Using Artificial Intelligence to Support Peer-to-Peer Discussions in Science Classrooms
Bibliographic Data
| ID | 22045332 |
|---|---|
| Authors | Kelly Billings (0000-0002-0179-8443, University of California, Berkeley, corresponding author), Hsin-Yi Chang (0000-0002-9659-1022, National Taiwan Normal University), Jonathan M Lim-Breitbart (0000-0001-8593-3392, University of California, Berkeley), Marcia C Linn (0000-0003-2257-9474, University of California, Berkeley) |
| Year | 2024 |
| Volume | 14 |
| Issue | 12 |
| Pages | 1411 |
| Publication date | 2024-12-23 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Education Sciences (JOURNAL) |
| Journal identifiers | ISSN: 2227-7102 • E-ISSN: 2227-7102 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/educsci14121411 |
| OpenAlex | W4405703008 |
| Language | EN |
| Citations received | 2 |
| References cited | 43 |
In successful peer discussions students respond to each other and benefit from supports that focus discussion on one another’s ideas. We explore using artificial intelligence (AI) to form groups and guide peer discussion for grade 7 students. We use natural language processing (NLP) to identify student ideas in science explanations. The identified ideas, along with Knowledge Integration (KI) pedagogy, informed the design of a question bank to support students during the discussion. We compare groups formed by maximizing the variety of ideas among participants to randomly formed groups. We embedded the chat tool in an earth science unit and tested it in two classrooms at the same school. We report on the accuracy of the NLP idea detection, the impact of maximized versus random grouping, and the role of the question bank in focusing the discussion on student ideas. We found that the similarity of student ideas limited the value of maximizing idea variety and that the question bank facilitated students’ use of knowledge integration processes
Mathematics education · Peer feedback · Computer Science · Educational Games and Gamification · Innovative Teaching and Learning Methods · Intelligent Tutoring Systems and Adaptive Learning · Psychology · Artificial Intelligence
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| Unique citing works | 2 |
|---|---|
| Citations per year | 2 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 2 |