Publications

INVITE Exclusive

• AnaDE1.0: A Novel Data Set for Benchmarking Analogy Detection and Extraction
  Bhavya, Shradha Sehgal, Jinjun Xiong, Chengxiang Zhai. (2024). Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (EACL).
• Analego: Let’s build analogies together!
  Bhavya, Zhou, Y., Sehgal, S., Bhat, S., Zhai, C. (2024). Demo presentation at the AAAI 2024 Workshop on AI for Education (AI4Ed). 2024.
• Thinking Critically: Classroom Activities to Examine Ethics in Computing
  Barrett, J. (2023). In ACM EngageCSEdu. ACM, New York, NY, USA.

Works Partially Supported by INVITE

• Learner Modeling Interpretability and Explainability in Intelligent Adaptive Systems
  Zapata-Rivera, D. & Arslan, B. (in press). In Santoianni, F., Giannini, G., and Ciasull, A. (Eds.) Mind, Body, and Digital Brains. Springer Nature Switzerland AG.
• Caring assessments: Challenges and opportunities
  Sparks, J. R., Lehman, B., & Zapata-Rivera, D. (in review). Frontiers in Education – Assessment, Testing, and Applied Measurement.
• MineObserver 2.0: A Deep Learning & In-Game Framework for Assessing Natural Language Descriptions of Minecraft Imagery
  Mahajan, J., Hum, S., Henhapl, J., Yunus, D., Gadbury, M,. Brown, E., Ginger, J., Lane, H.C. (2024). Association for the Advancement of Artificial Intelligence 2024 Conference, Vancouver.
• What makes a STEM role model motivating for young girls? The effects of the role model’s growth versus fixed mindsets about ability and interest
  Gladstone, J. R., Tallberg, M., Boston Jaxon, J., & Cimpian, A. (2024). Journal of Experimental Child Psychology, 238, 105775.
• Computing Self-Efficacy in Undergraduate Students: A Multi-Institutional and Intersectional Analysis
  Ojha, V., West, L., & Lewis, C. M. (2024). Proceedings of the 2024 ACM SIGCSE Technical Symposium on Computer Science Education.
• IEKG: A Commonsense Knowledge Graph for Idiomatic Expressions
  Zeng, Z., Cheng, K., Nanniyur, S., Zhou, J., & Bhat, S. (2023). In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP).
• Unified Representation for Non-compositional and Compositional Expression
  Zeng, Z., and Bhat, S. (2023). In Findings of the Association for Computational Linguistics: EMNLP 2023.
• Non-compositional Expression Generation Based on Curriculum Learning and Continual Learning
  Zhou, J., Zeng, Z., Gong, H. & Bhat, S. (2023). In Findings of the Association for Computational Linguistics: EMNLP 2023.
• Mars, Minecraft, and AI: A Deep Learning Approach to Improve Learning by Building
  Hum, S. Gadbury, M., Shipley, E., Lane, H.C., Ginger, J. (2024). 25th International Conference on Artificial Intelligence in Education, Recife, Brazil, 2024.
• Predicting student engagement in interactive reading.
  Beigman Klebanov, B., Weeks, J., Sinharay, S. (2024). In Proceedings of the 25th International Conference on Artificial Intelligence in Education: AIED 2024.

Informing Literature

Some sample works that have contributed to the knowledge base INVITE is inspired by:

Diversity, Equity and Inclusion

• Yes, We Still Need to Talk about Diversity in Computing
  Washington, N., Barnes, T., Payton, J., Dunton, S., Stukes, F., & Peterfreund, A. (2019). IEEE Computing in Science and Engineering.
• Stars Computing Corps: Enhancing Engagement of Underrepresented Students and Building Community in Computing
  Payton, J., Barnes, T., Buch, K., Rorrer, A., Zuo, H., Gosha, K., … & Dennis, L. (2016). IEEE Computing in Science and Engineering.
• A Multilevel Analysis of Diverse Learners Playing Life Science Video Games: Interactions between Game Content, Learning Disability Status, Reading Proficiency, and Gender
  Israel M., Wang S., Marino M. (2016). Journal of Research in Science Teaching.
• Intelligent Support for All? A Literature Review of the (In) equitable Design & Evaluation of Adaptive Pedagogical Systems for CS Education
  Martin, A. C., Ying, K. M., Rodríguez, F. J., Kahn, C. S., & Boyer, K. E. (2022). The 53rd ACM Technical Symposium on Computer Science Education (SIGCSE).
• Alignment of Goals and Perceptions of Computing Predicts Students’ Sense of Belonging in Computing
  Lewis, C. M., Bruno, P., Raygoza, J., & Wang, J. (2019). The 15th Annual ACM International Computing Education Research (ICER) Conference.

Learning STEM in INVITE platforms

• Fostering Balanced Contributions Among Children Through Dialogue Visualization
  Celepkolu, M., Galdo, A. C., & Boyer, K. E. (2022). IEEE Transactions on Learning Technologies.
• Triggering STEM interest with Minecraft in a Hybrid Summer Camp
  Lane, H. C., Gadbury, M., Ginger, J., Yi, S., Comins, N., Henhapl, J., & Rivera-Rogers, A. (2022). Technology, Mind, and Behavior.
• Mining for STEM Interest Behaviors in Minecraft
  Gadbury, M., & Lane, H. C. (2022). The 23th International Conference on Artificial Intelligence in Education (AIED).
• Would you? Could you? On a tablet? Analytics of Children’s eBook Reading
  Klebanov, B. B., Loukina, A., Madnani, N., Sabatini, J., & Lentini, J. (2019). The 9th International Conference on Learning Analytics & Knowledge (LAK).

Learner Modeling and Adaptive Educational Systems

• Enhancing Personalization by Integrating Top-down and Bottom-up Approaches to Learner Modeling
  Zapata-Rivera D., & Arslan, B. (2021). The 23rd HCI International Conference.
• Learner Modeling in the Context of Caring Assessments
  Zapata-Rivera, D., Lehman, B., & Sparks, J. R. (2020). The 22nd HCI International Conference.
• The Challenge of Noisy Classrooms: Speaker Detection During Elementary Students’ Collaborative Dialogue
  Ma Y, Wiggins J, Celepkolu M, Boyer K, Lynch C, Wiebe E. (2021). The 22nd International Conference on Artificial Intelligence in Education (AIED).
• Adaptive Educational Systems
  Shute, V. J., & Zapata-Rivera, D. (2012). Adaptive Technologies for Training and Education.
• Learning Intercultural Communication Skills with Virtual Humans
  Lane, H.C., Hays, M.J., Core, M.G., & Auerbach, D. (2013). Journal of Educational Psychology.
• Autonomous Agent that Provides Automated Feedback Improves Negotiation skills
  Monahan, S., Johnson, E., Lucas, G., Finch, J., & Gratch, J. (2018). The 19th International Conference on Artificial Intelligence in Education (AIED).

Learning Analytics and Educational Data Mining

• Modeling MOOC Student Behavior With Two-Layer Hidden Markov Models
  Geigle, C., & Zhai, C. (2017). The 4th Annual ACM Conference on Learning at Scale.
• A Sequential Decision Formulation of the Interface ard Model for Interactive IR
  Zhang, Y., & Zhai, C. (2016). The 39th International ACM SIGIR conference on Research and Development in Information Retrieval.
• Detecting Learning in Noisy Data: The Case of Oral Reading Fluency
  Klebanov, B. B., Loukina, A., Lockwood, J., Liceralde, V. R. T., Sabatini, J., Madnani, N., … & Lentini, J. (2020). The 10th International Conference on Learning Analytics & Knowledge.
• Exploring Emergent Features of Student Interaction within an Embodied Science Learning Simulation
  Kang, J., Lindgren, R., & Planey, J. (2018). Journal of Multimodal Technologies and Interaction.

assessment

• Assessing Collaborative Computing: Development of the Collaborative-Computing Observation Instrument (C-COI)
  Israel, M., Wherfel, Q. M., Shehab, S., Ramos, E. A., Metzger, A., & Reese, G. C. (2016). Computer Science Education.
• Culturally Responsive Evaluation
  Hood, S., Hopson, R. K., & Kirkhart, K. E. (2015). Handbook of Practical Program Evaluation.
• Hitting a High Note on Math Tests: Remembered Success Influences Test Preferences
  Finn, B., & Miele, D. B. (2016). Journal of Experimental Psychology: Learning, Memory, and Cognition.

MACHINE LEARNING AND NATURAL LANGUAGE PROCESSING

• Knowledge-Driven Data Construction for Zero-Shot Evaluation in Commonsense Question Answering
  Ma, K., Ilievski, F., Francis, J., Bisk, Y., Nyberg, E., & Oltramari, A. (2021). The 35th AAAI Conference on Artificial Intelligence (AAAI).
• Illinimet: Illinois System for Metaphor Detection with Contextual and Linguistic Information
  Gong, H., Gupta, K., Jain, A., & Bhat, S. (2020). The 2nd Workshop on Figurative Language Processing.
• Idiomatic Expression Paraphrasing without Strong Supervision
  Zhou, J., Zeng, Z., Gong, H., & Bhat, S. (2022). The 36th AAAI Conference on Artificial Intelligence (AAAI).
• On Robustness and Regularization of Structural Support Vector Machines
  Torkamani, M. A., & Lowd, D. (2014). The 31st International Conference on Machine Learning.