Identifying Enrollment And Student Success Drivers With Data Governance And AI/ML/Analytics

Identifying enrollment and student success drivers with data governance and AI/ML/analytics
Webinar 2020-09-24 22:30

Never has data-driven decision-making been more critical for post-secondary education.  Tracking students from recruitment through retention, progression, and graduation has become vitally important to the viability of colleges and universities. In this webinar, university administrators Abraham George (Information Technology) and Tom Hackett (Academics) will:

  • Address the need for a comprehensive data governance plan.
  • Outline a path to developing and implementing a successful data strategy.

Significant losses in state funding, declining enrollment, and increased competition have all impacted the work of campus administrators, student support personnel, and faculty members.  Changes in accreditation requirements that hold post-secondary institutions accountable for student performance on learning outcomes, altered perceptions related to costs of education, and new challenges in a post COVID-19 world contribute to the evolving higher education environment.

Many institutions have initiated major efforts in data-driven decision-making. Predictive analytics has proven effective for analyzing patterns, evaluating outcomes, and enhancing decision-making related to enrollment, student learning, and graduation. Without a comprehensive data plan that includes governance, process, analysis, and application, the effective use of data in meaningful ways is negatively impacted allowing consumers and users of data to become overwhelmed by the sheer magnitude of a data tsunami.

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