This session will give participants an overview of the projects undertaken by the 2013 and 2014 Provost's Learning Analytics Fellows.  Presentations will include:

Chemistry Placement at the University of Michigan: Burdening At-Risk Students While Propelling Others?

Ginger Shultz, Amy Gottfried, and Grace Winschel

Learning Analytics: Insights into Introductory Biology

Laura Olsen, Anna Cihak, Marc Ammerlaan, Priscilla Tucker, Matt Chapman

Invenire: Course Exploration Guide

Edgar Nuñez, Ying Ying Liu, Kimberly Springer, Maura Youngman, Raymond Alexander

Online and Distance Education at U-M Ann Arbor: What We Can Learn From U-M's Data Warehouse

Inger Bergom

Name That Scenario - An Online Study Tool for Stats 250

Barsaa Mohapatra, Jared Tritz, Karen Nielsen, Brenda Gunderson

Perceptions and Use of an Early Warning System During a Higher Education Transition Program

Stephen Aguilar & Steve Lonn

What Correlates With Student Achievement in Introductory Astronomy?

Eric Bell

How do LSA Students' Course Choices React to Calculated Shocks to Their Grades?

Julian Hsu

Who Majors in Philosophy and Why (or Why Not)? Survey and Warehouse Data from U-M Philosophy Students

Sarah Aronowitz, Robin Zheng

MOOC Video Access Patterns

Stephanie Wooten, Christopher Brooks

Visualizing Pedagogy with Instructor-to-Student Feedback

Adam Levick, Kevyn Collins-Thompson

Building a Better Course Recommender Tool

Eric Koo, Sanmeet Kanhere, Michelle Fiesta

Contextualizing Gendered Performance in Engineering 100

Stephanie Sheffield, Robin Fowler

How to Improve the Interaction Between Instructors and Students through LectureTools Data

Lu Liu, Perry Samson

An Exploration of Learning Analytics at the School of Dentistry

Janée Tyus, Vidya Ramaswamy

Effects of Text-based and Image-based Activities on Student Learning Outcomes

Anne Greenberg, Melissa Gross, & Mary Wright

The Student Learning and Analytics at Michigan (SLAM) Seminar series features both U-M faculty and visitors from other campuses, focusing on the use of data about students, courses and academic programs -- for the purposes of improving teaching and learning. For more information about learning analytics at U-M and to view videos and slides from past SLAM presentations, click here.