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Saturday, March 19 • 11:00am - 11:45am
Taming Big Data in MOOCs

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The rise of massive open online courses (MOOCs) has generated a high volume of learners' data available to higher education institutions. These data have been mainly used by these institutions for analytics purposes, providing essential information about students' engagement, drop-out rates, and different learning preferences. However, dealing with big data prompts questions such as: What are the proper ways to fully understand the complexity and amplitude of these data? How can technology be used as an ally in the process of cleaning and understanding these data for future decisions regarding online teaching and learning? How can data integrity be managed and maintained?

The process of answering these questions reveals challenges imposed by the nature of big data in the context of MOOCs. In this panel, we invite the Penn State community to discuss best practices for taming big data in MOOCs. Attendees will learn about selecting and combining various tools and technologies to process, transform, and analyze data and to communicate effectively as a team. Our panel will present our experiences both from the research and technical perspectives and will include a lively Q&A session. Providing tools and critical considerations to deal with the data will be beneficial for researchers and their teams in providing clean data for accurate insights and prediction models. Outcomes of our panel have the potential to ignite a collaborative work group about best practices in coding and data mining when dealing with big data generated by MOOCs.


Saturday March 19, 2016 11:00am - 11:45am
Room 109

Attendees (3)