Adaptive E-Learning Technologies for Sustained Learning Motivation in Engineering Science - Acquisition of Motivation through Self-Reports and Wearable Technology

Mathias Bauer, Cassandra Bräuer, Jacqueline Schuldt, Heidi Krömker

2018

Abstract

Surveys show besides the number of students also the drop-out rates are increasing, especially in early phases of studying natural or engineering sciences. The research project “SensoMot - Sensor Measures of Motivation for Adaptive Learning” tries to counter this development by means of improving the quality of teaching in the department of micro technology with the help of an adaptive e-learning system. For that purpose, the mediated learning content should be better adapted to the individual prior knowledge, competencies and motivational profiles of the learners. Furthermore, the continuous sensory data acquisition of physiological parameters of the learner shall be accomplished by current wearable technology. The paper presents first results in the form of conceptual determinations concerning self-reports and physiological measures, instructional design and adaptation techniques and further includes the early involvement of the subsequent users in the development process through an iterative, formative evaluation of prototypical solutions.

Paper Citation

in Harvard Style

Bauer M., Bräuer C., Schuldt J. and Krömker H. (2018). Adaptive E-Learning Technologies for Sustained Learning Motivation in Engineering Science - Acquisition of Motivation through Self-Reports and Wearable Technology.In Proceedings of the 10th International Conference on Computer Supported Education - Volume 1: CSEDU, ISBN 978-989-758-291-2, pages 418-425. DOI: 10.5220/0006787104180425

in Bibtex Style

@conference{csedu18,
author={Mathias Bauer and Cassandra Bräuer and Jacqueline Schuldt and Heidi Krömker},
title={Adaptive E-Learning Technologies for Sustained Learning Motivation in Engineering Science - Acquisition of Motivation through Self-Reports and Wearable Technology},
booktitle={Proceedings of the 10th International Conference on Computer Supported Education - Volume 1: CSEDU,},
year={2018},
pages={418-425},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006787104180425},
isbn={978-989-758-291-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Supported Education - Volume 1: CSEDU,
TI - Adaptive E-Learning Technologies for Sustained Learning Motivation in Engineering Science - Acquisition of Motivation through Self-Reports and Wearable Technology
SN - 978-989-758-291-2
AU - Bauer M.
AU - Bräuer C.
AU - Schuldt J.
AU - Krömker H.
PY - 2018
SP - 418
EP - 425
DO - 10.5220/0006787104180425