Changing the Optics: Comparing Traditional and Retrieval-Augmented GenAI E-Tutorials in Interdisciplinary Learning
On the map: Retrieval-augmented generation → Agentic RAG, agents and memory
Abstract (arXiv)
Understanding information-seeking behaviors in e-learning is critical, as learners must often make sense of complex and fragmented information, a challenge compounded in interdisciplinary fields with diverse prior knowledge. Compared to traditional e-tutorials, GenAI e-tutorials offer new ways to navigate information spaces, yet how they shape learners information-seeking behaviors remains unclear. To address this gap, we characterized behavioral differences between traditional and GenAI-mediated e-tutorial learning using the three search modes of orienteering. We conducted a between-subject study in which learners engaged with either a traditional e-tutorial or a GenAI e-tutorial accessing the same underlying information content. We found that the traditional users maintained greater awareness and focus of the information space, whereas GenAI users exhibited more proactive and exploratory behaviors with lower cognitive load due to the querying-driven interaction. These findings offer guidance for designing tutorials in e-learning.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Agentic RAG, agents and memory, one of 15 directions in Retrieval-augmented generation. Builds on 5 of its 44 references that are in the map. First posted on arXiv 24 Feb 2026.
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5 of 44 references.
References · 5
- 2023GPT-4 Technical Reportcited by 18,132
- 2025gpt-oss-120b & gpt-oss-20b Model Cardcited by 1,258
- 2024A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Modelscited by 450
- 2024Nomic Embed: Training a Reproducible Long Context Text Embeddercited by 255
- 2025Conversations over Clicks: Impact of Chatbots on Information Search in Interdisciplinary Learningcited by 2
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