A Self-assessment Tool for Teachers to Improve Their LMS Skills based on Teaching Analytics

Ibtissem Bennacer, Remi Venant, Sebastien Iksal

2022

Abstract

While learning management systems have spread for the last decades, many teachers still struggle to fully operate an LMS within their teaching, beyond its role of a simple resources repository. Moreover, there is still a lack of work in the literature to help teachers engage as learners of their own environment and improve their techno-pedagogical skills.Therefore, we suggest a web environment based on teaching analytics to provide teachers with self and social awareness of their own practices on the LMS. This article focuses on the behavioral model we designed on the strength of (i) a qualitative analysis from interviews we had with several pedagogical engineers and (ii) a quantitative analysis we conducted on teachers’ activities on the University’s LMS. This model describes teachers’ practices through six major explainable axes: evaluation, reflection, communication, resources, collaboration as well as interactivity and gamification. It can be used to detect particular teachers who may be in need of specific individual support or conversely, experts of a particular usage of the LMS who could bring constructive criticism for its improvement. While instrumented in our environment, this model enables supplying teachers with self-assessment, automatic feedback and peer recommendations in order to encourage them to improve their skills with the LMS.

Paper Citation

in Harvard Style

Bennacer I., Venant R. and Iksal S. (2022). A Self-assessment Tool for Teachers to Improve Their LMS Skills based on Teaching Analytics. In Proceedings of the 14th International Conference on Computer Supported Education - Volume 1: EKM, ISBN 978-989-758-562-3, pages 575-586. DOI: 10.5220/0011126100003182

in Bibtex Style

@conference{ekm22,
author={Ibtissem Bennacer and Remi Venant and Sebastien Iksal},
title={A Self-assessment Tool for Teachers to Improve Their LMS Skills based on Teaching Analytics},
booktitle={Proceedings of the 14th International Conference on Computer Supported Education - Volume 1: EKM,},
year={2022},
pages={575-586},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011126100003182},
isbn={978-989-758-562-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Computer Supported Education - Volume 1: EKM,
TI - A Self-assessment Tool for Teachers to Improve Their LMS Skills based on Teaching Analytics
SN - 978-989-758-562-3
AU - Bennacer I.
AU - Venant R.
AU - Iksal S.
PY - 2022
SP - 575
EP - 586
DO - 10.5220/0011126100003182