
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, i.e., 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 IS 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.
Authors manuscript accepted for publication in Journal of Management Information Systems
FOS: Computer and information sciences, 1404 Management Information Systems, Artificial Intelligence (cs.AI), 10009 Department of Informatics, Computer Science - Artificial Intelligence, 1706 Computer Science Applications, Computer Science - Human-Computer Interaction, 1802 Information Systems and Management, 1803 Management Science and Operations Research, 000 Computer science, knowledge & systems, Human-Computer Interaction (cs.HC)
FOS: Computer and information sciences, 1404 Management Information Systems, Artificial Intelligence (cs.AI), 10009 Department of Informatics, Computer Science - Artificial Intelligence, 1706 Computer Science Applications, Computer Science - Human-Computer Interaction, 1802 Information Systems and Management, 1803 Management Science and Operations Research, 000 Computer science, knowledge & systems, Human-Computer Interaction (cs.HC)
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
