Wookhee Min

Goslen, A., Gupta, A., Muthukrishnan, S., Midgett, R., Min, W., Vandenberg, J., … Mott, B. (2024, March 14). Engaging Students from Rural Communities in AI Education with Game-Based Learning. https://doi.org/10.1145/3626253.3635549

Lim, H., Min, W., Vandenberg, J., Cateté, V., Uchidiuno, J., & Mott, B. (2024, March 14). Supporting Student Engagement in K-12 AI Education with a Card Game Construction Toolkit. https://doi.org/10.1145/3626253.3635550

Emerson, A., Min, W., Azevedo, R., & Lester, J. (2023). Early prediction of student knowledge in game-based learning with distributed representations of assessment questions. BRITISH JOURNAL OF EDUCATIONAL TECHNOLOGY, 54(1), 40–57. https://doi.org/10.1111/bjet.13281

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

Emerson, A., Min, W., Rowe, J., Azevedo, R., & Lester, J. (2023, March 13). Multimodal Predictive Student Modeling with Multi-Task Transfer Learning. https://doi.org/10.1145/3576050.3576101

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

Vandenberg, J., Min, W., Cateté, V., Boulden, D., & Mott, B. (2022, March). Promoting AI Education for Rural Middle Grades Students with Digital Game Design. https://doi.org/10.1145/3545947.3576333

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

Henderson, N., Min, W., Rowe, J., & Lester, J. (2021). Enhancing Multimodal Affect Recognition with Multi-Task Affective Dynamics Modeling. 2021 9TH INTERNATIONAL CONFERENCE ON AFFECTIVE COMPUTING AND INTELLIGENT INTERACTION (ACII). https://doi.org/10.1109/ACII52823.2021.9597432

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

Emerson, A., Henderson, N., Min, W., Rowe, J., Minogue, J., & Lester, J. (2021). Multimodal Trajectory Analysis of Visitor Engagement with Interactive Science Museum Exhibits. ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2021), PT II, Vol. 12749, pp. 151–155. https://doi.org/10.1007/978-3-030-78270-2_27

Akram, B., Min, W., Wiebe, E., Navied, A., Mott, B., Boyer, K. E., & Lester, J. (2020). A conceptual assessment framework for k-12 computer science rubric design. Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE, 1328. https://doi.org/10.1145/3328778.3372643

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

Park, K., Mott, B. W., Min, W., Boyer, K. E., Wiebe, E. N., & Lester, J. C. (2019). Generating educational game levels with multistep deep convolutional generative adversarial networks. IEEE Conference on Computatonal Intelligence and Games, CIG, 2019-August. https://doi.org/10.1109/CIG.2019.8848085

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

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

Spain, R., Geden, M., Min, W., Mott, B., & Lester, J. (2019). Toward computational models of team effectiveness with natural language processing. CEUR Workshop Proceedings, 2501, 30–39. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-85075911853&partnerID=MN8TOARS

Wiggins, J. B., Kulkarni, M., Min, W., Mott, B., Boyer, K. E., Wiebe, E., & Lester, J. (2018). Affect-based early prediction of player mental demand and engagement for educational games. Proceedings of the 14th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2018, 243–249. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-85070822616&partnerID=MN8TOARS

Wang, P., Rowe, J., Min, W., Mott, B., & Lester, J. (2018). High-fidelity simulated players for interactive narrative planning. IJCAI International Joint Conference on Artificial Intelligence, 2018-July, 3884–3890. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-85055720882&partnerID=MN8TOARS

Akram, B., Min, W., Wiebe, E., Mott, B., Boyer, K. E., & Lester, J. (2018). Improving stealth assessment in game-based learning with LSTM-based analytics. Proceedings of the 11th International Conference on Educational Data Mining, EDM 2018. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-85080493724&partnerID=MN8TOARS

Wiggins, J. B., Kulkarni, M., Min, W., Boyer, K. E., Mott, B., Wiebe, E., & Lester, J. (2018). User Affect and No-Match Dialogue Scenarios: An Analysis of Facial Expression. Proceedings of the 4th International Workshop on Multimodal Analyses Enabling Artificial Agents in Human-Machine Interaction - MA3HMI'18, 6–14. https://doi.org/10.1145/3279972.3279979

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

Min, W., Mott, B., Rowe, J., & Lester, J. (2017). Deep LSTM-based goal recognition models for open-world digital games. AAAI Workshop - Technical Report, WS-17-01 - WS-17-15, 851–858. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-85046086839&partnerID=MN8TOARS

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

Wang, P., Rowe, J., Min, W., Mott, B., & Lester, J. (2017). Interactive narrative personalization with deep reinforcement learning. IJCAI International Joint Conference on Artificial Intelligence, 3852–3858. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-85031928990&partnerID=MN8TOARS

Min, W., Mott, B., Rowe, J., Taylor, R., Wiebe, E., Boyer, K. E., & Lester, J. (2017). Multimodal goal recognition in open-world digital games. Proceedings of the 13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017, 80–86. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-85051737443&partnerID=MN8TOARS

Wang, P., Rowe, J., Min, W., Mott, B., & Lester, J. (2017). Simulating player behavior for data-driven interactive narrative personalization. Proceedings of the 13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017, 255–261. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-85055706729&partnerID=MN8TOARS

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., Mott, B., Rowe, J., Liu, B., & Lester, J. (2016). Player goal recognition in open-world digital games with long short-term memory networks. IJCAI International Joint Conference on Artificial Intelligence, 2016-January, 2590–2596. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-85006136250&partnerID=MN8TOARS

Min, W., Vail, A. K., Frankosky, M. H., Wiggins, J. B., Boyer, K. E., Wiebe, E. N., … Lester, J. C. (2016). Predicting dialogue acts for intelligent virtual agents with multimodal student interaction data. Proceedings of the 9th International Conference on Educational Data Mining, EDM 2016, 454–459. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-85072280923&partnerID=MN8TOARS

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

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

Min, W., Ha, E. Y., Rowe, J., Mott, B., & Lester, J. (2014). Deep learning-based goal recognition in open-ended digital games. Proceedings of the 10th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2014, 37–43. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-84916877257&partnerID=MN8TOARS

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

Min, W., Rowe, J. P., Mott, B. W., & Lester, J. C. (2013). Personalizing embedded assessment sequences in narrative-centered learning environments: A collaborative filtering approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 369–378). https://doi.org/10.1007/978-3-642-39112-5-38

Min, W.-H., & Cheong, Y.-G. (2009). An interactive-content technique based approach to generating personalized advertisement for privacy protection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 185–191). https://doi.org/10.1007/978-3-642-02559-4_21

Cheong, Y.-G., Kim, Y.-J., Min, W.-H., Shim, E.-S., & Kim, J.-Y. (2008). PRISM: A framework for authoring interactive narratives. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 297–308). https://doi.org/10.1007/978-3-540-89454-4_37

Min, W.-H., Shim, E.-S., Kim, Y.-J., & Cheong, Y.-G. (2008). Planning-integrated story graph for interactive narratives. MM'08 - Proceedings of the 2008 ACM International Conference on Multimedia, with co-located Symposium and Workshops, 27–32. https://doi.org/10.1145/1462014.1462021

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.