The Goal - Question - Indicator Approach for Personalized Learning Analytics
Arham Muslim, Mohamed Amine Chatti, Memoona Mughal, Ulrik Schroeder
2017
Abstract
Open learning analytics (OLA) is a relatively new branch of learning analytics (LA) which emerged due to the growing demand for self-organized, networked, and lifelong learning opportunities. OLA deals with learning data collected from various learning environments and contexts, analyzed with a range of analytics methods, and for different stakeholders with diverse interests and objectives. This diversity in different dimensions of OLA is a challenge which needs to be addressed by adopting a personalized learning analytics (PLA) model. Current implementations of LA mainly rely on a predefined set of questions and indicators which is not suitable in the context of OLA where the indicators are unpredictable. In this paper we present the goal - question - indicator (GQI) approach for PLA and provide the conceptual, design, implementation and evaluation details of the indicator engine component of the open learning analytics platform (OpenLAP) that engages end users in the indicator generation process by supporting them in setting goals, posing questions, and self-defining indicators.
References
- Chatti, M. A. (2010). Personalization in technology enhanced learning: A social software perspective. Shaker Verlag.
- Chatti, M. A., Muslim, A., and Schroeder, U. (2017). Toward an open learning analytics ecosystem. In Big Data and Learning Analytics in Higher Education, pages 195-219. Springer.
- Lukarov, V., Chatti, M. A., Thüs, H., Kia, F. S., Muslim, A., Greven, C., and Schroeder, U. (2014). Data models in learning analytics. In Proceedings of DeLFI Workshops, pages 88-95.
- Muslim, A., Chatti, M. A., Bashir, M. B., Varela, O. E. B., and Schroeder, U. (2017). A modular and extensible framework for open learning analytics. Journal of Learning Analytics. (In review).
- Muslim, A., Chatti, M. A., Mahapatra, T., and Schroeder, U. (2016). A rule-based indicator definition tool for personalized learning analytics. In Proceedings of the Sixth International Conference on Learning Analytics & Knowledge, pages 264-273, New York, NY, USA. ACM.
Paper Citation
in Harvard Style
Muslim A., Chatti M., Mughal M. and Schroeder U. (2017). The Goal - Question - Indicator Approach for Personalized Learning Analytics . In Proceedings of the 9th International Conference on Computer Supported Education - Volume 1: CSEDU, ISBN 978-989-758-239-4, pages 371-378. DOI: 10.5220/0006319803710378
in Bibtex Style
@conference{csedu17,
author={Arham Muslim and Mohamed Amine Chatti and Memoona Mughal and Ulrik Schroeder},
title={The Goal - Question - Indicator Approach for Personalized Learning Analytics},
booktitle={Proceedings of the 9th International Conference on Computer Supported Education - Volume 1: CSEDU,},
year={2017},
pages={371-378},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006319803710378},
isbn={978-989-758-239-4},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 9th International Conference on Computer Supported Education - Volume 1: CSEDU,
TI - The Goal - Question - Indicator Approach for Personalized Learning Analytics
SN - 978-989-758-239-4
AU - Muslim A.
AU - Chatti M.
AU - Mughal M.
AU - Schroeder U.
PY - 2017
SP - 371
EP - 378
DO - 10.5220/0006319803710378