Abstract
Learning analytics focuses on collecting, cleaning, processing, visualization, and analyzing teaching and learning-related data from a great variety of academic sources. This paper presents the up-to-date findings and outcomes of the research, design, and development projects at the InterLabs Research Institute at Bradley University (USA) that are focused on the analysis and testing of effective systems to clean and visualize student academic performance data for learning analytics.
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Uskov, V.L., Bakken, J.P., Ganapathi, K.S., Gayke, K., Galloway, B., Fatima, J. (2020). Data Cleaning and Data Visualization Systems for Learning Analytics. In: Uskov, V., Howlett, R., Jain, L. (eds) Smart Education and e-Learning 2020. Smart Innovation, Systems and Technologies, vol 188. Springer, Singapore. https://doi.org/10.1007/978-981-15-5584-8_16
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DOI: https://doi.org/10.1007/978-981-15-5584-8_16
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