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

9:00am - 9:20am   Welcome/Opening Remarks/Introductions

9:20am - 9:45am   Promise and Value of Analytics to Inform Campus Decisions – a perspective from Academic Leadership
Speaker: Amber Vaill, Vice President for Academic Affairs, Becker College

College and university senior leadership teams are regularly faced with the task of making challenging decisions. Having easy access to the right types of data can greatly assist leaders in making informed decisions that will have the best impact on the institution. Having the right data allows leaders to determine what support services will have the greatest impact on student success and persistence. In this session we will discuss the important role that data plays in the decision-making tasks leaders face and what information is most critical to making decisions surrounding student success.

9:45am - 10:30am   Lessons from the Field –Using Open Source Tools to Build an Academic Analytics Framework
Speakers:  
Jing Qi, Learning Analytic Lead and LMS Specialist, Dartmouth College
William Cowen, Software Engineer, Dartmouth College

Building an agile and scalable platform that supports course-level learning analytics, which informs student course engagements in an LMS. Faculty can then leverage student content access, discussion interaction and quiz performance data to evaluate the efficacy of course materials and content design, moreover, to facilitate an effective learning community.

10:30am-10:45am  Break

10:45am-12:00pm Lessons from the Field – Developing a Course Completion Predictive Framework on a Modest Budget
Speaker:  David Demers, Chief Information Officer, University of Maine System

This session will focus on a combined SIS & LMS data mining approach to build robust predictive models for course completion and student success using readily available, low-cost tools.  In this session, participants will explore the benefits of examining granular, transactional elements within the LMS to identify students who may be at risk of struggling in a course and apply predictive scores to devise a scalable intervention strategy.

12:00pm - 1:00pm    Lunch

1:00pm - 2:00pm     Lessons from the Field – Building Student Success with Industry Partners
Speaker:  Rich Silva, Senior Director Administrative Computing, Bay Path University

This session will review Bay Path University’s predictive analytics journey beginning with the engagement of an analytics partner and the creation of an initial predictive model through the completion of the partnership and the transition to bringing data mining and modelling in-house. This presentation will include a discussion of the types of data that were utilized and how intervention strategies were developed to leverage the data points.

2:00pm - 3:00pm   Hands-On Activity: The Art of Utilizing Predictive Scores – Balancing Response and Scale

In this activity, participants will have an opportunity to apply a predictive model to score a student dataset and determine appropriate thresholds for intervention responses for a mock institution.

3:00pm   End