Converting Analytics to Insights: Dissolving Divides Across Faculty, Advisors, & Students

Concurrent Session 5

Session Materials

Brief Abstract

Building an intervention approach to advising utilizing an analytics based, predictive case management framework that places students at the center of the learning experience.


Jennifer Barry is the Campus Director for The American Women’s College at Bay Path University. She has been working in the field of higher education since 2006 with the primary focus being on the adult, online learner population. Jennifer has held various leadership roles in both Academic Advising and Admissions departments and has online teaching experience. She is committed to encouraging and empowering students to pursue their dreams and reach graduation. Her work is largely focused on how to improve processes and student satisfaction through efforts that can be scaled for a growing institution. In addition to her contributions to higher education, Jennifer is involved in giving back to her community. Jennifer is an Emerging Leaders Society member as well as a Regional Advisory Board member for the United Way of Central and Northeastern Connecticut. She is also a member of The Town of Enfield’s Beautification Committee. Jennifer received her Master of Science in Organizational Leadership in 2006 from Southern New Hampshire University.

Extended Abstract

Workshop Description

Bay Path University strives to place adult women learners at the center of the learning experience by championing learners' whole needs. Among our key strategies is to drive the evolution from a traditional model for advising to an analytics-based, predictive case management system characterized by automated alerts, pre-determined risk criteria, and established intervention guidelines. The primary goal of this strategy is to prompt student outreach in closest proximity to a precipitating risk event, thereby powering student outcomes.

To better understand learners' whole needs, Bay Path captures key elements of the student experience throughout students' educational journeys. Key experiential elements are extracted in the form of data beginning with an assessment of students' technical capabilities, individual attributes, and life factors prior to matriculation. On an ongoing basis, Bay Path captures engagement in social learning opportunities, weekly academic performance in both adaptive and traditional online courses, enrollment history, and financial aid eligibility. Data captured by the various systems in which students interact (e.g., SmarterMeasure Learning Readiness, Salesforce CRM, Jenzabar SIS, PowerFAIDS, Canvas LMS, RealizeIT adaptive platform) is consolidated within Bay Path's Data Warehouse, thereby comprising the whole learner profile.

Toward the goal of converting analytics to insights, Bath Path is actively working to establish risk markers whereby if triggered, the Data Warehouse auto generates alerts and cases in real-time to members of the Advising team and eventually faculty. Risk markers include, but are not limited to, inadequate learning readiness as evidenced prior to matriculation, grades on weekly assignments, missing assignments, before and after adaptive learning scores, and number of weekly discussion posts. Upon activation of a risk marker, Advisors will receive a case in Salesforce which they will use to assess risk severity, success probability, consult faculty as appropriate, and initiate and/or coordinate students' intervention needs. In a 6-week accelerated cycle, developing the capability to deliver an intervention in close proximity to risk events will be among the features that differentiate the Bay Path experience and propel degree attainment.

Learning Outcomes

  • Discuss the benefits and challenges associated with the development and adoption of an analytics-based, predictive case management model.
  • Identify recommended practices for design, implementation, and adoption of an analytics-based, predictive case management model.
  • Explore preliminary analysis regarding outcomes (pending availability).
  • Working within small groups, create a mini-process map of recommendations for case management suited to your institution's current utilization of technology.

Materials to be Provided

  • PPT for Demonstration section
  • Process Cards for Innovation section

Media Requirements

  • Standard - projector, cable, and internet connection

Program Track - Innovation Lab


  • Session facilitators ask attendees to form groups based on their institution's degree of technology utilization (e.g., high, moderate, low) for advising / wrap-around supports. An institution leveraging a high degree of technology includes those with established process automation, analytics capabilities, and/or use of multiple platforms.
  • In preparation for the Innovation segment, facilitators will organize attendees in 3 - 5 groups of 5 - 8 attendees each depending on session size. Facilitators will then distribute process cards and learner profiles highlighting needs and/or risks typically encountered by adult learners.
  • Each group will choose from the following advising use cases:
    • Learner Profile 1
      • Adult learner
      • First generation college student
      • Transfer credits: 30
      • Degree program: bachelor's with major in psychology
      • Campus type: online only
      • Behavior: satisfactory academic performance throughout mid-term; high engagement initially in peer-based social learning communities; participated in introductory appointment with academic advisor; did not submit assignment for week 6; has not responded to email outreach by instructor
    • Learner Profile 2
      • Adult learner
      • Degree program: bachelor's with major in business
      • Transfer credits: 45
      • Campus type: online only
      • Behavior: submitted application for college admittance well in advance of application deadline; participated in online orientation 1 month prior to start of term; did not complete pre-assignment prior to first day of class
    • Learner Profile 3
      • Adult learner
      • Degree program: associate's in liberal arts
      • Transfer credits: 0
      • Campus type: online only
      • Behavior: participation in self-assessment during orientation program indicates relatively minimal readiness for post-secondary studies; earned grades of 68 and 75 on first two weekly assignments

Demonstration (20 mins)

  • Facilitators describe implementation of an emerging case management model and associated use of analytics to anticipate, identify, and respond to the whole needs of adult learners' within an accelerated, 6-week academic cycle throughout their educational journey.
  • Using analytics sourced from one or more of Bay Path's 4 primary student data systems (e.g., Canvas LMS), facilitators will demonstrate (where possible) its automated case management process beginning with the risk trigger to auto alert / case creation to advisor-initiated case evaluation to faculty coordination and direct student outreach.

Innovation (20 mins)

  • Attendees reflect on practical application in their own instructional context.
  • Using the learner use cases and set of process cards, attendees will work in teams to brainstorm refinements to case management processes, practices, and/or use of technology with particular emphasis on opportunities for Advisor-Instructor collaborations.
  • Process cards will be reflective of the following major process categories while including numerous blank cards to encourage experimentation:
    • Identify learners in need of wrap-around support
    • Alert key process stakeholders
    • Evaluate learner needs and circumstances
    • Take action in response to learners needs
    • Assess impact of intervention
  • Each group will construct a mini-process map to illustrate recommendations for improving case management / outreach effectiveness.
  • Each group will offer a brief report out of process recommendations.