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Llorance, Leezet – Association for Institutional Research, 2020
The purpose of this research study was to explore the process, implementation, and impact of a business intelligence (BI) strategic system at Lone Star College--Tomball Campus (LSC-T), Texas, to determine the effectiveness of BI on community college decision-making. This research study (a) explored the process of implementing a new BI strategic…
Descriptors: Community Colleges, Decision Making, Management Information Systems, Program Implementation
Chan, Monnica; Kwon, Jihye; Nguyen, David; Saunders, Katherine M.; Shah, Nilkamal; Smith, Katie N. – Association for Institutional Research, 2020
Students are increasingly likely to use student loans to finance their postsecondary education. This article examines how students' use of federal loans changed from 2000 to 2016 by students' family income group and parental education level. We use logistic regression analysis and nationally representative data from the National Postsecondary…
Descriptors: Student Financial Aid, Paying for College, Family Income, Parent Background
Cornett, Jeffrey L. – Association for Institutional Research, 2020
Single measures of college performance fail to reflect the mix and diversity of students served. First-time students vary widely in terms of their readiness to succeed in college. Higher education environments (ecosystems) also vary widely and afford students differing admission and transfer opportunities. These factors confound college completion…
Descriptors: Graduation Rate, College Graduates, Student Diversity, College Readiness
Bloomfield, Amber; Rose, Bess A.; Preston, Alison M.; Henneberger, Angela K. – Association for Institutional Research, 2020
Brain drain--the movement of high school and college graduates out of state for employment--is a concern for state policymakers. This study focuses on brain drain of students who graduate from high school in Maryland. Using data from the Maryland Longitudinal Data System and applying propensity score matching to control for differences between the…
Descriptors: Brain Drain, Migration Patterns, Relocation, Student Mobility
Pastor, Dena A.; Foelber, Kelly J.; Jacovidis, Jessica N.; Fulcher, Keston H.; Sauder, Derek C.; Love, Paula D. – Association for Institutional Research, 2019
James Madison University has used dedicated Assessment Days for more than 30 years to collect longitudinal data on student learning outcomes. Our model ensures all incoming students are tested twice: once before beginning classes and again after accumulating 45-70 credit hours. Although each student completes only four instruments during a 2-hour…
Descriptors: College Outcomes Assessment, Student Evaluation, Universities, College Students
Anderson, Rebekah; Rip, Nichole – Association for Institutional Research, 2019
The main purpose of institutional research (IR) is to provide objective, systematic, and thorough data that support an institution's enrollment goals, planning, policy formation, and decision making. Traditionally, institutions gathered data on their activities, students and staff, programs, management, and operations. University staff then…
Descriptors: Institutional Research, Data Use, Decision Making, Private Colleges
Umbricht, Mark; Stange, Kevin – Association for Institutional Research, 2019
Every term, institutions of higher education must make decisions about the class size for each class they offer, which can have implications for student outcomes, satisfaction, and cost. These decisions must be made within the current higher education landscape of tightening budgets and calls for increased productivity. Beyond institution decision…
Descriptors: Class Size, Higher Education, Student Experience, College Students
Gandy, Rex; Crosby, Lynne; Luna, Andrew; Kasper, Daniel; Kendrick, Sherry – Association for Institutional Research, 2019
While Markov chains are widely used in business and industry, they are used within higher education only sporadically. Furthermore, when used to predict enrollment progression, most of these models use student level as the classification variable. This study uses grouped earned student credit hours to track the movement of students from one…
Descriptors: Markov Processes, Enrollment Projections, Higher Education, College Credits
Association for Institutional Research, 2018
Higher education institutions in the United States have collected and analyzed data for decades. From mandatory reporting for state and federal compliance to ad hoc reporting for internal and external stakeholders, there are myriad business purposes for which administrators, staff, and faculty routinely gather data. As more colleges and…
Descriptors: Colleges, Data Collection, Data Analysis, Strategic Planning
Fulcher, Keston H.; Smith, Kristen L.; Sanchez, Elizabeth R. H.; Sanders, Courtney B. – Association for Institutional Research, 2017
Higher education insiders trumpet the use of results for improvement as the most important part of the assessment cycle. Yet, at the same time, we acknowledge the rarity of improvement, especially at a program level. What are some reasons the most important phase of assessment occurs so infrequently? To seek answers, we investigated the "Use…
Descriptors: Information Utilization, Higher Education, Program Evaluation, Program Improvement
Chatman, Steve – Association for Institutional Research, 2017
Whatever your method of selecting institutions for comparison and benchmarking, you can both increase the validity and accuracy of those comparisons and extend the value of comparisons to department and college levels by constructing a peer institution from disaggregated components. This paper will demonstrate the methodology using the National…
Descriptors: Institutional Research, Institutional Characteristics, Institutions, Research Methodology
McGuire, Katherine A. – Association for Institutional Research, 2017
Data quality has become a pressing issue for many campuses in recent years, as colleges struggle to extract timely, accurate, and consistent information from ever-proliferating institutional data sources in order to meet strategic decision-making and accountability demands. In this mixed methods study, a survey and semi-structured interviews were…
Descriptors: Institutional Research, Data, Quality Assurance, Data Collection
D'Allegro, Mary Lou – Association for Institutional Research, 2017
This study considered three selection indices to choose institutional peers: (a) proximity, (b) percentile, and (c) normative. Although conceptually similar, only the proximity selection index had been previously studied. The purpose of this paper is threefold. First, the procedures used to generate the peer sets for each selection index are…
Descriptors: Institutional Characteristics, Private Colleges, Selection, Selection Tools
Swing, Randy L.; Jones, Darlena; Ross, Leah Ewing – Association for Institutional Research, 2016
A national survey of a professional field is an appropriate and logical undertaking for a professional membership association such as the Association for Institutional Research (AIR). The National Survey of Institutional Research Offices is the most comprehensive survey of offices of institutional research ever undertaken. The goal was to collect…
Descriptors: Institutional Research, National Surveys, Institutional Characteristics, Colleges
Swing, Randy L. – Association for Institutional Research, 2016
The need for data-informed decisions is not limited to national policy, state systems, or senior leadership of postsecondary institutions. Decisions that impact the achievement of higher education missions are also made by students, faculty, frontline staff, and program administrators--all of who deserve data and information to support their…
Descriptors: Institutional Research, Information Utilization, Higher Education, Data Collection
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