Learning Resources

Abstract: Data analytics related to student and institutional performance have evolved quite rapidly—and continue to advance—as the field of data science captures more attention across the higher education sector. And while data-informed decisions can help institutional leaders achieve their goals, there are increasing examples of analyses or visualizations that, when presented without the proper framework, result in misinterpretation and inaccurate conclusions. Context is critical, and erroneous deductions may lead to decisions that adversely affect student performance, program development, and policy changes.

Abstract: The services required to support the strategic work of universities often exist in silos, and this disconnection can impede the advancement of new initiatives. To prepare for a complex new program, a number of analytical processes need to occur—background research, environmental scans, and benchmarking. To develop the initiative, strong facilitation and project management skills are also required. To ensure the initiative’s success, careful space planning and financial planning must exist along with the development of evaluative measures to monitor progress. This article describes how one university combined these services into a single department to more effectively support the strategic work of schools, divisions, and campus-wide programs.

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: U.S. transportation data suggest that the number of vehicle miles traveled has far surpassed new capacity, resulting in increased traffic congestion in many communities throughout the country. This article reports on traffic congestion around a university campus located within a small town. The mix of trip purposes varies considerably in this context, with the majority of trips related to student movement to and from classes. The university itself becomes a major traffic generator, but in a complex way. This article describes how congestion in a university setting differs from that in a nonuniversity setting; what components drive this congestion; how best to reduce this congestion while adhering to overall university planning objectives; and how to set a foundation for traffic management strategies that provide environmental, social, and economic benefit to the university and, importantly, to the surrounding community. The information presented here applies beyond the campus setting to any community that contains nontraditional traffic generators and shows why context does matter when analyzing and managing traffic.

Abstract: A simple and readily understandable visual display of quantitative measures of academic efficiency and productivity is demonstrated in this article. This graphical construction facilitates annual comparisons of unit efficiency and productivity as well as an analysis of temporal changes in unit activity. By establishing a common framework upon which a data-driven conversation regarding unit activity is constructed, this method produces a single graphical representation of the activities of any academic unit. As such, this technique assists academic decision makers with goal setting, resource allocation and reallocation, and the program prioritization process.

Abstract: In 1998, a Carnegie Foundation Commission Report criticized America’s 123 research universities for failing our educational system by ignoring undergraduate education. Notably absent from the Commission's list of recommendations was mentoring research university faculty as a strategy to improve their teaching. This article discusses strategic collaboration, a mentoring model that can contribute significantly to achieving this objective. Such a network can also create an environment conducive to interdisciplinary research that, because of its increased value and rewards at such universities, can provide an added incentive for faculty participation.

Abstract: Book Review of A Guide to Decision Making in Student Affairs: A Case- Study Approach, by Stanley R. Levy and Charles E. Kozoll. Charles C. Thomas, Publishers, Ltd., 1998. 178 pages. ISBN 0-398-06871-2