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Collaborative Learning with Artificial Intelligence Speakers

Pre-service Elementary Science Teachers’ Responses to the Prototype

  • SI: Epistemic Insight & Artificial Intelligence
  • Published:
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Abstract

This research aims to demonstrate that artificial intelligence (AI) can function not only as a tool for learning, but also as an intelligent agent with which humans can engage in collaborative learning (CL) to change epistemic practices in science classrooms. We adopted a design and development research approach, following the Analysis, Design, Development, Implementation and Evaluation (ADDIE) model, to prototype a tangible instructional system called Collaborative Learning with AI Speakers (CLAIS). The CLAIS system is designed to have 3–4 human learners join an AI speaker to form a small group, where humans and AI are considered peers participating in the Jigsaw learning process. The development was carried out using the NUGU AI speaker platform. The CLAIS system was successfully implemented in a Science Education course session with 15 pre-service elementary science teachers. The participants evaluated the CLAIS system through mixed methods surveys as teachers, learners, peers, and users. Quantitative data showed that the participants’ Intelligent-Technological, Pedagogical, and Content Knowledge was significantly increased after the CLAIS session, the perception of the CLAIS learning experience was positive, the peer assessment on AI speakers and human peers was different, and the user experience was ambivalent. Qualitative data showed that the participants came to anticipate future changes in the epistemic process in science classrooms, while acknowledging technical issues such as speech recognition and response latency. This study highlights the potential of human-AI collaboration for knowledge co-construction in authentic classroom settings and exemplifies how AI could shape the future landscape of epistemic practices in the classroom.

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Notes

  1. https://www.springer.com/journal/11191/updates/23312040 (Retrieved January 5.th, 2023).

  2. https://www.nugu.co.kr/ (Retrieved November 19th, 2023).

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Funding

This research is supported by Seoul National University Department of AI-Integrated Education.

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Authors and Affiliations

  1. AI4STEM Education Center, University of Georgia, Athens, GA, 30602, USA

    Gyeong-Geon Lee & Xiaoming Zhai

  2. Department of Mathematics, Science, and Social Sciences Education, University of Georgia, Athens, GA, 30602, USA

    Gyeong-Geon Lee & Xiaoming Zhai

  3. Sejong Science High School, 79 Gurogu Oriro 21-Gil, Seoul, 08258, Republic of Korea

    Seonyeong Mun

  4. Department of Science Education, Gyeongin National University of Education, 62 Gyeyanggu Gyesanro, Incheon, 21044, Republic of Korea

    Myeong-Kyeong Shin

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  1. Gyeong-Geon Lee
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Appendices

Appendix 1. Course syllabus

figure a

Appendix 2. English version of handout with learning content and problem set (Fig. 5)

(a): A handout page on Driver’s alternative conceptual framework [(Bold): The content students have to fill in].

figure b

(b): Peer evaluation rubric and problem set.

figure c

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Lee, GG., Mun, S., Shin, MK. et al. Collaborative Learning with Artificial Intelligence Speakers. Sci & Educ (2024). https://doi.org/10.1007/s11191-024-00526-y

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