A Review of Learning Analytics Dashboard and a Novel Application in Maritime Simulator Training

Open Access
Conference Proceedings
Authors: Ziaul Haque MunimTae-Eun Kim

Abstract: Developing a Learning Analytics Dashboard (LAD) to evaluate maritime simulation training performance based on key performance indicators (KPIs) of maritime navigational competence can improve learning efficiency and effectiveness. Relevant data needs to be fed from simulation training logs and other sources, analysed using appropriate visualization and artificial intelligence approaches, and reported in a single window with valuable insights for trainees and instructors. This study provides a Systematic Literature Review (SLR) of published literature on LADs using scientometric tools and techniques. The findings reveal six research clusters and publication trends in LAD research. An example of a novel application of Automated Machine Learning (AutoML) analysing data from maritime desktop simulator training is presented for future maritime LAD development.

Keywords: Learning analytics, learning dashboard, machine learning, simulator training

DOI: 10.54941/ahfe1003158

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