Book Chapter

Daley, M., Bai, Z. , Borasi, R., Miller, D. Chapter 22, Machine Learning - a new lens for integrating computational thinking and science in the high school classroom.  Age of Inference: Cultivating a Scientific Mindset. Short P, Henson H, McConnell J, editors. Charlotte, NC: Information Age Publishing.

Peer Reviewed Journal Papers

Zhou, X., Gong, Y., Bai, Z. (2025). Co-Design Analogical and Embodied Representations with Children for Child-Centered AI Learning Experiences. International Journal of Human-Computer Studies (ijHCS). Special Issue on “Child-Centered AI”. Volume 199, May 2025, 103462. 1-15. [PDF]

Tang, J., Zhou, X., Wan, X., Daley, M., & Bai, Z. (2022). ML4STEM Professional Development Program: Enriching K-12 STEM Teaching with Machine Learning. International Journal of Artificial Intelligence in Education, 1-40. [PDF]

Bai, Z., Blackwell, A.F., Coulouris, G. (2015). Using Augmented Reality to Elicit Pretend Play for Children with Autism. (2015) IEEE Transactions on Visualization and Computer Graphics, vol.21, no.5, pages 598-610. (By invitation) [PDF]

Bai, Z., Blackwell, A.F. (2012). Analytic Review of Usability Evaluation in ISMAR. Interacting with Computers, 24(6), pages 450-460. [PDF]

Peer Reviewed Conference Papers

(to appear) Liu, X., Cheng, H., Chastel, G., Chastel, M., Bai. Z. CoSignPlay: A Collaborative Approach to Learning Non-Manual Signs in ASL for Hearing Families with Deaf Children. In Proceedings of the 27th International ACM SIGACCESS Conference on Computers and Accessibility. [PDF]

(to appear) Li, Y., Willis, A., Bai, Z. (2025). RhymASL: An Interactive Rhyming ASL Story Generator. In Proceedings of the 27th International ACM SIGACCESS Conference on Computers and Accessibility. [PDF]

Wu, S., Wang, H., Bai, Z. AGen: Personalized Analogy Generation through Large Language Model. In International Conference on Artificial Intelligence in Education (pp. 242-249). Cham: Springer Nature Switzerland. [PDF]

Zhou, X., Lyu, H., Sa, Y., Li, M., Sarkar, A., Luo, J., Daley, M., and Bai, Z. (2025, July). Empower Secondary School Teachers to Create ML-Supported Inquiry-Based Learning Activities. In International Conference on Artificial Intelligence in Education (pp. 150-164). Cham: Springer Nature Switzerland. [PDF]

Zhou, X., Gong, Y., Yu, Y., Zhang, Y., Smith, J., Bai, Z. Design AI for My Community: A Case Study of Collaborative Learning in a Freedom-to-Read Summer Camp. In Proceedings of the 19th International Conference of the Learning Sciences-ICLS 2025, pp. 1295-1299. International Society of the Learning Sciences. [PDF]

Ragone, G., Bai, Z., Good, J., Guneysu, A., Yadollahi, E., Child-centered Interaction and Trust in Conversational AI. 2025 Annual ACM Interaction Design and Children Conference (IDC’25) (pp. 1235–1238). [PDF]

Li, Y., Wang, H., Hossain, E., Mann M., Yu, J., Newman, K.S., Bao, A., Willis A., Kurumada, C., Hall, W., Bai, Z. Leveraging Usefulness and Autonomy: Designing AI-Mediated ASL Communication Between Hearing Parents and Deaf Children. 2025 Annual ACM Interaction Design and Children Conference (IDC’25) (pp. 512 - 526). [PDF]

Liu, X., Cheng, H., Bai, Z., Chastel, M., Chastel, G. (2025, April). An Educational Game Prototype for Avatar-based Non-Manual Sign Learning in American Sign Language. Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1-6). [PDF]

Zhou, X., Zhang, Y., Jiang, Y., Gong, Y., Zhang, C., Antle, N. A., Bai, Z. (2025, April).  Briteller: Shining a Light on AI Recommendation for Children. 2025 ACM CHI Conference on Human Factors in Computing Systems (pp. 1-30). [PDF]

Zhou, X., Zhou, Y., Gong, Y., Cai, Z., Qiu, A., Xiao, Q., Antle, A., Bai, Z. (2024, June). “Bee and I need diversity!” Break Filter Bubbles in Recommendation Systems through Embodied AI Learning. In Proceedings of the 23rd Annual ACM Interaction Design and Children Conference (pp. 44-61). [PDF]

Zhou, X., Xiong, P., Xiao, Q., Bai, Z. (2024, May). OptiDot: An Optical Interface for Children to Explore Dot Product and AI Recommendation. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1-7). [PDF]

Zhou, X., Tang, J., Lyu, H., Liu, X., Zhang, Z., Qin, L., Au, F., Sarkar, A., Bai, Z. (2024, May). Creating an authoring tool for K-12 teachers to design ML-supported scientific inquiry learning. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1-7). [PDF]

Gong, Y., Zhou, X., Zhou, Y., Luehmann, A., Han, Y., Bai, Z. (2024, June). Approaching “Filter Bubble” in Recommendation Systems: A Transformative AI Literacy Learning Experience. In Proceedings of the 18th International Conference of the Learning Sciences-ICLS 2024, pp. 490-497. International Society of the Learning Sciences. [PDF]

Zhou, X., Tang, J., Xiao, Q., Zhou Y., Bai, Z. (2024, June). Supporting Multidimensional Data Analysis for High-School Students in the Era of Machine Learning. In Proceedings of the 18th International Conference of the Learning Sciences-ICLS 2024, pp. 1255-1258. International Society of the Learning Sciences. [PDF]

Hossain, E., Newman, K., Bao, A., Mann, M., Kurumada, C., Hall, W., Bai, Z. (2023, November). Supporting ASL Communication Between Hearing Parents and Deaf Children. The 25th International ACM SIGACCESS Conference on Computers and Accessibility (pp. 1-5). [PDF]

Xu, E., Wang, H., & Bai, Z. (2023, April). Engage AI and Child in Explanatory Dialogue on Commonsense Reasoning. In Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems (pp. 1-8). [PDF]

Hossain, E., Cahoon, M., Liu, Y., Kurumada, C., and Bai, Z. (2022, October). Context-responsive ASL Recommendation for Parent-Child Interaction. The 24th International ACM SIGACCESS Conference on Computers and Accessibility (pp. 1-5). [PDF]

Zhou, X., Tang, J., Guo, B., Lyu, H., and Bai, Z. (2022, July). Challenges and Design Opportunities in Data Analysis for ML-Empowered Scientific Inquiry - Insights from a Teacher Professional Development Study. The International Society of the Learning Sciences Annual Meeting (ISLS)(pp. 847-854). [PDF]

Bai, Z., Codick, E.M., Tenesaca, A., Hu, W., Yu, X., Hao, P., Kurumada, C., Hall, W.  (2022, June). Signing-on-the-Fly: Technology Preferences to Reduce Communication Gap between Hearing Parents and Deaf Children. ACM Interaction Design and Children (IDC) Conference. [PDF]

Zhou, X., Tang, J., Bai, Z. (2021, June). “Now, I Want to Teach it for Real!”: Introducing Machine Learning as a Scientific Discovery Tool for K-12 Teachers. In International Conference on Artificial Intelligence in Education (pp. 486-499). Springer, Cham. (Best paper award nominee) (Best student paper award nominee) [PDF]

Wan, X., Tang, J., Zhou, X., Bai, Z. (2021, June). Exploratory Process Analysis of Teacher Learning of AI Integration through Collaborative Design. 5th Educational Data Mining in Computer Science Education (CSEDM) Workshop, Joint Proceedings of the Workshops at the International Conference on Educational Data Mining 2021. [PDF]

Zhou, X., Li, K., Munawar, A. M., Bai, Z. (2021, June). Scaffolding Design to Bridge the Gaps between Machine Learning and Scientific Discovery for K-12 STEM Education. In Interaction Design and Children (pp. 604-609). [PDF]

Sinha, T., Bai, Z., & Cassell, J. (2021, March). A Novel Multimodal Approach for Studying the Dynamics of Curiosity in Small Group Learning. https://doi.org/10.35542/osf.io/rfxwg [PDF]

Wan, X., Zhou, X., Ye, Z., Mortensen, C. K., & Bai, Z. (2020, June). SmileyCluster: supporting accessible machine learning in K-12 scientific discovery. In Proceedings of the Interaction Design and Children Conference (pp. 23-35). [PDF]

Zhou, X., Tang, J., Mushtaq, S., Wan, X. and Bai, Z. Empowering Teachers to Integrate Machine Learning into K-12 Scientific Discovery. International Workshop on Education in Artificial Intelligence K-12 (EduAI-20). [PDF]

Tenesaca, A., Oh, J. Y., Hu, W., Lee, C., Bai, Z. Augmenting Communication Between Hearing Parents and Deaf Children. In 2019 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct). [PDF]

Samrose, S., Chu,W., He, C., Gao, Y., Shahrin, S. S., Bai, Z. , Hoque, M. Visual Cues for Disrespectful Conversation Analysis. Eighth International Conference on Affective Computing and Intelligent Interaction, ACII 2019, Cambridge, UK. Sept. 3-5, 2019. [PDF]

Holmes, J. R., To, A., Zhang, F., Park, S. E., Ali, S., Bai, Z., Kaufman, G. & Hammer, J. (2019, April). A Good Scare: Leveraging Game Theming and Narrative to Impact Player Experience. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems (p. LBW0178). ACM. [PDF]

Paranjape, B., Ge, Y., Bai, Z., Hammer, J., Cassell, J. Towards automatic generation of peer-targeted science talk in a curiosity-evoking virtual agent. In Proceedings of the 18th International Conference on Intelligent Virtual Agents (pp. 71-78), November 5-8, Sydney, Australia, 2018. [PDF]

Ali, S., To, A., Bai, Z., Holmes, J., Fath, E., Kaufman, G., Hammer, J. (2018). Transition from Goal Driven Game Design to Game Driven Goal Delineation in Tandem Transformational Game Design. In Proc. International Academic Conference on Meaningful Play 2018. [PDF]

Paranjape, B., Bai, Z., & Cassell, J. (2018, June). Predicting the Temporal and Social Dynamics of Curiosity in Small Group Learning. In International Conference on Artificial Intelligence in Education (pp. 420-435). Springer, Cham. [PDF]

Sinha, T., Bai, Z., Cassell, J. (2017) A New Theoretical Framework for Curiosity for Learning in Social Contexts. 12th European Conference on Technology Enhanced Learning. [Accept rate: 25.3%] (Best paper award nominee) [PDF]

Sinha, T., Bai, Z., Cassell, J. (2017) Curious Minds Wonder Alike: Studying Multimodal Behavioral Dynamics to Design Social Scaffolding of Curiosity. 12th European Conference on Technology Enhanced Learning. [Accept rate: 25.3%] [PDF]

Bai, Z., Blackwell, A.F., Coulouris, G. (2015). Exploring Expressive Augmented Reality: The FingAR Puppet System for Social Pretend Play. In Proc. ACM CHI Conference on Human Factors in Computing Systems, Seoul, Republic of Korea, April 18-23, 2015, pages 1035-1044. [Accept rate: ~23%] [PDF]

Bai, Z., Blackwell, A.F., Coulouris, G. (2013). Through the Looking Glass: Pretend Play for Children with Autism. In Proc. 12th International Symposium on Mixed and Augmented Reality (ISMAR), 1-4 October 2013, Adelaide, Australia, pages 49-58. [Accept rate: ~3%](Best paper award nominee) [PDF]

Poster and Workshop Papers

Bai, Z., Blackwell, A.F. (2013). See-through Window vs. Magic Mirror: A Comparison in Supporting Visual-Motor Tasks. In Proc. 12th International Symposium on Mixed and Augmented Reality (ISMAR), pages 239-240. [PDF]

Bai, Z., Blackwell, A.F., Coulouris, G. (2013). Can We Augment Reality with “Mental Images” to Elicit Pretend Play? A Usability Study. In Proc. ACM CHI Extended Abstract 2013, 27 April -2 May 2013, Paris, France, pages 1-6. [PDF]

Bai, Z., Blackwell, A.F., Coulouris, G. (2012). Making Pretense Visible and Graspable: An Augmented Reality Approach to Promote Pretend Play. In Proc. 11th IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 5-8 November 2012, Atlanta, Georgia, USA, pages 267-268. [Accept rate: ~28%] [PDF]

Bai, Z. (2012). Augmenting Imagination for Children with Autism. In Proc. 11th International Conference on Interaction Design and Children (IDC), 12-15 June 2012, Bremen, Germany, pages 327-330. [Accept rate: ~31%] [PDF]