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Research Projects

We engage in multidisciplinary, iterative, and evidence-based research and development with diverse stakeholders to create new technologies, activities, practices and programs for real-world impact in homes, schools, afterschool programs and online communities. A list of publications for these projects can be found here.

Selected Publications

AI Education Peer-reviewed Research Articles and Preprints

Personal Robots Group - 2020

Can Children Emulate a Robotic Non-Player Character’s Figural Creativity?

Ali, S., Park, HW., & Breazeal, C. (2020). Can Children Emulate a Robotic Non-Player Character’s Figural Creativity?. Proceedings of the Annual Symposium on Computer-Human Interaction in Play (CHI PLAY ’20).

MIT App Inventor - 2020

Using Transfer Learning, Spectrogram Audio Classification, and MIT App Inventor to Facilitate Machine Learning Understanding

Bhatia, N. & Lao, N. (2020). Using Transfer Learning, Spectrogram Audio Classification, and MIT App Inventor to Facilitate Machine Learning Understanding. International Conference on Computational Thinking Education 2020 (CTE2020).

MIT App Inventor - 2020

Experiences from Teaching Actionable Machine Learning at the University Level through a Small Practicum Approach

Lao, N., Lee, I., & Abelson, H. (2020). Experiences from Teaching Actionable Machine Learning at the University Level through a Small Practicum Approach. International Conference on Computational Thinking Education 2020 (CTE2020).

Personal Robots Group - 2020

Escape!Bot: Child-Robot Interaction to Promote Creative Expression During Gameplay

Devasia, N., Ali, S., & Breazeal, C. (2020). Escape!Bot: Child-Robot Interaction to Promote Creative Expression During Gameplay. Extended Abstracts of the 2020 Annual Symposium on Computer-Human Interaction in Play (CHI PLAY ’20 EA).

MIT App Inventor - 2020

Engaging Teachers to Co-Design Integrated AI Curriculum for K-12 Classrooms

Jessica Van Brummelen, Phoebe Lin, (2020 in submission). Engaging Teachers to Co-Design Integrated AI Curriculum for K-12 Classrooms..

MIT App Inventor - 2020

Designing AI Learning Experiences for K-12

Xiaofei Zhou, Jessica Van Brummelen, Phoebe Lin (2020 in submission). Designing AI Learning Experiences for K-12: Emerging Works, Future Opportunities and a Design Framework..

MIT App Inventor - 2019

CONVO: What does conversational programming need?

Van Brummelen, J., Weng, K., Lin, P., & Yeo, C. (2020). CONVO: What does conversational programming need?. 2020 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 1-5.

MIT App Inventor & Personal Robots Group - 2019

Zhorai: Designing a Conversational Agent for Children to Explore Machine Learning Concepts

Lin, P., Van Brummelen, J., Lukin, G., Williams, R. & Breazeal, C. (2020). Zhorai: Designing a Conversational Agent for Children to Explore Machine Learning Concepts. Proceedings of the AAAI Conference on Artificial Intelligence 34, 13381—13388.

Personal Robots Group - 2020

Teaching and learning with children: Impact of reciprocal peer learning with a social robot on children’s learning and emotive engagement

Chen, H., Park, HW., & Breazeal, C. (2020). Teaching and Learning with Children: Impact of Reciprocal Peer Learning with a Social Robot on Children’s Learning and Emotive Engagement. Computers & Education, 150(8).

Personal Robots Group - 2020

Impact of Interaction Context on the Student Affect-Learning Relationship in Child-Robot Interaction

Chen, H., Park, HW., Zhang, X., & Breazeal, C. (2020). Impact of Interaction Context on the Student Affect-Learning Relationship in Child-Robot Interaction. Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction, 389–397.

MIT App Inventor - 2019

PIC: A Personal Image Classification Webtool for High School Students

Tang, D., Utsumi, Y., & Lao, N. (2019). PIC: A Personal Image Classification Webtool for High School Students. Proceedings of the 2019 IJCAI EduAI Workshop.

MIT App Inventor - 2019

A Deep Learning Practicum: Concepts and Practices for Teaching Actionable Machine Learning at the Tertiary Education Level

Lao, N., Lee, I., & Abelson, H. (2019). A Deep Learning Practicum: Concepts and Practices for Teaching Actionable Machine Learning at the Tertiary Education Level. IATED2019 Proceedings (12th International Conference of Education, Research and Innovation).

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