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Planning for Higher Education Journal

Published
May 15, 2020

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Reduce Curriculum Costs While Increasing Student Enrollment

Optimizing Academic Balance Analyses Let Kentucky Institutions Stay Competitive

Results of the study supplied evidence needed to support tough institutional decisions. The 13 Kentucky colleges and universities that participated in the research now have critically important data to use in making choices about how they best serve their students, maximize scarce resources, and sustain financial stability.

From Volume 48 Number 3 | April–June 2020

Abstract: An Optimizing Academic Balance (OAB) analysis provides colleges and universities with effective tools to use in making strategic academic decisions needed to stay competitive in the context of institutional mission, program quality, market potential, cost, and revenue. The Association of Independent Kentucky Colleges and Universities recently completed a three-year statewide OAB project with the participation of 13 higher education institutions. The results supported the colleges and universities in making tough decisions.


A Follow-Up

An introduction to the Optimizing Academic Balance process and early results of the research were published in the 2015 Planning for Higher Education article, “Reshaping Your Curriculum to Grow the Bottom Line,”. The current article, with final research data, represents the study’s wrap-up report.

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Planning for Higher Education Journal

Published
April 16, 2020

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Can You Trust Your Eyes?

Learn How to Minimize Misinterpretation of Data Reports and Visualizations

Volumes of data are available to administrators to support decision-making. But that doesn’t mean that what’s been presented is accurate. When data are misused or misconstrued, senior leaders at higher education institutions may make the wrong conclusions, ineffective policies may be enacted, and students may not be successful in completing their academic goals.

From Volume 48 Number 2 | January–March 2020

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.

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Planning for Higher Education Journal

Published
July 1, 2016

A Call to Action for Student Success Analytics

Optimizing student success should be Institutional Strategy #1.

From Volume 44 Number 4 | July–September 2016

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.

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Planning for Higher Education Journal

Published
October 1, 2007

Traffic Congestion on a University Campus

A Consideration of Unconventional Remedies to Nontraditional Transportation Patterns

Universities are in a special position to take information related to the patterns and causes of congestion and apply it to their planning goals. In particular, they can work effectively to reduce demand.

From Volume 36 Number 1 | October–December 2007

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.

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Planning for Higher Education Journal

Published
April 1, 2006

Visualization of Academic Efficiency and Productivity

The author describes a method to display a variety of quantitative information in a compact, easy-to-understand way, providing an analytical tool useful in analyzing and comparing the relative strengths and weaknesses of an academic unit over time or in comparison with others.

From Volume 34 Number 3 | April–June 2006

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.

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Planning for Higher Education Journal

Published
December 1, 2004

Faculty Mentoring: What the Boyer Commission Forgot

A proposed mentoring program using “strategic collaboration” to improve learning by motivating and enabling faculty to become better undergraduate teachers is suggested in support of the Boyer Commission’s goals.

From Volume 33 Number 2 | December–February 2004

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.

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Planning for Higher Education Journal

Published
April 1, 1999

Decision-Making Challenges in Student Affairs

From Volume 27 Number 3 | Spring 1999

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

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Planning for Higher Education Journal

Published
April 1, 1973

Consortia

The Decision-Makers

Consortia, their impact on cooperating institutions, and critical factors in inter-institutional planning were the subject of a recent study for the United States Office of Education. This article, by staff members of one of the the studied consortia, is devoted to a discussion of the process of consortium decision-making.

From Volume 2 Number 2 | April 1973

Abstract: Consortia, their impact on cooperating institutions, and critical factors in inter-institutional planning were the subject of a recent study for the United States Office of Education, directed by Harold L. Hodgkinson of the Center for Research and Development in Higher Education at the University of California at Berkeley. The critical issues, according to the study findings, are problems of reciprocity and autonomy, coordination of programs among diverse institutions, and strategies for campus involvement and leadership. The following article, by three staff members of the New Hampshire College and University Council—one of the consortia in the Hodgkinson study—is devoted to a discussion of the process of consortium decision-making, touching on the three key issues. The authors are: Lynn G. Johnson, the Council's associate director in charge of academic programs; Dr. William W. Barnard, consultant and coordinator of a two-year Cooperative Curriculum Project, and Douglas W. Lyon, coordinator of January Term Programs and communications coordinator.

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