Siying (Belle) Li

• Purdue University — Ph.D. in Learning Design and Technology, 2026
• Purdue University — Graduate Certificate in AI in Education, 2026
• Carnegie Mellon University — Certificate of Completion, 2026 LearnLab Summer School, Intelligent Tutoring Systems Track, 2026
• Indiana University Bloomington — Master’s degree in Instructional Systems Technology, 2020

Purdue University, 2026–Present
Ross-Lynn Postdoctoral Research Scholar, Department of Curriculum and Instruction. Conducts research on AI in education; supports college-wide AI initiatives; contributes to research, publications, grant development, and the design and evaluation of educational AI tools.

Indiana University Bloomington, 2021–2023
Visiting Faculty, Pedagogy Specialist, and Tutor Coordinator, Department of East Asian Languages and Cultures. Designed tutor onboarding and professional development, developed curricula and assessments, supported more than 200 tutors, conducted program evaluation, and taught language and culture courses.

Hilink LLC, 2020–2021
Product Manager and Curriculum Coordinator.

CourseNetworking (CyberLab), 2020–2021
Instructional and Research Manager.

• Best Practices in AIED: Scenarios-Driven Educational Transformation, WDEA Certificate Recognition, 2026
• Frank B. DeBruicker Graduate Award in Educational Technology, Purdue University, 2026
• Dean’s Dissertation Fellowship, Purdue University College of Education, 2026
• Global Smart Education Innovation – Research Innovation Prize, Global Smart Education Conference, 2025
• AECT Systems Thinking and Change Outstanding Journal Article Award, 2025
• Dean’s Doctoral Fellowship, Purdue University, 2023–2027

• American Educational Research Association (AERA), 2023–Present
• Association for Educational Communications and Technology (AECT), 2023–Present

Li, B., Exter, M., Feng, W., Tang, G., & Xu, K. (2026). A systematic review of language educators’ practices and development with GenAI. International Journal of Artificial Intelligence in Education, 36(1–2), 100010. https://doi.org/10.1016/j.ijaied.2026.100010

Li, B., & Lowell, V. L. (2026). AI-generation literacy. In L. McCallum & D. Tafazoli (Eds.), The Palgrave encyclopedia of computer-assisted language learning. Palgrave Macmillan. https://doi.org/10.1007/978-3-031-51447-0_260-1

Li, B., Zhang, Z., Lowell, V. L., Wang, C., & Bonk, C. J. (2025). Development and validation of the PA-SDA Scale: Measuring personal attributes in AI-integrated self-directed language learning. System, 133, 103793. https://doi.org/10.1016/j.system.2025.103793

Li, B., Tan, L. Y., Wang, C., & Lowell, V. L. (2025). Two years of innovation: A systematic review of empirical generative AI research in language learning and teaching. Computers & Education: Artificial Intelligence, 9, 100445. https://doi.org/10.1016/j.caeai.2025.100445

Li, B., & Hikmatilla, U. (2025). Getting viral on social media: Exploring Chinese language EduTubers’ perceptions and practices. Innovation in Language Learning and Teaching, 19, 1–25. https://doi.org/10.1080/17501229.2025.2505700

Aslan, S., Alyuz, N., Li, B., Durham, L. M., Shi, M., Sharma, S., & Nachman, L. (2025). An early investigation of collaborative problem solving in conversational AI-mediated learning environments. Computers & Education: Artificial Intelligence, 8, 100393. https://doi.org/10.1016/j.caeai.2025.100393

Yang, M., Jiang, S., Li, B., Herman, K., Luo, T., Moots, S. C., & Lovett, N. (2025). Analysing nontraditional students’ ChatGPT interaction, engagement, self-efficacy and performance: A mixed-methods approach. British Journal of Educational Technology. Advance online publication. https://doi.org/10.1111/bjet.13588

Li, B., Lowell, V. L., Wang, C., & Li, X. (2024). A systematic review of the first year of publications on ChatGPT and language education. Computers & Education: Artificial Intelligence, 7, 100266. https://doi.org/10.1016/j.caeai.2024.100266

Li, B., Bonk, C. J., Wang, C., & Kou, X. (2024). Reconceptualizing self-directed learning in the era of generative AI: An exploratory analysis of language learning. IEEE Transactions on Learning Technologies, 17(3), 1515–1529. https://doi.org/10.1109/TLT.2024.3386098

Li, B., Wang, C., Bonk, C. J., & Kou, X. (2024). Exploring inventions in self-directed language learning with generative AI: Implementations and perspectives of YouTube content creators. TechTrends. https://doi.org/10.1007/s11528-024-00960-3

NSF Collaborative Research: T3-CIDERS — A Train-the-Trainer Approach to Fostering CI- and Data-Enabled Research in Cybersecurity. National Science Foundation, $1,000,000, 2023–2027.
Lead PIs: Hongyi Wu and Masha Sosonkina.
Role: Project collaborator; contributed to research evaluation design, instructional design, training-material development, and pedagogy-focused professional development.

AI-Powered Personalized Support for Working Adult Online Learners. Purdue University VIP Seeding Solutions, $2,000, 2026.
Lead PIs: Qiang Qiu and Wei Zakharov.
Partner: Purdue Global.
Role: Mentor; contributed to instructional-design framing, evaluation design, and proposal development.

TRAIN-AI: A Cascading Train-the-Trainer Model for K–16 AI Competency and Tool Development. Michael de Miranda EMERGE Grant, Texas A&M University College of Education and Human Development, $50,000, 2026–2027.
PI: Mohan Yang. Co-PIs: Seung Won Yoon, Chih-Pu Dai, Cheng Zhang, Nolan Lovett, and Siying (Belle) Li. Role: Co-PI; supports AI-tool development, curriculum design, and instructional design across project phases.