Learning Resources

Abstract: Literature points out that big data and analytics (BDA) still fails to positively influence institutional planning—even though it's promoted as a novel approach to improving efficiency and effectiveness. What limits the usefulness of BDA? Researchers point to a lack of conceptual models that translate information into meaningful signals. Nonsense! We're using a metrics-based planning framework that's producing remarkable outcomes. We'll share our framework and how you can apply this concept at your institution.

Abstract: Working across boundaries is essential for student success, but also incredibly difficult to do. This session looks at the collaboration between enrollment management and departmental faculty—specifically the planning, monitoring, and communication of student progress in an online doctoral program. You will learn techniques to improve communication between departments that historically work independent of each other, along with opportunities for future interdepartmental partnerships that improve student success.

Abstract: There is increased demand to provide facilities that encourage student success. But how do you know if a space "works"? We will focus on how you can link your facilities planning to measurable student success. After reviewing broader national trends, we'll discuss metrics for student success and how space contributes to student success. Finally, we'll focus on tools and solutions that your institution can incorporate into its facilities planning process to ensure your learning spaces contribute to student success.

Abstract: The City University of New York's (CUNY) Accelerated Study in Associate Programs (ASAP) assists students in earning associate degrees within three years by providing a comprehensive range of financial, academic, and personal supports. Completion rates at community colleges remain extremely low; however, CUNY's ASAP students earned their associate degrees at substantially higher rates than non-ASAP students, even when a longer timeframe was considered. In this session, you will learn about CUNY's ASAP model, how it receives operating and capital funding, and how the physical spaces that support the program were identified, designed, and renovated.

Abstract: Data is only as powerful as your understanding around it. Analytics makes possible new understandings of students and their needs, and creates an advanced ability to improve student success through use of new software being implemented on campuses around the world.

This handbook is designed to help any higher ed leader unleash the power of data that is always available but seldom leveraged. It helps to answer the questions, (1) How does a campus strategically develop a plan for use of analytics in better supporting their students? (2) Once a culture is in place, how do leaders effectively move new evidence into action? This primer walks readers through each step of the analytics adoption.

Abstract: Academic strategic planning can be difficult given the bevy of stakeholders and often multiple sets of accreditation criteria. Recognizing the limits of the traditional SWOT model, our program chose to use the Strategic Planning Engine model. The model itself is quite laborious, and to increase its usability, we simplified the environmental assessments. Our results proved to be useful and relevant, and we developed a series of feasible objectives. In this article, we describe and evaluate our experience. In comparison to SWOT, we found this process to be more objective and replicable, scalable and responsive to multiple criteria, flexible to accommodate changing strategic plans or criteria, and transparent. With that being said, we caution about the level of labor required and organization and communication needed. Finally, we recommend implementing a leadership team, a communication plan, and a plan on how to respond to uncontrollable circumstances and developing a level of comfort with limited resource allocation.

Abstract: Planners and institutional leaders need to understand the relevance of digital capabilities and IT capacity as they relate to student success. This session will improve your understanding of digital capabilities needed to achieve student success and discuss how you can inform integrated planning efforts with IT benchmarking data. You will learn how to assess your institution’s digital capacity for student success technologies so you can affect costs and improve outcomes with new analytics tools and services.

Abstract: Institutions are managing numerous student success initiatives simultaneously, but they lack the necessary data and infrastructure to evaluate outcomes. They also struggle to clearly link a particular initiative to a specific individual outcome. Using prediction-based propensity score matching (PPSM), a methodology compliant with the U.S. Department of Education’s What Works Clearinghouse’s requirements, we facilitated the analysis of key initiatives to measure efficacy, ensuring that outcomes of students participating are compared to control students with similar propensity. The recent work explored in this article helps two institutions understand the impact of their innovation and more precisely scale student support.

Abstract: The past two decades have seen great social change and both massive consolidation and expansion of institutions of higher education, clearly presenting circumstances warranting the use of formal approaches to planning. Varying planning theories, past failures and successes, and differing circumstances have generated several partially contrasting planning models to guide organizational change. Therefore, institutions of higher education have a variety of such approaches from which to choose. This article presents a case study illustrating the use of several approaches to planning that is distinctive because it relies heavily upon experience-based planning, examples of which are unfortunately lacking in the literature base.