New Practices of Personalized Learning: Privacy and Autonomy

ID: 53462 Type: Full Paper
  1. Heather Greenhalgh-Spencer, Texas Tech University, United States

Wednesday, October 17 10:45 AM-11:15 AM Location: Las Vegas Ballroom 3 View on map

Presider: Mary Jo Parker, University of Houston-Downtown, United States

Abstract: Personalized Learning (PL) is a new model of teaching and learning that attempts to disrupt traditional models of schooling. PL leverages the use of digital technology to create personalized pathways of learning for each student. PL involves changes in roles for teachers and students, as well as new pedagogical strategies. PL relies on, and generates, a great deal of data that is then further leveraged to support student learning. In this paper, I analyze some of the complexities that PL invokes regarding concepts of autonomy and privacy. I choose to focus on these concepts because, in my experience as a practitioner, mentor, and researcher in PL, autonomy and privacy are two issues that are intimately intertwined with the ‘pillars of personalized learning’. In all of these areas, autonomy and privacy play key roles. In order to dig deep into the ways that autonomy and privacy play out in personalized learning, I begin by defining PL and describing two key components of PL: data-driven instruction and student agency. I then flesh out some of the questions that a philosophical orientation on autonomy and privacy open regarding PL pedagogical strategies and ideological goals.

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