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Dashboards and OLAP services in LLL and distance learning processes
Leading article: 2017. December (MIAU No. 232.)
(Previous article: 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.
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