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Towards Learning Style Prediction based on Personality

  • This paper assesses the relation between personality, demographics, and learning style. Hence, data is collected from 200 participants using 1) the BFI-10 to obtain the participant’s expression of personality traits according to the five-factor model, 2) the ILS to determine the participant’s learning style according to Felder and Silverman, and 3) a demographic questionnaire. From the obtained data, we train and evaluate a Bayesian network. Using Bayesian statistics, we show that age and gender slightly influence personality and that demographics as well as personality have at least a minor effect on learning styles. We also discuss the limitations and future work of the presented approach.

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Metadaten
Author:Flemming Bugert, Lisa GrabingerORCiD, Dominik BittnerORCiD, Florian HauserORCiD, Vamsi Krishna Nadimpalli, Susanne StauferORCiD, Jürgen MottokORCiDGND
DOI:https://doi.org/10.1145/3593663.3593682
ISBN:978-1-4503-9956-2
Parent Title (English):Proceedings of the 5th European Conference on Software Engineering Education, Seeon/Germany, June 19 - 21, 2023
Publisher:ACM
Document Type:conference proceeding (article)
Language:English
Year of first Publication:2023
Release Date:2023/07/17
First Page:48
Last Page:55
Institutes:Fakultät Elektro- und Informationstechnik
Fakultät Elektro- und Informationstechnik / Laboratory for Safe and Secure Systems (LAS3)
Begutachtungsstatus:peer-reviewed
research focus:Digitalisierung
Licence (German):Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG