Andy Smith 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 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 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 Fahid, F. M., Tian, X., Emerson, A., Wiggins, J. B., Bounajim, D., Smith, A., … Lester, J. (2021). Progression Trajectory-Based Student Modeling for Novice Block-Based Programming. Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization. https://doi.org/10.1145/3450613.3456833 Cluster-Based Analysis of Novice Coding Misconceptions in Block-Based Programming. (2020). Proceedings of the 51st ACM Technical Symposium on Computer Science Education. https://doi.org/10.1145/3328778.3366924 Designing Block-Based Programming Language Features to Support Upper Elementary Students in Creating Interactive Science Narratives. (2020). Proceedings of the 51st ACM Technical Symposium on Computer Science Education. https://doi.org/10.1145/3328778.3372653 Predictive Student Modeling in Block-Based Programming Environments with Bayesian Hierarchical Models. (2020). Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization. https://doi.org/10.1145/3340631.3394853 Taub, M., Sawyer, R., Smith, A., Rowe, J., Azevedo, R., & Lester, J. (2020). The agency effect: The impact of student agency on learning, emotions, and problem-solving behaviors in a game-based learning environment. Computers and Education, 147. https://doi.org/10.1016/j.compedu.2019.103781 Smith, A., Mott, B., Taylor, S., Hubbard-Cheuoua, A., Minogue, J., Oliver, K., & Ringstaff, C. (2020). Toward a Block-Based Programming Approach to Interactive Storytelling for Upper Elementary Students. Interactive Storytelling, 111–119. https://doi.org/10.1007/978-3-030-62516-0_10 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 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 Min, W., Frankosky, M., Mott, B. W., Rowe, J., Smith, P. A. M., Wiebe, E., … Lester, J. (2019). DeepStealth: Game-Based Learning Stealth Assessment with Deep Neural Networks. IEEE Transactions on Learning Technologies, 13(2), 1–1. https://doi.org/10.1109/tlt.2019.2922356 Taylor, S., Min, W., Mott, B., Emerson, A., Smith, A., Wiebe, E., & Lester, J. (2019). Position: IntelliBlox: A Toolkit for Integrating Block-Based Programming into Game-Based Learning Environments. Proceedings - 2019 IEEE Blocks and Beyond Workshop, B and B 2019, 55–58. https://doi.org/10.1109/BB48857.2019.8941222 Lester, J. C., Boyer, K. E., Wiebe, E. N., Mott, B., & Smith, A. (2019). Prime: Engaging STEM undergraduates in computer science with intelligent tutoring systems. ASEE Annual Conference and Exposition, Conference Proceedings. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-85078800967&partnerID=MN8TOARS Rodriguez, F. J., Smith, C. R., Smith, A., Boyer, K. E., Wiebe, E. N., Mott, B. W., & Lester, J. C. (2019). Toward a Responsive Interface to Support Novices in Block-Based Programming. Proceedings - 2019 IEEE Blocks and Beyond Workshop, B and B 2019, 9–13. https://doi.org/10.1109/BB48857.2019.8941205 Psaradellis, C., Muis, K. R., Smith, A., & Lajoie, S. P. (2018). Enhancing complex mathematics problem solving through learning by teaching with a teachable agent. IMSCI 2018 - 12th International Multi-Conference on Society, Cybernetics and Informatics, Proceedings, 2, 31–36. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-85056509594&partnerID=MN8TOARS 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 Sawyer, R., Smith, A., Rowe, J., Azevedo, R., & Lester, J. (2017). Enhancing student models in game-based learning with facial expression recognition. UMAP 2017 - Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, 192–201. https://doi.org/10.1145/3079628.3079686 Sawyer, R., Smith, A., Rowe, J., Azevedo, R., & Lester, J. (2017). Is More Agency Better? The Impact of Student Agency on Game-Based Learning. In Lecture Notes in Computer Science: Vol. 10331 LNAI (pp. 335–346). https://doi.org/10.1007/978-3-319-61425-0_28 Shelton, A., Smith, A., Wiebe, E., Behrle, C., Sirkin, R., & Lester, J. (2016). Drawing and Writing in Digital Science Notebooks: Sources of Formative Assessment Data. Journal of Science Education and Technology, 25(3), 474–488. https://doi.org/10.1007/s10956-016-9607-7 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. Smith, A., Min, W., Mott, B. W., & Lester, J. C. (2015). Diagrammatic Student Models: Modeling Student Drawing Performance with Deep Learning. In Lecture Notes in Computer Science (Vol. 9146, pp. 216–227). https://doi.org/10.1007/978-3-319-20267-9_18 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 Miller, S. A., Smith, A., Bahram, S., & St. Amant, R. (2012). A glove for tapping and discrete 1D/2D input. International Conference on Intelligent User Interfaces, Proceedings IUI, 101–104. https://doi.org/10.1145/2166966.2166986 Smith, A. P., & Spontak, R. J. (1999). P-methylstyrene. Polymer Data Handbook, 688–695. Smith, A. E., Evans, M. V., & Davidian, M. (1998). Statistical properties of fitted estimates of apparent in vivo metabolic constants obtained from gas uptake data. I. Lipophilic and slowly metabolized VOCs. Inhalation Toxicology, 10(5), 383–409. 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. Sawyer, R., Smith, A., Rowe, J., Azevedo, R., & Lester, J. Is more agency better? The impact of student agency on game-based learning. Artificial intelligence in education, aied 2017, 10331, 335–346.