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Dashboards and OLAP services in LLL and distance learning processes

Vezércikk: 2017. December (MIAU No. 232.)
(Előző cikk: MIAU No. 231.)

Keywords: e-learning, public services, data-driven decision making, data asset management, artificial intelligence

Abstract: This paper shows case study elements of the new CMS/LMS for employees in public services in Hungary which may be considered as a sort of LLL process embedded in an elearning framework. The activities of users will be logged and analyzed. Techniques like dashboards and/or OLAP services could be used by each person (for benchmarking) and especially for further modelling. Static and dynamic comparisons of users, subjects, mentors, etc. could lead to improvements in a spontaneous way. Model-based support processes can validate and/or prepare subjective/intuitive decisions. Users in each level of CMS/LSM have to learn using standard solutions of the data assets management in order to work effectively and efficiently in a log-based environment. More (DOC) *** More (PDF)


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