IWILDS'25: The 5th International Workshop on Investigating Learning During Web Search

Web-based learning is evolving rapidly as traditional search engines are complemented by Large Language Models (LLMs) and other AI technologies. This evolution offers new opportunities, such as automated information synthesis and personalized learning experiences. However, this also presents new challenges, including the need for learners to be aware of potential biases and misinformation in AI-generated content, and to maintain focus and depth in their learning journeys.

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Publication Details

Published
2025-02-26
DOI
https://doi.org/10.1145/3701551.3705709
Citations
1
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
Field-Weighted Citation Impact
2.48
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article

IWILDS'25: The 5th International Workshop on Investigating Learning During Web Search

Nilavra Bhattacharya, Ran Yu, Anett Hoppe, Jiqun Liu
1 citations
Intelligent Tutoring Systems and Adaptive Learning
2.48
article

IWILDS'25: The 5th International Workshop on Investigating Learning During Web Search

Nilavra Bhattacharya, Ran Yu, Anett Hoppe, Jiqun Liu
article en
1 citations

Abstract

Web-based learning is evolving rapidly as traditional search engines are complemented by Large Language Models (LLMs) and other AI technologies. This evolution offers new opportunities, such as automated information synthesis and personalized learning experiences. However, this also presents new challenges, including the need for learners to be aware of potential biases and misinformation in AI-generated content, and to maintain focus and depth in their learning journeys.

University of Bonn (DE), Technische Informationsbibliothek (TIB) (DE), L3S Research Center (DE), ABB (Germany) (DE), University of Oklahoma (US)
Openalex Percentile: Top 12%
Intelligent Tutoring Systems and Adaptive Learning
2.48
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