research-article

Towards Learning Style Prediction based on Personality

Authors:

Flemming Bugert,

Lisa Grabinger,

Dominik Bittner,

Florian Hauser,

Vamsi Krishna Nadimpalli,

Susanne Staufer,

Jürgen Prof. Dr. MottokAuthors Info & Claims

ECSEE '23: Proceedings of the 5th European Conference on Software Engineering Education

Pages 48 - 55

https://doi.org/10.1145/3593663.3593682

Published: 19 June 2023 Publication History

Abstract

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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Cited By

Bittner DNadimpalli VGrabinger LEzer THauser FMottok J(2024)Uncovering Learning Styles through Eye Tracking and Artificial IntelligenceProceedings of the 2024 Symposium on Eye Tracking Research and Applications10.1145/3649902.3653940(1-7)Online publication date: 4-Jun-2024
https://dl.acm.org/doi/10.1145/3649902.3653940

Index Terms

Towards Learning Style Prediction based on Personality
1. Computing methodologies
  1. Artificial intelligence
  2. Machine learning
    1. Cross-validation
2. Information systems
  1. Data management systems
    1. Database design and models
      1. Graph-based database models

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Published In

cover image ACM Other conferences

ECSEE '23: Proceedings of the 5th European Conference on Software Engineering Education

June 2023

264 pages

ISBN:9781450399562

DOI:10.1145/3593663

Editor:
Jürgen Mottok
OTH Regensburg

Copyright © 2023 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 19 June 2023

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German Federal Ministry of Education and

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ECSEE 2023

ECSEE 2023: European Conference on Software Engineering Education

June 19 - 21, 2023

Seeon/Bavaria, Germany

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Overall Acceptance Rate 11 of 16 submissions, 69%

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Cited By

Bittner DNadimpalli VGrabinger LEzer THauser FMottok J(2024)Uncovering Learning Styles through Eye Tracking and Artificial IntelligenceProceedings of the 2024 Symposium on Eye Tracking Research and Applications10.1145/3649902.3653940(1-7)Online publication date: 4-Jun-2024
https://dl.acm.org/doi/10.1145/3649902.3653940

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