motion
- LASERII (Learning analytics training for researchers and practioners; 2023–2025; NSF):Collaborative Research: BCSER: Broadening the Use of Learning Analytics in STEM Education Research
- LASERI (Learning analytics training for researchers and practioners; 2020–2024; NSF): Learning Analytics in STEM Education Research Institute
- Be the Dataset (Undergraduate data science education; 2020–2025; NSF): Enhancing Undergraduate Learning About Biomechanics and Data Science Through Augmented Reality and Self-motion Data
- ADAPT (Undergraduate data science education; 2023–2025; NSF): Creating Diverse Data Science Learning Pathways
Journal Editorial Boards
Educational Technology Research and Development (ETRD)
Editorial Board
Journal of Science Education and Technology (JOST)
Editorial Board