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Cited by 51Intelligent Tutoring Systems and Adaptive LearningInnovative Teaching and Learning MethodsTeaching and Learning Programming

Shifting the Load: a Peer Dialogue Agent that Encourages its Human Collaborator to Contribute More to Problem Solving

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Howard, Cynthia, Jordan, Pamela, Di Eugenio, Barbara, Katz, Sandra·2017·International Journal of Artificial Intelligence in Education
DOI 10.1007/s40593-015-0071-y
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Abstract

Despite a growing need for educational tools that support students at the earliest phases of undergraduate Computer Science (CS) curricula, relatively few such tools exist–the majority being Intelligent Tutoring Systems. Since peer interactions more readily give rise to challenges and negotiations, another way in which students can become more interactive during problem solving, we created an artificial peer collaborator to determine its value for aiding CS students. Central to its development was the notion that it should monitor the student’s collaborative behavior and attempt to guide him/her towards more productive behavior. In prior work, we found that initiative shifts correlate with both Knowledge Co-Construction (KCC) and learning and are potentially easier to model as an indicator of productive collaboration in instructional software. In this paper, we describe a unique peer dialogue agent that we created to test the effects of tracking and reacting to initiative shifts. While our study did not find differences in learning gains when comparing agents that do and do not track and react to initiative shifts, we did find that students do learn when interacting with the agent and that attempting to influence initiative taking did make a difference. This suggests that by tracking initiative shifts, the agent was able to detect times when the student had been letting the agent do most of the “deep thinking” and that the agent’s tactics for encouraging the student to begin taking the initiative again were helpful.

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93 of 93 references verified0 citation errors · 0 not checkable

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  • The same tutorial dialogue toolkit (TuTalk) is the core of the peer dialogue agent presented by Howard et al. (2017), where the ITS engages in one-on-one problem-solving peer interaction with a student and can interact verbally, graphically and in a process-oriented way, and engage in collaborative problem solving instead of tutoring.

    “The same tutorial dialogue toolkit (TuTalk) is the core of the peer dialogue agent presented by Howard et al. (2017), where the ITS engages in a one-on-one problem-solving peer interaction with a student and can interact verbally, graphically and in a process-oriented way, and engage in collaborative problem solving instead of tutoring.”

    From Systematic review of research on artificial intelligence applications in higher education – where are the educators? (2019) · cites this paper as Howard et al. (2017)

  • The study by Howard et al. (2017) could be considered as part of a new category regarding peer-agent collaboration.

    “This last study could be considered as part of a new category regarding peeragent collaboration.”

    From Systematic review of research on artificial intelligence applications in higher education – where are the educators? (2019) · cites this paper as Howard et al. (2017)

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Related

Authors
Howard, C., Jordan, P., Di Eugenio, B., & Katz, S.
Affiliations
  • Lewis University (US)
  • University of Pittsburgh (US)
Corresponding author
Jordan, Pamela
ORCID
Jordan, Pamela
Venue
International Journal of Artificial Intelligence in Education
Publisher
Elsevier BV
Published
2017-03
Volume
27
Issue
1
Pages
101-129
ISSN
1560-4292 (ISSN-L)
DOI
10.1007/s40593-015-0071-y
OpenAlex
W2230347737
Cited by
51
References
98
Citations by year
2026: 4 · 2025: 7 · 2024: 7 · 2023: 8 · 2022: 8 · 2021: 4 · 2020: 7 · 2019: 3 · 2018: 1 · 2016: 2
FWCI
0.98
Type
journal article
Language
en
Open access
Licence
Locations
International Journal of Artificial Intelligence in Education (publishedVersion, cc-by-nc-nd)
Funders
  • National Science Foundation (ALT-0536959, ALT-0536968)
  • Office of Naval Research (N000140010640)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
  • Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
  • Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
Keywords
knowledge co-construction, peer collaboration, computer science education, cooperative learning

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