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Cited by 37Intelligent Tutoring Systems and Adaptive LearningEducational Games and GamificationOnline Learning and Analytics

Detecting Off-Task Behavior from Student Dialogue in Game-Based Collaborative Learning

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Carpenter, Dan, Emerson, Andrew, Mott, Bradford W., Saleh, Asmalina, Glazewski, Krista D., Hmelo-Silver, Cindy E., Lester, James C.·2020·Lecture Notes in Computer Science
DOI 10.1007/978-3-030-52237-7_5PMC PMC7334155
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  • F1 scores for detecting students' off-task messages in game-based collaborative learning are around 0.67.

    “the F1 scores for detecting student confusion in the course forum (Geller et al., 2021) and students' off-task messages in game-based collaborative learning (Carpenter et al., 2020) are around 0.77 and 0.67, respectively.”

    From Practical and ethical challenges of large language models in education: A systematic scoping review (2024) · cites this paper as Carpenter et al., 2020

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Research works printed but not linked: 14

  1. [5]Jeong, H., Hmelo-Silver, C.E.: Technology supports in CSCL. In: The Future of Learning: Proceedings of the 10th International Conference of the Learning Sciences (ICLS 2012), vol. 1, pp. 339–346 (2012)
  2. [7]Saab N van Joolingen WR van Hout-Wolters BH Communication in collaborative discovery learning Br. J. Educ. Psychol. 2005 75 4 603 621 16318681
  3. [8]Rowe, J.R., McQuiggan, S.W., Robison, J.L., Lester, J.: Off-task behavior in narrative-centered learning environments. In: Proceedings of the International Conference on Artificial Intelligence in Education, pp. 99–106 (2009)
  4. [9]Baker, R.S., Corbett, A.T., Koedinger, K.R., Wagner, A.Z.: Off-task behavior in the cognitive tutor classroom: when students “game the system”. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 383–390 (2004)
  5. [13]Baker, R.S.: Modeling and understanding students’ off-task behavior in intelligent tutoring systems. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1059–1068 (2007)
  6. [14]Cocea, M., Hershkovitz, A., Baker, R.S.: The impact of off-task and gaming behaviors on learning: immediate or aggregate? In: Proceeding of the 2009 Conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling, pp. 507–514. IOS Press (2009)
  7. [15]Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: Distributed representations of words and phrases and their compositionality. In: Advances in Neural Information Processing Systems, pp. 3111–3119 (2013)
  8. [16]Peters, M.E., et al.: Deep contextualized word representations (2018). arXiv preprint arXiv:1802.05365 · arXiv
  9. [18]Louis, A., Higgins, D.: Off-topic essay detection using short prompt texts. In: Proceedings of the NAACL HLT 2010 Fifth Workshop on Innovative Use of NLP for Building Educational Applications, Association for Computational Linguistics, pp. 92–95 (2010)
  10. [19]Persing, I., Ng, V.: Modeling prompt adherence in student essays. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 1534–1543 (2014)
  11. [20]Rei, M.: Detecting off-topic responses to visual prompts. In: Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications, pp. 188–197 (2017)
  12. [22]Rodriguez, F.J., Price, K.M., Boyer, K.E.: Exploring the pair programming process: characteristics of effective collaboration. In: Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education. ACM (2017)
  13. [25]Sultan, M.A., Bethard, S., Sumner, T.: DLS@CU: sentence similarity from word alignment and semantic vector composition. In: Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), pp. 148–153 (2015)
  14. [27]Niwattanakul, S., Singthongchai, J., Naenudorn, E., Wanapu, S.: Using of Jaccard coefficient for keywords similarity. In: Proceedings of the International Multiconference of Engineers and Computer Scientists, pp. 380–384 (2013)

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Authors
Carpenter, D., Emerson, A., Mott, B. W., Saleh, A., Glazewski, K. D., Hmelo-Silver, C. E., & Lester, J. C.
Affiliations
  • North Carolina State University (US)
  • Indiana University Bloomington (US)
Corresponding author
Carpenter, Dan
ORCID
Venue
Lecture Notes in Computer Science
Publisher
Springer International Publishing
Published
2020
Pages
55-66
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
DOI
10.1007/978-3-030-52237-7_5
PMC
PMC7334155
OpenAlex
W3040489519
Cited by
37
References
2
Citations by year
2026: 4 · 2025: 12 · 2024: 2 · 2023: 11 · 2022: 3 · 2021: 5
FWCI
1.81
Type
conference paper
Language
en
Open access
Licence
Locations
  • Lecture notes in computer science (publishedVersion)
  • PubMed Central (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
  • Social Sciences › Psychology › Developmental and Educational Psychology › Educational Games and Gamification
  • Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
Keywords
student dialogue, group chat, word embeddings, contextual information, adaptive scaffolding, junior high school science

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