How Do Learners Read the Content in a Multi-source Reading-to-Write Task? – A Multimodal Study

Debarshi Nath, Dragan Gašević, Yizhou Fan, Ramkumar Rajendran

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

Text comprehension is an important skill that a student can develop, and reading behaviours like skimming and scanning can provide deep insights into how comprehension unfolds in realtime. These behaviours can be examined through deliberate eye movements, which offer a unique lens for investigating reading processes. Yet, most studies rely on low-level eye gaze metrics, such as fixations, as proxies for reading that do not distinguish reading from other tasks like video watching. More precise operationalisations of reading behaviours can provide deeper insights into learning when examined in real-world educational activities. In this study, we assessed the feasibility of a reading-skimming detection algorithm in a two-hour reading-to-write task. Our analysis identified three distinct reading behaviours—persistent reading, scanning, and skimming, demonstrating the potential of this algorithm for multimodal analysis. Our findings indicate that learners engage in thorough reading when encountering new content for the first time and tend to re-read only specific sections while drafting their essays. By integrating log data with reading behaviours, we identified several theoretical learning strategies and reconstructed a temporal narrative of reading-writing that aligns with contemporary models of reading comprehension.

Original languageEnglish
Title of host publicationArtificial Intelligence in Education - 26th International Conference, AIED 2025 Palermo, Italy, July 22–26, 2025 Proceedings, Part V
EditorsAlexandra I. Cristea, Erin Walker, Yu Lu, Olga C. Santos, Seiji Isotani
Place of PublicationCham Switzerland
PublisherSpringer
Pages293-300
Number of pages8
ISBN (Electronic)9783031984624
ISBN (Print)9783031984617
DOIs
Publication statusPublished - 2025
EventInternational Conference on Artificial Intelligence in Education 2025 - Palermo, Italy
Duration: 22 Jul 202526 Jul 2025
Conference number: 26th
https://link.springer.com/book/10.1007/978-3-031-98465-5 (Published Proceedings)
https://aied2025.itd.cnr.it/ (Website)

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume15881
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Artificial Intelligence in Education 2025
Abbreviated titleAIED 2025
Country/TerritoryItaly
CityPalermo
Period22/07/2526/07/25
Internet address

Keywords

  • eyetracking
  • learning strategies
  • multimodal learning analytics
  • Reading comprehension

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