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Learning with Digital Agents: An Analysis based on the Activity Theory

Dolata, Mateusz; Katsiuba, Dzmitry; Wellnhammer, Natalie; Schwabe, Gerhard (2023). Learning with Digital Agents: An Analysis based on the Activity Theory. Journal of Management Information Systems, 40(1):56-95.

Abstract

Digital agents are considered a general-purpose technology. They spread quickly in private and organizational contexts, including education. Yet, research lacks a conceptual framing to describe interaction with such agents in a holistic manner. While focusing on the interaction with a pedagogical agent, that is, a digital agent capable of natural-language interaction with a learner, we propose a model of learning activity based on activity theory. We use this model and a review of prior research on digital agents in education to analyze how various characteristics of the activity, including features of a pedagogical agent or learner, influence learning outcomes. The analysis leads to identification of information systems research directions and guidance for developers of pedagogical agents and digital agents in general. We conclude by extending the activity theory-based model beyond the context of education and show how it helps designers and researchers ask the right questions when creating a digital agent.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Scopus Subject Areas:Social Sciences & Humanities > Management Information Systems
Physical Sciences > Computer Science Applications
Social Sciences & Humanities > Management Science and Operations Research
Social Sciences & Humanities > Information Systems and Management
Scope:Discipline-based scholarship (basic research)
Language:English
Date:30 March 2023
Deposited On:13 Jun 2023 13:05
Last Modified:26 Feb 2025 02:38
Publisher:Taylor & Francis
ISSN:0742-1222
Additional Information:This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Management Information Systems on 30.03.2023, available online: http://wwww.tandfonline.com/10.1080/07421222.2023.2172775.
OA Status:Green
Publisher DOI:https://doi.org/10.1080/07421222.2023.2172775
Other Identification Number:merlin-id:23649
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  • Content: Accepted Version
  • Language: English
  • Licence: Creative Commons: Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)

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