Institutional staff such as enrollment managers, business officers, and institutional researchers are often asked to predict enrollments. Developing any predictive model can be intimidating, particularly when there is no textbook to follow. This paper provides a practical framework for generating enrollment projection options and for evaluating…

This article describes the step-by-step process of how data science, marketing and communications, and higher education improved access and success for students. Over the last three years, strategic planning efforts helped develop a data-informed culture on campus. The work described within the playbook required time, energy, and a lot of…

In recent years we have developed a data analytics pipeline using artificial neural networks to predict prospective student matriculation for university admissions using very limited demographic data. Predictions are generated at the earliest stages of the admissions process and successfully inform recruiting and admissions staff about the…

Effective strategic enrollment management (SEM) efforts require vast amounts of internal and external data to ensure that meaningful reporting and analysis systems can assist managers in decision making. A wide range of information is integral for leading effective and efficient student recruitment and retention programs. This article is designed…

This article explores implementation of strategic enrollment management (SEM) at a two-year college and why SEM is critical to the long-term viability of an institution. This article also outlines the five initial steps needed to implement SEM, including identifying SEM leadership, building a SEM committee, developing a common understanding of…

Interest on the part of the American Association of Collegiate Registrars and Admissions Officers (AACRAO) Board of Directors in the development of a set of descriptions of the core competencies for AACRAO professions goes back several years, with more active discussion beginning in 2011 under the leadership of AACRAO President Nora McLaughlin. At…

This article describes a model that can be used to analyze student enrollment data and can give insights for improving retention of part-time students and refining institutional budgeting and planning efforts. Adult higher-education programs are often challenged in that part-time students take courses less reliably than full-time students. For…

The authors describe an innovative technique for using Classification and Regression Tree (CART) with student characteristics, including geographical data for analyzing student enrollment patterns between students who enroll within a community college district (stayers) and those who enroll outside the district (movers) at neighboring community…

The authors provide an overview of data mining, giving special attention to the relationship between data mining and statistics to unravel some misunderstandings about the two techniques. (Contains 1 figure.)

As a tour de force, data mining is likely to gain wider use in the next few years. To facilitate this transition, we make several recommendations addressed to both institutional research professionals and the Association of Institutional Research.

In responding to internal and external pressures for accountability in higher education, especially in the areas of improved learning outcomes and student success, IT leaders may soon become critical partners with academic and student affairs. IT can help answer this call for accountability through "academic analytics," which is emerging…

Transfer is a primary strategy for providing access to baccalaureate-level education in Washington State. For thousands of students, transfer is an effective and efficient way to complete their studies. About 41 percent of the 16,800 students awarded degrees at Washington public baccalaureate institutions in the 2000-2001 academic year had…