Publications

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.