Detecting the Disengaged Reader: Using Scrolling Data to Predict Disengagement during Reading

Daniel Biedermann, Jan Schneider, George-Petru Ciordas-Hertel, Beate Eichmann, Carolin Hahnel, Frank Goldhammer, Hendrik Drachsler

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


When reading long and complex texts, students may disengage and miss out on relevant content. In order to prevent disengaged behavior or to counteract it by means of an intervention, it is ideally detected an early stage. In this paper, we present a method for early disengagement detection that relies only on the classification of scrolling data. The presented method transforms scrolling data into a time series representation, where each point of the series represents the vertical position of the viewport in the text document. This time series representation is then classified using time series classification algorithms. We evaluated the method on a dataset of 565 university students reading eight different texts. We compared the algorithm performance with different time series lengths, data sampling strategies, the texts that make up the training data, and classification algorithms. The method can classify disengagement early with up to 70% accuracy. However, we also observe differences in the performance depending on which of the texts are included in the training dataset. We discuss our results and propose several possible improvements to enhance the method.
Original languageEnglish
Title of host publicationLAK 2023 Conference Proceedings - Towards Trustworthy Learning Analytics - 13th International Conference on Learning Analytics and Knowledge
PublisherAssociation for Computing Machinery (ACM)
Number of pages7
ISBN (Electronic)9781450398657
Publication statusPublished - 13 Mar 2023
Event13th International Learning Analytics and Knowledge Conference - Arlington, United States
Duration: 13 Mar 202317 Mar 2023
Conference number: 13


Conference13th International Learning Analytics and Knowledge Conference
Abbreviated titleLAK 2023
Country/TerritoryUnited States


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