Conversational agents for fostering curiosity-driven learning in children
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The increased intrinsic motivation in AI-assisted groups aligns with recent research on AI-enhanced learning environments, suggesting AI partners can provide motivational support similar to human instructors or peers.
“The increased intrinsic motivation aligns with recent research on AI-enhanced learning environments (Abdelghani et al., 2022), suggesting that AI partners can provide motivational support similar to human instructors or peers.”
From The impact of AI-assisted pair programming on student motivation, programming anxiety, collaborative learning, and programming performance: a comparative study with traditional pair programming and individual approaches (2025) · cites this paper as Abdelghani et al., 2022
The Discussion (p. 18) explicitly says the incentive agent did not produce higher intrinsic motivation, contrary to the suggested alignment with increased intrinsic motivation. The Motivation measures (p. 17) likewise report no significant difference between agent conditions; the paper does not compare motivational support from AI partners with that from human instructors or peers. (LLM, conf=0.86)
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Experimental — accuracy not yet measuredWhen generated by hand, the answer-to-a-divergent-question type of cues showed to be rather efficient in training children's divergent QA skills.
“when generated by hand, this type of cues showed to be rather efficient in training children's divergent QA skills.”
From GPT-3-Driven Pedagogical Agents to Train Children’s Curious Question-Asking Skills (2024) · cites this paper as [1]
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- Authors
- Abdelghani, R., Oudeyer, P.-Y., Law, E., de Vulpillières, C., & Sauzéon, H.
- Affiliations
- Institut national de recherche en sciences et technologies du numérique (FR)
- University of Waterloo (CA)
- Corresponding author
- Abdelghani, Rania
- Venue
- International Journal of Human-Computer Studies
- Publisher
- Elsevier BV
- Published
- 2022-11
- Volume
- 167
- Pages
- 102887
- ISSN
- 1071-5819 (ISSN-L)
- OpenAlex
- W4286252734
- Cited by
- 39
- References
- 47
- Citations by year
- 2026: 14 · 2025: 10 · 2024: 6 · 2023: 8 · 2022: 1
- FWCI
- 2.06
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (am, 267 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- International Journal of Human-Computer Studies (acceptedVersion)
- arXiv (Cornell University) (submittedVersion, cc-by-nc-nd)
- HAL (submittedVersion, other-oa)
- Oskar-Bordeaux (Universite de Bordeaux) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Association Nationale de la Recherche et de la Technologie
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychological and Educational Research Studies
- Keywords
- chatbots, curiosity-driven learning, curiosity, metacognitive skills, autonomous exploration, elementary school students, question generation, semantic cues, knowledge acquisition, educational technology
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