Abstract
Data cleaning is a complex, multi-step process of modifying input data to ensure that it is free of irrelevant, incorrect, duplicated and/or incomplete data. It accounts for about 60% of the work by data scientists. Data cleaning in companies, business and organizations requires 1) an availability of knowledgeable and experienced expert(s) in a designated area of business operation (for example, teaching/learning, enrollment, sales, manufacturing, etc.), 2) a specialized set of data cleaning tools for automatic and/or manual modification of data, and 3) well-defined data cleaning techniques/procedures and secure protocols of working with corporate/organizational data. These days it is important not just to teach a new subject or topic, but also to teach it in a smart way - using smart pedagogy - with the goal to maximize student learning outcomes. This paper presents the up-to-date findings and outcomes of a multi-aspect project in the Department of Computer Science and Information Systems, the Department of Education, Counseling and Leadership, and the InterLabs Research Institute in Bradley University (IL, USA) that is aimed to design, develop and test the innovative data cleaning curriculum based on corresponding features of smart pedagogy.
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Uskov, V.L. et al. (2022). Smart Pedagogy-Focused Design and Development of Innovative Curriculum for Data Cleaning. In: Uskov, V.L., Howlett, R.J., Jain, L.C. (eds) Smart Education and e-Learning - Smart Pedagogy. SEEL-22 2022. Smart Innovation, Systems and Technologies, vol 305. Springer, Singapore. https://doi.org/10.1007/978-981-19-3112-3_3
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DOI: https://doi.org/10.1007/978-981-19-3112-3_3
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