7:30am – 9:00am Registration and Coffee

9:00am – 10:15am Projecting and Managing Enrollment
Speaker: Nathan Fuerst, Director of Admissions, University of Connecticut

In a time of rising costs and limited resources, managing enrollment has become even more so important. When the outlook of our institution is dependent on the behavior of 18 years high school seniors, it is critical that a thoughtful process is involved in managing enrollment. The foundation of managing and meeting enrollment targets are built on data trends and environmental analyses. In this presentation, UConn’s Director of Admissions will share data analysis approaches, both simple and complex, that are employed in projecting and managing enrollment at UConn.

10:15am - 10:30am Break

10:30am – 11:45am But Will It Work on My iPad? Developing a University Key Indicators Dashboard
Speakers:
Ravi Harve, Manager, Data Warehouse / Architecture, Boston College
Dan Riehs, Lead Business Intelligence/Business Analyst, Boston College

Current trends in higher education management emphasize the need for careful review of core metrics to assist University leaders with strategic planning and accountability efforts. This presentation will describe how Institutional Research and Information Technology have worked collaboratively to implement a Key Indicators Dashboard delivered as a Cognos Active Report.

Two main topics will be addressed during the session: (1) presenters will outline how metrics and comparison institutions, the primary components of the dashboard, were generated and the challenges associated with the demand for value-added analyses within the dashboard; (2) presenters will also discuss the ETL methods used to integrate a variety of data sources (IPEDS, survey responses, Data Warehouse data) at both point-in-time and trend views and the trials surrounding the report’s presentation as an iPad-ready Cognos Active Report. The final version of the Key Indicators Report will also be demonstrated enabling end users to assess how business intelligence tools can be leveraged to meet business needs.

11:45am – 12:45pm Lunch

12:45pm – 2:00pm Predicting Longer-Term Outcomes From Automated Measures of Engagement and Affect
Speaker: Ryan Baker, Associate Professor, Department of Human Development, Teachers College, Columbia University

In recent years, researchers have been able to model an increasing range of aspects of student interaction with online learning environments, including affect, meta-cognition, robust learning, and engagement.

In this talk, I discuss how automated detectors of engagement and learning can be used in prediction of long-term student outcomes, illustrating this with examples of how affect, engagement, and learning during middle school use of educational software can support prediction of student long-term success, including end-of-year learning, decisions about whether to attend college several years later, and even what major a student chooses after enrolling in college. These predictive models can in turn support inference about what factors make a specific student at-risk for poorer learning or lower long-term engagement in learning.

2:00pm - 2:15pm Break

2:15pm – 3:30pm Becoming a Data Scientist: Skills and Knowledge You Need
Speaker: Juliane Schneider, Metadata Librarian, Countway Library of Medicine, Harvard Medical School

Recent studies suggest that there will be a shortfall in the near future of skilled talent available to help take advantage of big data in organizations. Meanwhile, government initiatives have encouraged the research community to share their data more openly, raising new challenges for researchers. Librarians can assist in this new data driven environment. Data Scientist Training for Librarians is an experimental course being offered by the Harvard Library to train librarians to respond to the growing data needs of their communities. In the course, librarians familiarize themselves with the research data lifecycle, hands-on, using the latest tools for extracting, wrangling, storing, analyzing and visualizing data. By experiencing the research data lifecycle themselves, becoming data savvy and embracing the data science culture, librarians can begin to imagine how their services might be transformed.

3:30pm End