Learning Resources

Abstract: For the past decade, Georgia State University (GSU) has been at the leading edge of demographic shifts in the Southeast region. Using data to inform systematic institutional change, GSU has doubled its enrollment of underrepresented populations, raised graduation rates by 70 percent, and closed all achievement gaps based on race, ethnicity, and income level. Through a discussion of innovations—from AI-enhanced chatbots and predictive analytics to meta-majors and micro-grants— this keynote will share lessons learned from GSU's transformation and outline concrete and scalable steps that you can take on your campus to improve outcomes for underserved students while increasing revenues.

Abstract: For the past 20 years, higher education has invested heavily in improving student success, using new data and analytics systems, tools, and practices. Improvements and progress across higher education have mostly failed to meet expectations. But the arrival of next-generation artificial intelligence (AI) provides an exceptional opportunity. By combining AI with human intelligence (HI), we can create a powerful collaborative intelligence that can be embedded in learning processes, tools, and practices, enterprise-wide. AI can accelerate the long-overdue transformation of higher education. This article describes how to combine AI and HI in collaborative intelligence to significantly improve student success.

Abstract: Institutional success depends on long-term sustainability, connecting investments with outcomes, and creating a culture that is data-informed. As the role of institutional effectiveness expands across higher education, designing a comprehensive integrated planning process is critical. Integrated planning requires a unified approach to utilizing academic and administrative data for continuous improvement. However, this can be an overwhelming process for institutions, with many unsure of where to start. Learn from leaders in two different accreditation regions as they share best practices and lessons learned associated with their integrated planning evolution and its impact on operational efficiency and student learning.

Abstract: Higher Education Systems Redesigned: From Perpetuation to Innovation to Student Success
Edited by Jonathan S. Gagliardi and Jason E. Lane
SUNY Press: Albany, New York: 2022
ISBN: 9781438487670
252 Pages

Abstract: This article is based on follow-up survey research from a doctoral case study that highlighted effective retention practices for low-income and/or single mothers who were students within the Women in Transition (WIT) program at Charter Oak State College. The concept of retention in this instance is an enrollment management practice aimed at maintaining a student population while aiding the institution in sustaining organizational success. Emphasis is placed on the retention concepts of social and academic integration that enabled the specific population to persist and succeed.

Abstract: Curriculum complexity impacts several aspects of student success, including time to degree, persistence, and the accumulation of student debt. This article describes the process of measuring and analyzing course prerequisites and sequencing. It outlines strategies to engage campus leadership and faculty in effectively improving curriculum and ensuring that support services are focused on the greatest area of need.

Abstract: In the Spring 2020 SCUP Trends report, most colleges and universities excel at collecting data, but struggle when it comes to effectively using that data to improve teaching and learning or business operations. According to the article, the key to success is a robust cross-institutional strategy that engages multiple stakeholders.

But what does that look like in practice? We reached out to Colleen Carmean, former associate vice chancellor for academic innovation, University of Washington-Tacoma, for her insights.

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: Student success analytics promise to dramatically improve our capacity to increase student success across the entire spectrum of the student life cycle and throughout the student experience. Institutions will move beyond institutional accountability statistics to improve performance at the level of student success processes, practices, and interventions. Ultimately, these new processes, practices, and interventions promise to enable institutions to reinvent and personalize approaches to success.
By leveraging analytics and data science, leading-edge institutions “optimize” student success for individuals and cohorts by making student success a mission-critical, overarching institutional strategy. “Student success science” is a critical ingredient in reimagining higher education. This article provides a road map for institutional leaders on how to raise their analytics IQ so that they can leverage these practices to better serve their students, improve performance, and demonstrate value.
The use of analytics is potentially a key ingredient in sense making and decision making in all aspects of institutional performance and is critical in improving student success. Enlightened higher education leaders are committing to analytics and data science that deliver active interventions that improve student success.

Abstract: This article uses the results of a national study to propose several multidimensional planning models for institutional planners and researchers. It focuses on developing, supporting, and using a number of dimensions within six domains that the research study identified as important factors for inclusion in planning models. The domains are external influences on student assessment, institutional context (type, control, and size), institutional approach to student assessment, institution-wide support for student assessment, assessment management policies and practices, and uses and impacts of student assessment.