The DOI matches its Crossref record; 60 of the 66 references it cites were found in a registry or an index.
Towards an Agile Approach to Adapting Dynamic Collaboration Support to Student Needs
Open accessAbstract
This paper investigates the use of conversational agents to scaffold on-line collaborative learning discussions through an approach called Academically Productive Talk (APT). In contrast to past work on dynamic support for collaborative learning, where agents were used to elevate conceptual depth by leading students through directed lines of reasoning (Kumar & Rosé, IEEE Transactions on Learning Technologies, 4 (1), 2011 ), this APT-based approach uses generic prompts that encourage students to articulate and elaborate their own lines of reasoning, and to challenge and extend the reasoning of their teammates. This paper integrates findings from a series of studies across content domains (biology, chemistry, engineering design), grade levels (high school, undergraduate), and facilitation strategies. APT based strategies are contrasted with simply offering positive feedback when the students themselves employ APT facilitation moves in their interactions with one another, an intervention we term Positive Feedback for APT engagement. The pattern of results demonstrates that APT based support for collaborative learning can significantly increase learning, but that the effect of specific APT facilitation strategies is context specific. It appears the effectiveness of each strategy depends upon factors such as the difficulty of the material (in terms of being new conceptual material versus review) and the skill level of the learner (urban public high school vs. selective private university). In contrast, Feedback for APT engagement does not positively impact learning. In addition to an analysis based on learning gains, an automated conversation analysis technique is presented that effectively predicts which strategies are successfully operating in specific contexts. Implications for design of more agile forms of dynamic support for collaborative learning are discussed.
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“One study presented negative results regarding the type of support that the ITS provided (Adamson et al., 2014)”
From Systematic review of research on artificial intelligence applications in higher education – where are the educators? (2019) · cites this paper as Adamson et al., 2014
In the citing paper
“which could have been more useful if it was more adjusted to the type of (in this case, more advanced) learners.”
From Systematic review of research on artificial intelligence applications in higher education – where are the educators? (2019) · cites this paper as Adamson et al., 2014
Citations
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Stahl, G., Koschmann, T. D., & Suthers, D. (2006) · Cited by 1,226
Corpus-based and Knowledge-based Measures of Text Semantic Similarity
Mihalcea, R. F., Corley, C. D., & Strapparava, C. (2006) · University of North Texas Digital Library (University of North Texas) · Cited by 1,196
Scardamalia, M., & Bereiter, C. (2005) · Cambridge University Press eBooks · doi:10.1017/cbo9780511816833.008 · Cited by 1,159
Research works printed but not linked: 2
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Cited by
Sorted by citations
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-019-0171-0 · Cited by 7,242
Evolution and Revolution in Artificial Intelligence in Education
Roll, I., & Wylie, R. (2016) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-016-0110-3 · Cited by 1,229
Power to the Teachers: An Exploratory Review on Artificial Intelligence in Education
Lameras, P., & Arnab, S. (2021) · Information · doi:10.3390/info13010014 · Cited by 291
Affordances and challenges of artificial intelligence in K-12 education: a systematic review
Crompton, H., Jones, M. V., & Burke, D. (2024) · Journal of Research on Technology in Education · doi:10.1080/15391523.2022.2121344 · Cited by 213
Aims for cultivating students’ key competencies based on artificial intelligence education in China
Huang, X. (2021) · Education and Information Technologies · doi:10.1007/s10639-021-10530-2 · Cited by 187
Metadata
- Authors
- Adamson, D., Dyke, G., Jang, H., & Rosé, C. P.
- Affiliations
- Carnegie Mellon University (US)
- Corresponding author
- Rosé, Carolyn Penstein
- Venue
- International Journal of Artificial Intelligence in Education
- Publisher
- Elsevier BV
- Published
- 2014-01
- Volume
- 24
- Issue
- 1
- Pages
- 92-124
- ISSN
- 1560-4292 (ISSN-L)
- OpenAlex
- W2065443038
- Cited by
- 156
- References
- 66
- Citations by year
- 2026: 12 · 2025: 22 · 2024: 15 · 2023: 12 · 2022: 17 · 2021: 15 · 2020: 11 · 2019: 9 · 2018: 6 · 2017: 9 · 2016: 9 · 2015: 12 · 2014: 6
- FWCI
- 11.96
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- International Journal of Artificial Intelligence in Education (publishedVersion, cc-by-nc-nd)
- HAL (submittedVersion)
- Funders
- National Science Foundation (0836012, 0835426)
- 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 › Online Learning and Analytics
- Keywords
- chatbots, dynamic support, cooperative learning, online forums, scaffolding, positive feedback, facilitation techniques, student reasoning, conceptual understanding, adaptive learning support
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