Item request has been placed! ×
Item request cannot be made. ×
loading  Processing Request

A Proposed Methodology for Investigating Student-Chatbot Interaction Patterns in Giving Peer Feedback

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
Read Online Read More Add to Saved list
  • Author(s): Michael Pin-Chuan Lin (ORCID Michael Pin-Chuan Lin (ORCID 0000-0002-7646-7024); Daniel H. Chang (ORCID Daniel H. Chang (ORCID 0000-0003-4836-8309); Philip H. Winne (ORCID Philip H. Winne (ORCID 0000-0001-5133-7525)
  • Language:
    English
  • Source:
    Educational Technology Research and Development. 2025 73(1):353-386.
  • Publication Date:
    2025
  • Document Type:
    Journal Articles
    Reports - Research
  • Additional Information
    • Availability:
      Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
    • Peer Reviewed:
      Y
    • Source:
      34
    • Subject Terms:
      Artificial Intelligence; Technology Uses in Education; Man Machine Systems; Computer Mediated Communication; Peer Evaluation; Feedback (Response); Computer Software; Learning Experience; Instructional Design; Writing Instruction; Content Area Writing; Communication (Thought Transfer); Scripts
    • Accession Number:
      10.1007/s11423-024-10408-3
    • ISSN:
      1042-1629
      1556-6501
    • Abstract:
      A chatbot is artificial intelligence software that converses with a user in natural language. It can be instrumental in mitigating teaching workloads by coaching or answering student inquiries. To understand student-chatbot interactions, this study is engineered to optimize student learning experience and instructional design. In this study, we developed a chatbot that supplemented disciplinary writing instructions to enhance peer reviewer's feedback on draft essays. With 23 participants from a lower-division post-secondary education course, we delved into characteristics of student-chatbot interactions. Our analysis revealed students were often overconfident about their learning and comprehension. Drawing on these findings, we propose a new methodology to identify where improvements can be made in conversation patterns in educational chatbots. These guidelines include analyzing interaction pattern logs to progressively redesign chatbot scripts that improve discussions and optimize learning. We describe new methodology providing valuable insights for designing more effective instructional chatbots by enhancing and engaging student learning experiences through improved peer feedback.
    • Abstract:
      As Provided
    • Publication Date:
      2025
    • Accession Number:
      EJ1462634