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Embodied Agents to Scaffold Data Science Education

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Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium (AIED 2022)

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Abstract

Arguing and working with data has become commonplace in several study domains. One way to immerse students in hands-on exploration with data is to provide them with problem-solving environments, for example jupyter notebooks, which can scaffold students’ reasoning and bring them closer to disciplinary ways of thinking. Although the intrinsic affordances of jupyter notebooks (e.g., interaction with multiple data representations, automation of procedural task aspects) allow students to engage in rich learning experiences, students lack crucial social scaffolding that directly targets the process of learning. We are developing an AIED infrastructure EASEx for use in higher education contexts that brings in the affordances of embodied pedagogical agents to significantly advance educational practice by scaffolding students in a personalized manner as they work through problems using jupyter notebooks.

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Author information

Authors and Affiliations

  1. Professorship for Learning Sciences and Higher Education, ETH Zürich, Zürich, Switzerland

    Tanmay Sinha

  2. Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, India

    Shivam Malhotra

Authors
  1. Tanmay Sinha
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  2. Shivam Malhotra
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Corresponding author

Correspondence to Tanmay Sinha .

Editor information

Editors and Affiliations

  1. Ateneo De Manila University, Quezon, Philippines

    Maria Mercedes Rodrigo

  2. Department of Computer Science, North Carolina State University, Raleigh, NC, USA

    Noburu Matsuda

  3. Durham University, Durham, UK

    Alexandra I. Cristea

  4. University of Leeds, Leeds, UK

    Vania Dimitrova

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Sinha, T., Malhotra, S. (2022). Embodied Agents to Scaffold Data Science Education. In: Rodrigo, M.M., Matsuda, N., Cristea, A.I., Dimitrova, V. (eds) Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium. AIED 2022. Lecture Notes in Computer Science, vol 13356. Springer, Cham. https://doi.org/10.1007/978-3-031-11647-6_26

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  • DOI: https://doi.org/10.1007/978-3-031-11647-6_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-11646-9

  • Online ISBN: 978-3-031-11647-6

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