Classroom Adoptions

  • University of Pittsburgh: 1) CS2001, 2) CS2610, 3) CS0401, 4) CS1635 5) PHYS0174, 6) PHYS0175, 7) PSY0422.
  • Purdue University: 1) ENGR131, 2) ENGR132
  • Bogazici University: 1) IE256, 2) IE312
  • Thiel College: 1) MATH125
  • Ivy Tech Community College: 1) MATH043, 2) MATH123, 3) MATH137, 4) MATH201.
  • University of Florida: 1) CGS2531, 2) COP2271, 3) COP2274

Publications

  • Magooda, A., Litman, D. & Elaraby M. (2021). Exploring Multitask Learning for Low-Resource Abstractive Summarization. Findings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP), Punta Cana, Dominican Republic, November 2021.
  • Magooda, A. & Litman, D. (2021). Mitigating Data Scarceness through Data Synthesis, Augmentation and Curriculum for Abstractive Summarization. Findings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP), Punta Cana, Dominican Republic, November 2021.
  • Magooda, A., & Litman, D. (2020). Abstractive Summarization for Low Resource Data using Domain Transfer and Data Synthesis. In Proceedings of the 33rd International FLAIRS Conference, North Miami Beach, Florida, May 2020.
  • Menekse, M. (2020). The reflection-informed learning and instruction to improve students’ academic success in undergraduate classrooms. The Journal of Experimental Education88(2), 183-199.
  • Anwar, S., & Menekse, M. (2020). A systematic review of observation protocols used in postsecondary STEM classrooms. Review of Education9(1), 81-120.
  • Luo, W., Liu, F., Liu, Z., & Litman, D. (2018). A Novel ILP Framework for Summarizing Content with High Lexical Variety. Natural Language Engineering, Volume 24, Issue 6, pp. 887-920,
  • Heo, D., Anwar, S., & Menekse, M. (2018). The relationship between engineering students’ achievement goals, reflection behaviors, and learning outcomes. International Journal of Engineering Education, 34(5), 1634-1643 (pdf)
  • Menekse, M., Anwar, S., & Purzer, S. (2018). Self-Efficacy and Mobile Learning Technologies: A Case Study of CourseMIRROR. C. B. Hodges (ed.), Self-Efficacy in Instructional Technology Contexts, Springer Nature Switzerland AG 2018.
  • Anwar, S., Menekse, M., Heo, D., & Kim, D. (2018). Work-in-Progress: Students’ reflection quality and effective team membership. In Proceedings of the 2018 ASEE Annual Conference, Salt Lake City, Utah. (pdf)
  • Heo, D., Anwar, S., & Menekse, M. (2017). How do engineering students’ achievement goals influence their reflection behaviors and learning outcomes? In Proceedings of the 2017 ASEE Annual Conference, Columbus, Ohio. (pdf)
  • Fan, X., Luo, W., Menekse, M., Litman, D., & Wang, J. (2017). Scaling reflection prompts in large classrooms via mobile interfaces and natural language processing. In Proceedings of 22nd ACM Conference on Intelligent User Interfaces (IUI 2017), Limassol, Cyprus. (pdf)
  • Luo, W., Liu, F., & Litman, D. (2016). An improved phrase-based approach to annotating and summarizing student course responses. In Proceedings of the 26th International Conference on Computational Linguistics (COLING), pp. 53-63, Osaka, Japan. (pdf)
  • Luo, W., & Litman, D. J. (2016). Determining the quality of a student reflective response. In Proceedings 29th International FLAIRS Conference, pp. 226-231, Key Largo, FL. (Best Student Paper Award Nominee) (pdf )
  • Luo, W., Liu, F., Liu, Z., & Litman, D. (2016). Automatic summarization of student course feedback. In Proceedings Conference of the North American Chapter of the Association for Computational Linguistics – Human Language Technologies (NAACL HLT), pp. 80-85, San Diego, CA. (short paper) (pdf )
  • Fan, X., Luo, W., Menekse, M., Litman, D., & Wang, J. (2015). CourseMIRROR: Enhancing large classroom instructor-student interactions via mobile interfaces and natural language processing. Works-In-Progress, In Proceedings of ACM Conference on Human Factors in Computing Systems (CHI 2015), 1473-1478, Seoul, Korea. (extended abstract) (pdf )
  • Luo, W., Fan, X., Menekse, M., Wang, J., & Litman, D. J. (2015). Enhancing instructor-student and student-student interactions with mobile interfaces and summarization. In Proceedings NAACL HLT Companion, 16-20, Denver, Colorado. (demo) (pdf )
  • Luo, W., & Litman, D. J. (2015). Summarizing student responses to reflection prompts. In Proceedings of Empirical Methods in Natural Language Processing (EMNLP ) pp. 1955–1960, Lisbon, Portugal (short paper). (pdf)

Dissertations

  • Fan, X. (2017). Scalable teaching and learning via intelligent user interfaces, (Doctoral Dissertation). University of Pittsburgh. (pdf)
  • Luo, W. (2017) Automatic summarization for student reflective responses, (Doctoral Dissertation). University of Pittsburgh. (pdf )