An ontology-based and case-based reasoning supported workplace learning approach

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Authors

Emmenegger, Sandro
Hinkelmann, Knut
Laurenzi, Emanuele

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Publisher

Springer

Abstract

The support of workplace learning is increasingly relevant as the change in every form determines today’s working world in the industry and public administrations alike. Adapting quickly to a new job, a new task or a new team is a significant challenge that must be dealt with ever faster. Workplace learning differs significantly from school learning as it is aligned with business goals. Our approach supports workplace learning by suggesting historical cases and providing recommendations of experts and learning resources. We utilize users’ workplace environment, we consider their learning preferences, provide them with useful prior lessons, and compare required and acquired competencies to issue the best-suited recommendations. Our research work follows a Design Science Research strategy and is part of the European funded project Learn PAd. The recommender system introduced here is evaluated in an iterative manner, first by comparing it to previously elicited user requirements and then through practical application in a test process conducted by the project application partner.

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Keywords

Case-based reasoning, Ontology supported learning, Ontology-based case-based reasoning, Personalized learning, Recommender system, Workplace learning, Engineering research, Public administration, Software design, Design-science researches, Learning preference, Supported learning, User requirements, Workplace environments

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Citation

Emmenegger S. et al. (2017) An Ontology-Based and Case-Based Reasoning Supported Workplace Learning Approach. In: Hammoudi S., Pires L., Selic B., Desfray P. (eds) Model-Driven Engineering and Software Development. MODELSWARD 2016. Communications in Computer and Information Science, vol 692. Springer, Cham.