Bradford Mott Mott, B., Gupta, A., Vandenberg, J., Chakraburty, S., Ottenbreit-Leftwich, A., Hmelo-Silver, C., … Lester, J. (2024). AI Planning is Elementary: Introducing Young Learners to Automated Problem Solving. PROCEEDINGS OF THE 2024 CONFERENCE INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION, VOL 2, ITICSE 2024, pp. 811–811. https://doi.org/10.1145/3649405.3659503 Feng, C., Bae, H., Glazewski, K., Hmelo-Silver, C. E., Brush, T. A., Mott, B. W., … Lester, J. C. (2024). Exploring facilitation strategies to support socially shared regulation in a problem-based learning game. EDUCATIONAL TECHNOLOGY & SOCIETY, 27(3), 318–334. https://doi.org/10.30191/ETS.202407_27(3).SP08 Vandenberg, J., & Mott, B. (2023). "AI teaches itself": Exploring Young Learners' Perspectives on Artificial Intelligence for Instrument Development. PROCEEDINGS OF THE 2023 CONFERENCE ON INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION, ITICSE 2023, VOL 1, pp. 485–490. https://doi.org/10.1145/3587102.3588778 Bae, H., Feng, C., Glazewski, K., Hmelo-Silver, C. E., Chen, Y., Mott, B. W., … Lester, J. C. (2023, November 8). Co-designing a Classroom Orchestration Assistant for Game-based PBL Environments. TECHTRENDS. https://doi.org/10.1007/s11528-023-00903-4 Mott, B., Gupta, A., GlazewskiAnne, K., Ottenbreit-Leftwich, A., Hmelo-Silver, C., Scribner, A., … Lester, J. (2023). Fostering Upper Elementary AI Education: Iteratively Refining a Use-Modify-Create Scaffolding Progression for AI Planning. PROCEEDINGS OF THE 2023 CONFERENCE ON INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION, ITICSE 2023, VOL. 2, pp. 647–647. https://doi.org/10.1145/3587103.3594170 Vandenberg, J., Min, W., Catete, V., Boulden, D., & Mott, B. (2023). Leveraging Game Design Activities for Middle Grades AI Education in Rural Communities. PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON THE FOUNDATIONS OF DIGITAL GAMES, FDG 2023. https://doi.org/10.1145/3582437.3587193 Monahan, R., Vandenberg, J., Gupta, A., Smith, A., Elsayed, R., Fox, K., … Mott, B. (2023). Multimodal CS Education Using a Scaffolded CSCL Environment. PROCEEDINGS OF THE 2023 CONFERENCE ON INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION, ITICSE 2023, VOL. 2, pp. 645–645. https://doi.org/10.1145/3587103.3594181 Vandenberg, J., Min, W., Gupta, A., Catete, V., Boulden, D., & Mott, B. (2023). Toward AI-infused Game Design Activities for Rural Middle Grades Students. PROCEEDINGS OF THE 2023 CONFERENCE ON INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION, ITICSE 2023, VOL. 2, pp. 644–644. https://doi.org/10.1145/3587103.3594199 Saleh, A., Phillips, T. M., Hmelo-Silver, C. E., Glazewski, K. D., Mott, B. W., & Lester, J. C. (2022, February 26). A learning analytics approach towards understanding collaborative inquiry in a problem-based learning environment. BRITISH JOURNAL OF EDUCATIONAL TECHNOLOGY. https://doi.org/10.1111/bjet.13198 Zhang, J., Hutt, S., Ocumpaugh, J., Henderson, N., Goslen, A., Rowe, J. P., … Lester, J. (2022). Investigating Student Interest and Engagement in Game-Based Learning Environments. ARTIFICIAL INTELLIGENCE IN EDUCATION, PT I, Vol. 13355, pp. 711–716. https://doi.org/10.1007/978-3-031-11644-5_72 Park, K., Mott, B., Lee, S., Gupta, A., Jantaraweragul, K., Glazewski, K., … Lester, J. (2022). Investigating a visual interface for elementary students to formulate AI planning tasks. JOURNAL OF COMPUTER LANGUAGES, 73. https://doi.org/10.1016/j.cola.2022.101157 Ottenbreit-Leftwich, A., Glazewski, K., Hmelo-Silver, C., Jantaraweragul, K., Chakraburty, S., Jeon, M., … Lester, J. (2023). Is Elementary AI Education Possible? PROCEEDINGS OF THE 54TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, VOL 2, SIGCSE 2023, pp. 1364–1364. https://doi.org/10.1145/3545947.3576308 Ottenbreit-Leftwich, A., Glazewski, K., Jeon, M., Jantaraweragul, K., Hmelo-Silver, C. E., Scribner, A., … Lester, J. (2022, September 14). Lessons Learned for AI Education with Elementary Students and Teachers. INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION. https://doi.org/10.1007/s40593-022-00304-3 Fahid, F. M., Acosta, H., Lee, S., Carpenter, D., Mott, B., Bae, H., … Lester, J. (2022). Multimodal Behavioral Disengagement Detection for Collaborative Game-Based Learning. ARTIFICIAL INTELLIGENCE IN EDUCATION: POSTERS AND LATE BREAKING RESULTS, WORKSHOPS AND TUTORIALS, INDUSTRY AND INNOVATION TRACKS, PRACTITIONERS AND DOCTORAL CONSORTIUM, PT II, Vol. 13356, pp. 218–221. https://doi.org/10.1007/978-3-031-11647-6_38 Vandenberg, J., Min, W., Catete, V., Boulden, D., & Mott, B. (2023). Promoting AI Education for Rural Middle Grades Students with Digital Game Design. PROCEEDINGS OF THE 54TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, VOL 2, SIGCSE 2023, pp. 1388–1388. https://doi.org/10.1145/3545947.3576333 Vandenberg, J., Gupta, A., Smith, A., ElSayed, R., Fox, K., Cheuoua, A. H., … Mott, B. (2023). Supporting Upper Elementary Students in Multidisciplinary Block-Based Narrative Programming. PROCEEDINGS OF THE 54TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, VOL 2, SIGCSE 2023, pp. 1401–1401. https://doi.org/10.1145/3545947.3576345 Spain, R., Rowe, J., Smith, A., Goldberg, B., Pokorny, R., Mott, B., & Lester, J. (2021, July 23). A reinforcement learning approach to adaptive remediation in online training. JOURNAL OF DEFENSE MODELING AND SIMULATION-APPLICATIONS METHODOLOGY TECHNOLOGY-JDMS, Vol. 7. https://doi.org/10.1177/15485129211028317 Park, K., Mott, B., Lee, S., Glazewski, K., Scribner, J. A., Ottenbreit-Leftwich, A., … Lester, J. (2021). Designing a Visual Interface for Elementary Students to Formulate AI Planning Tasks. 2021 IEEE SYMPOSIUM ON VISUAL LANGUAGES AND HUMAN-CENTRIC COMPUTING (VL/HCC 2021). https://doi.org/10.1109/VL/HCC51201.2021.9576163 Park, K., Sohn, H., Mott, B. W., Min, W., Saleh, A., Glazewski, K. D., … Lester, J. C. (2021). Detecting Disruptive Talk in Student Chat-Based Discussion within Collaborative Game-Based Learning Environments. LAK21 CONFERENCE PROCEEDINGS: THE ELEVENTH INTERNATIONAL CONFERENCE ON LEARNING ANALYTICS & KNOWLEDGE, pp. 405–415. https://doi.org/10.1145/3448139.3448178 Tian, X., Wiggins, J. B., Fahid, F. M., Emerson, A., Bounajim, D., Smith, A., … Lester, J. (2021). Modeling Frustration Trajectories and Problem-Solving Behaviors in Adaptive Learning Environments for Introductory Computer Science. ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2021), PT II, Vol. 12749, pp. 355–360. https://doi.org/10.1007/978-3-030-78270-2_63 Rachmatullah, A., Reichsman, F., Lord, T., Dorsey, C., Mott, B., Lester, J., & Wiebe, E. (2021). Modeling Secondary Students' Genetics Learning in a Game-Based Environment: Integrating the Expectancy-Value Theory of Achievement Motivation and Flow Theory. JOURNAL OF SCIENCE EDUCATION AND TECHNOLOGY, 30(4), 511–528. https://doi.org/10.1007/s10956-020-09896-8 Min, W., Spain, R., Saville, J. D., Mott, B., Brawner, K., Johnston, J., & Lester, J. (2021). Multidimensional Team Communication Modeling for Adaptive Team Training: A Hybrid Deep Learning and Graphical Modeling Framework. ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2021), PT I, Vol. 12748, pp. 293–305. https://doi.org/10.1007/978-3-030-78292-4_24 Saleh, A., Chen, Y., Hmelo-Silver, C. E., Glazewski, K. D., Mott, B. W., & Lester, J. C. (2020). Coordinating scaffolds for collaborative inquiry in a game-based learning environment. JOURNAL OF RESEARCH IN SCIENCE TEACHING, 57(9), 1490–1518. https://doi.org/10.1002/tea.21656 Henderson, N. L., Rowe, J. P., Mott, B. W., Brawner, K., Baker, R., & Lester, J. C. (2019). 4D Affect Detection: Improving Frustration Detection in Game-Based Learning with Posture-Based Temporal Data Fusion. ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2019), PT I, Vol. 11625, pp. 144–156. https://doi.org/10.1007/978-3-030-23204-7_13 Smith, A., Leeman-Munk, S., Shelton, A., Mott, B., Wiebe, E., & Lester, J. (2019). A Multimodal Assessment Framework for Integrating Student Writing and Drawing in Elementary Science Learning. IEEE Transactions on Learning Technologies, 12(1), 3–15. https://doi.org/10.1109/TLT.2018.2799871 Saleh, A., Hmelo-Silver, C. E., Glazewski, K. D., Mott, B., Chen, Y., Rowe, J. P., & Lester, J. C. (2019). Collaborative inquiry play A design case to frame integration of collaborative problem solving with story-centric games. INFORMATION AND LEARNING SCIENCES, 120(9/10), 547–566. https://doi.org/10.1108/ILS-03-2019-0024 Geden, M., Smith, A., Campbell, J., Spain, R., Amos-Binks, A., Mott, B. W., … Lester, J. (2019). Construction and Validation of an Anticipatory Thinking Assessment. FRONTIERS IN PSYCHOLOGY, 10. https://doi.org/10.3389/fpsyg.2019.02749 Mott, B. W., Taylor, R. G., Lee, S. Y., Rowe, J. P., Saleh, A., Glazewski, K. D., … Lester, J. C. (2019). Designing and Developing Interactive Narratives for Collaborative Problem-Based Learning. INTERACTIVE STORYTELLING, ICIDS 2019, Vol. 11869, pp. 86–100. https://doi.org/10.1007/978-3-030-33894-7_10 Ozer, E. M., Penilla, C., Spain, R. D., Mott, B. W., Woodson, D., & Lester, J. C. (2019, February). HEALTH QUEST: PROMOTING ADOLESCENTS' HEALTH SCIENCE CAREER INTERESTS THROUGH TECHNOLOGY-RICH LEARNING EXPERIENCES. JOURNAL OF ADOLESCENT HEALTH, Vol. 64, pp. S134–S134. https://doi.org/10.1016/j.jadohealth.2018.10.279 Min, W., Park, K., Wiggins, J., Mott, B., Wiebe, E., Boyer, K. E., & Lester, J. (2019). Predicting Dialogue Breakdown in Conversational Pedagogical Agents with Multimodal LSTMs. ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2019, PT II, Vol. 11626, pp. 195–200. https://doi.org/10.1007/978-3-030-23207-8_37 Wiggins, J. B., Kulkarni, M., Min, W., Boyer, K. E., Mott, B., Wiebe, E., & Lester, J. (2019). Take the Initiative: Mixed Initiative Dialogue Policies for Pedagogical Agents in Game-Based Learning Environments. ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2019, PT II, Vol. 11626, pp. 314–318. https://doi.org/10.1007/978-3-030-23207-8_58 Catete, V., Lytle, N., Dong, Y., Boulden, D., Akram, B., Houchins, J., … Boyer, K. (2018). Infusing Computational Thinking into Middle Grade Science Classrooms: Lessons Learned. WIPSCE'18: PROCEEDINGS OF THE 13TH WORKSHOP IN PRIMARY AND SECONDARY COMPUTING EDUCATION, pp. 109–114. https://doi.org/10.1145/3265757.3265778 Buffum, P. S., Ying, K. M., Zheng, X., Boyer, K. E., Wiebe, E. N., Mott, B. W., … Lester, J. C. (2018). Introducing the Computer Science Concept of Variables in Middle School Science Classrooms. Proceedings of the 49th ACM Technical Symposium on Computer Science Education - SIGCSE '18, 906–911. https://doi.org/10.1145/3159450.3159545 Geden, M., Smith, A., Campbell, J., Amos-Binks, A., Mott, B., Feng, J., & Lester, J. (2018). Towards Adaptive Support for Anticipatory Thinking. PROCEEDINGS OF THE TECHNOLOGY, MIND, AND SOCIETY CONFERENCE (TECHMINDSOCIETY'18). https://doi.org/10.1145/3183654.3183665 Pezzullo, L. G., Wiggins, J. B., Frankosky, M. H., Min, W., Boyer, K. E., Mott, B. W., … Lester, J. C. (2017). "Thanks Alisha, Keep in Touch": Gender Effects and Engagement with Virtual Learning Companions. ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2017, Vol. 10331, pp. 299–310. https://doi.org/10.1007/978-3-319-61425-0_25 DeFalco, J. A., Rowe, J. P., Paquette, L., Georgoulas-Sherry, V., Brawner, K., Mott, B. W., … Lester, J. C. (2018). Detecting and Addressing Frustration in a Serious Game for Military Training. INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION, 28(2), 152–193. https://doi.org/10.1007/s40593-017-0152-1 Min, W., Frankosky, M. H., Mott, B. W., Wiebe, E. N., Boyer, K. E., & Lester, J. C. (2017). Inducing Stealth Assessors from Game Interaction Data. ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2017, Vol. 10331, pp. 212–223. https://doi.org/10.1007/978-3-319-61425-0_18 Rowe, J. P., Lobene, E. V., Mott, B. W., & Lester, J. C. (2017). Play in the Museum: Design and Development of a Game-Based Learning Exhibit for Informal Science Education. INTERNATIONAL JOURNAL OF GAMING AND COMPUTER-MEDIATED SIMULATIONS, 9(3), 96–113. https://doi.org/10.4018/ijgcms.2017070104 Buffum, P. S., Frankosky, M., Boyer, K. E., Wiebe, E. N., Mott, B. W., & Lester, J. C. (2016). Collaboration and Gender Equity in Game-Based Learning for Middle School Computer Science. Computing in Science & Engineering, 18(2), 18–28. https://doi.org/10.1109/mcse.2016.37 Smith, A., Aksit, O., Min, W., Wiebe, E., Mott, B. W., & Lester, J. C. (2016). Integrating Real-Time Drawing and Writing Diagnostic Models: An Evidence-Centered Design Framework for Multimodal Science Assessment. In A. Micarelli, J. Stamper, & K. Panourgia (Eds.), Intelligent Tutoring Systems (Vol. 9684, pp. 165–175). https://doi.org/10.1007/978-3-319-39583-8_16 Smith, A., Aksit, O., Min, W., Wiebe, E., Mott, B. W., & Lester, J. C. (2016). Integrating real-time drawing and writing diagnostic models: An evidence-centered design framework for multimodal science assessment. Intelligent tutoring systems, its 2016, 0684, 165–175. Min, W., Frankosky, M. H., Mott, B. W., Rowe, J. P., Wiebe, E., Boyer, K. E., & Lester, J. C. (2015). DeepStealth: Leveraging Deep Learning Models for Stealth Assessment in Game-Based Learning Environments. ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2015, Vol. 9112, pp. 277–286. https://doi.org/10.1007/978-3-319-19773-9_28 Buffum, P. S., Frankosky, M., Boyer, K. E., Wiebe, E., Mott, B., & Lester, J. (2015). Leveraging collaboration to improve gender equity in a game-based learning environment for middle school computer science. 2015 Research in Equity and Sustained Participation in Engineering, Computing, and Technology (RESPECT). https://doi.org/10.1109/respect.2015.7296496 Buffum, P. S., Boyer, K. E., Wiebe, E. N., Mott, B. W., & Lester, J. C. (2015). Mind the Gap: Improving Gender Equity in Game-Based Learning Environments with Learning Companions. ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2015, Vol. 9112, pp. 64–73. https://doi.org/10.1007/978-3-319-19773-9_7 Leeman-Munk, S., Smith, A., Mott, B., Wiebe, E., & Lester, J. (2015). Two Modes Are Better Than One: A Multimodal Assessment Framework Integrating Student Writing and Drawing. ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2015, Vol. 9112, pp. 205–215. https://doi.org/10.1007/978-3-319-19773-9_21 Lee, S. Y., Rowe, J. P., Mott, B. W., & Lester, J. C. (2014). A Supervised Learning Framework for Modeling Director Agent Strategies in Educational Interactive Narrative. IEEE TRANSACTIONS ON COMPUTATIONAL INTELLIGENCE AND AI IN GAMES, 6(2), 203–215. https://doi.org/10.1109/tciaig.2013.2292010 Baikadi, A., Rowe, J., Mott, B., & Lester, J. (2014). Generalizability of goal recognition models in narrative-centered learning environments. User modeling, adaptation, and personalization, umap 2014, 8538, 278–289. https://doi.org/10.1007/978-3-319-08786-3_24 Min, W., Mott, B. W., Rowe, J. P., & Lester, J. C. (2014). Leveraging semi-supervised learning to predict student problem-solving performance in narrative-centered learning environments. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 664–665). https://doi.org/10.1007/978-3-319-07221-0_99 Rowe, J. P., Lobene, E. V., Mott, B. W., & Lester, J. C. (2014). Serious games go informal: a museum-centric perspective on intelligent game-based learning. Intelligent tutoring systems, its 2014, 8474, 410–415. https://doi.org/10.1007/978-3-319-07221-0_51 Lester, J. C., Spires, H. A., Nietfeld, J. L., Minogue, J., Mott, B. W., & Lobene, E. V. (2014). Designing game-based learning environments for elementary science education: A narrative-centered learning perspective. INFORMATION SCIENCES, 264, 4–18. https://doi.org/10.1016/j.ins.2013.09.005 McQuiggan, S. W., Mott, B. W., & Lester, J. C. (2008). Modeling self-efficacy in intelligent tutoring systems: An inductive approach. USER MODELING AND USER-ADAPTED INTERACTION, 18(1-2), 81–123. https://doi.org/10.1007/s11257-007-9040-y Mott, B. W., & Lester, J. C. (2006). Narrative-centered tutorial planning for inquiry-based learning environments. Lecture Notes in Computer Science, (4053), 675–684. https://doi.org/10.1007/11774303_67 Ocumpaugh, J., Andres, J. M., Baker, R., DeFalco, J., Paquette, L., Rowe, J., … Sottilare, R. Affect dynamics in military trainees using vMedic: From engaged concentration to boredom to confusion. Artificial intelligence in education, aied 2017, 10331, 238–249. Smith, A., Min, W., Mott, B. W., & Lester, J. C. Diagrammatic student models: Modeling student drawing performance with deep learning. User modeling, adaptation and personalization, 9146, 216–227. Grafsgaard, J. F., Lee, S. Y., Mott, B. W., Boyer, K. E., & Lester, J. C. Modeling self-efficacy across age groups with automatically tracked facial expression. Artificial intelligence in education, aied 2015, 9112, 582–585.