ARCHIE: Exploring Language Learner Behaviors in LLM Chatbot-Supported Active Reading Log Data with Epistemic Network Analysis
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LLMs have demonstrated substantial capabilities in educational practice, e.g., automatic grading, answer generation, and student-chatbot interaction.
“Large Language Models (LLMs) have demonstrated substantial capabilities in educational practice, e.g., automatic grading (Ferreira Mello et al., 2025), answer generation (Rodrigues et al., 2025), and student-chatbot interaction (Woollaston et al., 2025; Hao et al., 2026; Zhang et al., 2025).”
From Assessing the Impact and Underlying Pathways of Sequenced AI feedback on Student Learning (2026) · cites this paper as Woollaston et al., 2025
Cites
Croes, E. A. J., & Antheunis, M. L. (2021) · Journal of Social and Personal Relationships · doi:10.1177/0265407520959463 · Cited by 291 · see citing works
Epistemic Network Analysis: A Worked Example of Theory-Based Learning Analytics
University of Wisconsin–Madison, U., Shaffer, D. W., Ruis, A. R., & University of Wisconsin–Madison, U. (2017) · Handbook of Learning Analytics · doi:10.18608/hla17.015 · Cited by 255 · cited 1× · see citing works
“We applied epistemic network analysis [21] to our data using the ENA Web Tool (version 1.7.0) [17].”
InfluentialThe impact of chatbots based on large language models on second language vocabulary acquisition
Zhang, Z., & Huang, X. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e25370 · Cited by 107 · see citing works
Zheng, S. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100271 · Cited by 58 · see citing works
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Assessing the Impact and Underlying Pathways of Sequenced AI feedback on Student Learning
Cao, J., Zhao, C. Q., Schunn, C., McLaughlin, E. A., Lin, J., & Koedinger, K. R. (2026) · arXiv · doi:10.48550/arxiv.2604.07469
- Authors
- Woollaston, S., Flanagan, B., Ocheja, P., Toyokawa, Y., & Ogata, H.
- Affiliations
- Kyoto University (JP)
- Venue
- Proceedings of the 15th International Learning Analytics and Knowledge Conference
- Publisher
- ACM
- Published
- 2025-03-03
- Pages
- 642-654
- OpenAlex
- W4407842494
- Cited by
- 10
- References
- 4
- Citations by year
- 2026: 9 · 2025: 1
- FWCI
- 55.02
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- International Conference on Learning Analytics and Knowledge (LAK) (publishedVersion, cc-by)
- Funders
- Japan Society for the Promotion of Science ((B) JP20H01722, JP23H01001, (Exploratory) JP21K19824, 22KJ1914, (A) JP23H00505)
- New Energy and Industrial Technology Development Organization (JPNP20006)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Second Language Acquisition and Learning
- Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- LLM chatbots, epistemic network analysis, reading comprehension, AI-assisted language learning, learner metacognition
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