Abstract: Each year, the amount of research publications is increasing. Staying on top of the state of the art is a pressing issue. The field of Learning Analytics (LA) is no exception, with the rise of digital education systems that are used broadly these days from K12 up to Higher Education. Keeping track of the advances in LA is challenging. This is especially the case for newcomers to the field, as well as for the increasing number of LA units that consult their teachers and scholars on applying evidence-based research outcomes in their lectures. To keep an overview of the rapidly growing research findings on LA, we developed LAxplore, a tool that uses NLP to extract relevant information from the LA literature. In this article, we present the evaluation of LAxplore. Results from the evaluation show that LAxplore can significantly support researchers in extracting information from relevant LA publications as it reduces the time of searching and retrieving the knowledge by a factor of six. However, the accurate extraction of relevant information from LA literature is not yet ready to be fully automatized and some manual work is still required.
Citation:
Ahmad, A.; Schneider, J.; Schiffner, D.; Islamovic, E. and Drachsler, H. (2023). LAxplore: An NLP-Based Tool for Distilling Learning Analytics and Learning Design Instruments out of Scientific Publications. In Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management – Volume 1: KDIR, ISBN 978-989-758-671-2, ISSN 2184-3228, pages 230-239. DOI: 10.5220/0012163600003598
https://www.scitepress.org/PublicationsDetail.aspx?ID=RbEybDRGg48%3d&t=1