Please use this identifier to cite or link to this item:
Files in This Item:
File Description SizeFormat 
Tavakoli2020.pdf339.95 kBAdobe PDFView/Open
Title: Labour Market Information Driven, Personalized, OER Recommendation System for Lifelong Learners
Authors: Tavakoli, MohammadrezaMol, StefanKismihók, Gábor
Editors: Lane, H. ChadZvacek, SusanUhomoibhi, James
Publishers Version:
Issue Date: 2020
Published in: Proceedings of the 12th International Conference on Computer Supported Education Vol. 2, 2020
Publisher: Setúbal, Portugal : Science and Technology Publications, Lda
Abstract: In this paper, we suggest a novel method to aid lifelong learners to access relevant OER based learning content to master skills demanded on the labour market. Our software prototype 1) applies Text Classification and Text Mining methods on vacancy announcements to decompose jobs into meaningful skills components, which lifelong learners should target; and 2) creates a hybrid OER Recommender System to suggest personalized learning content for learners to progress towards their skill targets. For the first evaluation of this prototype we focused on two job areas: Data Scientist, and Mechanical Engineer. We applied our skill extractor approach and provided OER recommendations for learners targeting these jobs. We conducted in-depth, semi-structured interviews with 12 subject matter experts to learn how our prototype performs in terms of its objectives, logic, and contribution to learning. More than 150 recommendations were generated, and 76.9% of these recommendations were treated as us eful by the interviewees. Interviews revealed that a personalized OER recommender system, based on skills demanded by labour market, has the potential to improve the learning experience of lifelong learners.
Keywords: Lifelong Learning; Open Education Resources; Recommender Systems; Labour Market Intelligence; Machine Learning; Text Mining
DDC: 020
License: CC BY-NC-ND 4.0 Unported
Link to License:
Appears in Collections:Informationswissenschaften

This item is licensed under a Creative Commons License Creative Commons