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Global supply chains span multiple countries and regions, and diverse cultural and competitive nuances distinguish them. To manage their international operations as efficiently as possible, companies must understand these differences and how they influence supply chain practices and priorities. This article explores how approaches to key elements of supply chain management vary across geographies, particularly […]
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The project aims to support online learners’ self-regulated learning, performance, and retention by designing a learning analytics dashboard (LAD). The research questions: LAD design process: To address the theoretical gap and context-specific needs, we focused on four design dimensions as below: Meta-LAD: Key Findings: We currently completed the LAD design and usability testing. From usability […]
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The project aims at increasing learners’ engagement in massive, open, and online education in Supply Chain Management by applying learning analytics.
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In this project we investigate the fundamental trade-off involved with providing an educational platform for both learning and assessment, and propose strategies to ensure academic integrity in a MOOC-based program
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This research aims to develop a data-driven framework to evaluate design changes in MOOCs. We explore a change from multiple angles-process, proficiency, and perception- and apply various analytical methods-temporal, causal and predictive to map out the outcome of instruction along multiple dimensions of learning.
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This research aims to identify the likelihood of dropping out from a MOOC-based program. Program dropout happens both, within and between courses. We identify the key dropout factors and develop a machine learning model to predict future student dropout.