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Learning analytics (LA) is the collection and analysis of data associated with student learning. The analysis of this data, coming from a variety of sources like the LMS, the library, and the student information system, helps us observe and understand learning behaviors in order to enable appropriate interventions. The reports that an LA application generates can be helpful for instructors (regarding student activities and progress), for students (regarding their progress), and for administrators (regarding course and degree completion data). LA applications help instructors monitor student progress, students evaluate their own performance, and administrators track course and degree  completion. Although still emergent, learning analytics is a rapidly expanding area of research and a practice worthy of exploration.

Through plenary sessions and various institutional case studies, we:

  • Explored learning analytics' potential for positively impacting student learning and instructor effectiveness
  • Understood the concept of learning analytics and how it may be operationalized and deployed at the course level
  • Explored the various perspectives on learning analytics: learner, faculty member, and institutional
  • Learned about the privacy, policy, and ethical issues associated with learning analytics
  • Toured institutional case studies on learning analytics, from design through implementation
  • Explored some initial approaches to begin local learning analytics work

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