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.
Author: | Flemming Bugert, Lisa GrabingerORCiD, Dominik BittnerORCiD, Florian HauserORCiD, Vamsi Krishna Nadimpalli, Susanne StauferORCiD, Jürgen MottokORCiDGND |
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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 |