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Planning for Higher Education Journal

Published
April 26, 2022

The Future of Planning is . . .

. . . Aligned, Integrated, and Collaborative Institutional Effectiveness

IE professionals are both translators and integrators—and universities need these people who know how to interpret the data. Within the context of an IIE office, they assist in developing data-informed strategic plans, financial forecasts, enrollment plans, and other assessments of institutional efficacy.

From Volume 50 Number 3 | April–June 2022

Abstract: The institutions that will thrive in the future will be those that use high-quality, relevant mission-driven data as part of their strategic, integrated planning process. Because of this it is imperative to create integrated institutional effectiveness (IIE) offices that serve as the connective tissue among all units within a college or university. The data and expertise of institutional effectiveness can be leveraged to benefit the institution as a whole. In this article, we discuss the value of creating an IIE office and challenges associated with a centralized infrastructure.

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Planning for Higher Education Journal

Published
November 15, 2021

Book Review: Big Data on Campus

Data Analytics and Decision Making in Higher Education

From Volume 50 Number 1 | October–December 2021

Abstract: Edited by Karen L. Webber and Henry Y. Zheng
Johns Hopkins University Press: Baltimore: 2020
324 pages
ISBN: 978-1-4214-3903-7

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Planning for Higher Education Journal

Published
May 15, 2020

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

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
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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