Towards Speech-Based Collaboration Detection in a Noisy Classroom

Bahar Shahrokhian, Kurt VanLehn

Research output: Chapter in Book/Report/Conference proceedingConference contribution


An Intelligent Orchestration System, such as our FACT [1], should act like an automated teaching assistant that helps teachers provide relevant, timely help. To do so, it needs to know what the students are doing and thus who needs help more than the others. This is especially important when students work in small groups and the teacher’s ability to monitor every group frequently diminishes. This project is an attempt to investigate the feasibility and challenges of only using the students’ speech to predict each group’s collaboration status. We are using machine-learning techniques to build models that agree with our human annotator’s collaboration status judgments.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium - 23rd International Conference, AIED 2022, Proceedings
EditorsMaria Mercedes Rodrigo, Noburu Matsuda, Alexandra I. Cristea, Vania Dimitrova
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages6
ISBN (Print)9783031116469
StatePublished - 2022
Event23rd International Conference on Artificial Intelligence in Education, AIED 2022 - Durham, United Kingdom
Duration: Jul 27 2022Jul 31 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13356 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference23rd International Conference on Artificial Intelligence in Education, AIED 2022
Country/TerritoryUnited Kingdom


  • Collaboration detection
  • Educational data mining
  • Intelligent orchestration systems
  • Intelligent tutoring systems

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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