Data Processing Pipeline for Eye-Tracking Analysis

URN to cite this document:: urn:nbn:de:bvb:355-epub-772697
DOI to cite this document:: 10.5283/epub.77269

Landes, Jennifer ; Köppl, Sonja ; Klettke, Meike

License: Creative Commons Attribution 4.0
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Date of publication of this fulltext: 28 Aug 2025 05:18

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Item type:	Conference or workshop item (Paper)
Open Access Type:	CC-License
Title of Book:	Proceedings of the 35th GI-Workshop Grundlagen von Datenbanken
Publisher:	CEUR-WS.org
Other Series:	CEUR Workshop Proceedings
Volume:	3710
Page Range:	pp. 35-42
Date:	2024
Institutions:	Informatics and Data Science > General computer science > Data Engineering (Prof. Dr.-Ing. Meike Klettke)
Keywords:	Data Pipeline, Data Preprocessing, Machine Learning
Dewey Decimal Classification:	000 Computer science, information & general works > 004 Computer science
Status:	Published
Refereed:	Yes, this version has been refereed
Created at the University of Regensburg:	Partially
Item ID:	77269

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Abstract

The overarching topic of this research project is academic misconduct in online assessments, aiming to understand students´ behavior and methods. To gain deeper insights, an eye-tracking experiment was conducted to capture when and how students engage in academic misconduct. Data from this experiment will reveal irregularities in cheating behavior. This paper presents a data engineering pipeline ...