Learning with Digital Agents: An Analysis based on the Activity Theory
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866913461952315392 |
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| author | Dolata, Mateusz Katsiuba, Dzmitry Wellnhammer, Natalie Schwabe, Gerhard |
| author_facet | Dolata, Mateusz Katsiuba, Dzmitry Wellnhammer, Natalie Schwabe, Gerhard |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2408_04304 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Learning with Digital Agents: An Analysis based on the Activity Theory Dolata, Mateusz Katsiuba, Dzmitry Wellnhammer, Natalie Schwabe, Gerhard Human-Computer Interaction Artificial Intelligence 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. |
| title | Learning with Digital Agents: An Analysis based on the Activity Theory |
| topic | Human-Computer Interaction Artificial Intelligence |
| url | https://arxiv.org/abs/2408.04304 |