All too often, digital learner data ethics and its accompanying commitment to learner privacy are viewed as obstacles to innovation using learner analytics. This tension between assessing progress and student privacy has heightened during the pandemic. Finding the right balance is critical in today's all-in digital learning environments, as are the ability to use learner data to promote student success, a focus on inclusivity in course design, and data-informed decisions about digital learning methods and programs. The opportunity to use learner analytics to improve student success should not be hamstrung by a lack of digital data ethics, guidelines, principles, policies, procedures, and accountability. In this presentation, Instructure, Rutgers University, and Unizin will describe their diverse but convergent perspectives regarding learner data ethics. Can strong data ethics serve as the rails to empower the collection, analysis, and applied use of learner data for the common good? The purpose of a learning management system, a university, and Unizin is to promote student success by providing new insights that inform innovation in teaching and learning. Participation in this session will provide attendees with an opportunity to explore how protecting individual privacy, acting as the secure custodian of learner data, and establishing learning analytics guidelines can further educational opportunities and success by learners of all types.
