The Learning Analytics Research Network (NYU-LEARN) is pleased to invite you to our first Learning Analytics Conversation Series of the semester, engaging with two different perspectives on how we can responsibly use learning analytics to support academic advising within higher education.
Join Tinne De Laet from Katholieke Universiteit Leuven and Kyle Jones from Indiana University-Indianapolis along with Emily Schlam from Senior Director, Student Success at NYU for a timely conversation about questions of academic advising using learning analytics.
Tuesday, October 19, 2021
12 pm - 1 pm ET
Our Learning Analytics Conversation Series format has each expert provide a brief overview of their work in the area, followed by a moderated dialogue about commonalities, differences and emergent high level principles. The end of the session is reserved for questions from the audience.
AI for Academic Advising, a Matter of Trust?
Dr. Tinne De Laet is associate professor at KU Leuven, Belgium. She also chairs the Tutorial Services of Engineering Science, a service that advises and supports students throughout their engineering studies. In her research she tries to brings research in AI and learning analytics to advising practice.
Advising, Nudging, or Coercing? Ethics of Advising Analytics
Dr. Kyle M. L. Jones is an assistant professor at Indiana University-Indianapolis (IUPUI) in the United States. He researches information ethics and policy issues, such as student privacy and trust, associated with learning analytics in the context of American higher education.
Conversation Moderated by
Dr. Emily Schlam is the Senior Director of Student Success at New York University. In this role, she serves as a subject matter expert and consultative resource for university partners on issues related to student retention, graduation, and enhancing the student experience. Emily also guides university-wide committees where students, faculty, and administrators identify opportunities to support and enhance student success efforts. Emily’s research focuses on organizational complexities within higher education and their impact on student retention and persistence.