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Artificial Intelligence (AI) Student Assistants in the Classroom: Designing Chatbots to Support Student Success

Author

Listed:
  • Yu Chen

    (San Jose State University)

  • Scott Jensen

    (San Jose State University)

  • Leslie J. Albert

    (San Jose State University)

  • Sambhav Gupta

    (San Jose State University)

  • Terri Lee

    (San Jose State University)

Abstract

In higher education, low teacher-student ratios can make it difficult for students to receive immediate and interactive help. Chatbots, increasingly used in various scenarios such as customer service, work productivity, and healthcare, might be one way of helping instructors better meet student needs. However, few empirical studies in the field of Information Systems (IS) have investigated pedagogical chatbot efficacy in higher education and fewer still discuss their potential challenges and drawbacks. In this research we address this gap in the IS literature by exploring the opportunities, challenges, efficacy, and ethical concerns of using chatbots as pedagogical tools in business education. In this two study project, we conducted a chatbot-guided interview with 215 undergraduate students to understand student attitudes regarding the potential benefits and challenges of using chatbots as intelligent student assistants. Our findings revealed the potential for chatbots to help students learn basic content in a responsive, interactive, and confidential way. Findings also provided insights into student learning needs which we then used to design and develop a new, experimental chatbot assistant to teach basic AI concepts to 195 students. Results of this second study suggest chatbots can be engaging and responsive conversational learning tools for teaching basic concepts and for providing educational resources. Herein, we provide the results of both studies and discuss possible promising opportunities and ethical implications of using chatbots to support inclusive learning.

Suggested Citation

  • Yu Chen & Scott Jensen & Leslie J. Albert & Sambhav Gupta & Terri Lee, 2023. "Artificial Intelligence (AI) Student Assistants in the Classroom: Designing Chatbots to Support Student Success," Information Systems Frontiers, Springer, vol. 25(1), pages 161-182, February.
    • Handle: RePEc:spr:infosf:v:25:y:2023:i:1:d:10.1007_s10796-022-10291-4
    DOI: 10.1007/s10796-022-10291-4
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    References listed on IDEAS

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    1. Jaana Porra & Mary Lacity & Michael S. Parks, 2020. "“Can Computer Based Human-Likeness Endanger Humanness?” – A Philosophical and Ethical Perspective on Digital Assistants Expressing Feelings They Can’t Have”," Information Systems Frontiers, Springer, vol. 22(3), pages 533-547, June.
    2. Rangina Ahmad & Dominik Siemon & Ulrich Gnewuch & Susanne Robra-Bissantz, 2022. "Designing Personality-Adaptive Conversational Agents for Mental Health Care," Information Systems Frontiers, Springer, vol. 24(3), pages 923-943, June.
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    Cited by:

    1. Denis Dennehy & Anastasia Griva & Nancy Pouloudi & Yogesh K. Dwivedi & Matti Mäntymäki & Ilias O. Pappas, 2023. "Artificial Intelligence (AI) and Information Systems: Perspectives to Responsible AI," Information Systems Frontiers, Springer, vol. 25(1), pages 1-7, February.
    2. Zhang, Zhuo, 2023. "The impact of the artificial intelligence industry on the number and structure of employments in the digital economy environment," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    3. Firuz Kamalov & David Santandreu Calonge & Ikhlaas Gurrib, 2023. "New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution," Sustainability, MDPI, vol. 15(16), pages 1-27, August.

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