The Institutional Research Handbook2nd Edition

INSTITUTIONAL RESEARCH HANDBOOK, Edition 2.0

Published by Southeastern University, Office of Institutional Effectiveness1000 Longfellow Blvd., Lakeland, FL, 33801.

Copyright © 2016, 2020 by Southeastern University, Inc. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior permission of the copyright owner.

Authors of the 2nd edition: Justin E. Rose, Director of Institutional Effectiveness L. Jordan Kleinhenn, Data Tech & Reporting SpecialistAuthor of previous editions: Keith Kelso, Assistant Director of Research & Reporting

Table of Contents

Introduction .................................................................................................................................. 1

History of Institutional Research at Southeastern ...................................................................... 1

Institutional Research Today ...................................................................................................... 2

Institutional Research Operations .............................................................................................. 2

Institutional Research as a Profession ....................................................................................... 5

Duties and Functions of Institutional Research .......................................................................... 5

AIR Statement of Aspirational Practice for Institutional Research ............................................ 7

Ethical Considerations in Institutional Research ..................................................................... 12

Institutional Researchers as Campus and Public Educators ..................................................... 14

Research ...................................................................................................................................... 17

SEU’s Data Ecosystem: Jenzabar ERP & Business Intelligence Database .............................. 21

Fact Book ................................................................................................................................. 29

Data Dictionary ........................................................................................................................ 31

Business Intelligence .................................................................................................................. 39

Reporting .................................................................................................................................... 43

Common Data Set .................................................................................................................... 43

List of Reports - Alphabetical .................................................................................................. 46

List of Reports - By Due Date .................................................................................................. 47

Summary of Report Process ..................................................................................................... 48

Appendix A: Census Data ........................................................................................................... 65

Appendix B: Essential Institutional Research Software ............................................................. 69

Appendix C: Suggested Resources ............................................................................................. 75

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Introduction

The field of Institutional Research, a term specific to postsecondary education, has many permutations and functions within the higher education landscape, a reality that continues to expand both in scope and scale in an increasingly data-driven society. The demand for timely, relevant, actionable data and research-based solutions within colleges and universities in general, and among campus decision-makers in particular, is strong enough to require a robust, well-trained, and technologically advanced organizational unit dedicated to the research, reporting, and analytics functions of Institutional Research. At Southeastern University, this function is embodied in Institutional Research & Effectiveness, which comprises both the Office of Institutional Effectiveness (IE) and the Office of Research & Strategic Projects (RSP). IE is responsible for the primary research and reporting requirements of the IR function at Southeastern, as well as institutional assessment and strategic planning, learning analytics, and both regional and disciplinary accreditation support. RSP is responsible for high-level analytics, business intelligence solutions, managing Southeastern’s data ecosystem, and specific research and reporting requirements. This volume will largely explore the operations and resources relevant to IE’s role in institutional research, but the work of RSP will also be cited when relevant.

History of Institutional Research at SoutheasternThe Office of Institutional Effectiveness at Southeastern University began in 1990 as the university prepared for its first accreditation reaffirmation with the Southern Association of Colleges and Schools Commission on Colleges (SACSCOC). Initial accreditation had been awarded in 1986, and the concept of institutional effectiveness was a new emphasis of the organization. The first director was Frank Tallman (1990-1994), but the position was half-time with no additional support staff. During the tenure of Glenn Pearl (1994-2006) the position was made full time and the department name changed to Institutional Research and Planning.

Dr. Andrew Permenter took over the role in 2006, and the office added an administrative assistant. Over the next few years the office added three more positions as Dr. Permenter’s role was elevated to the level of a dean, overseeing the Office of the Registrar and other academic support areas, as well as institutional effectiveness. Following the results of the 2011 accreditation, Dr. Permenter was promoted to associate vice president, and Andrew Miller became the Director of Institutional Effectiveness.

In 2014, Andrew Miller chose to relinquish control of institutional effectiveness, having been put in charge of what has become the College of Unrestricted Education. Cody Lloyd became the head of the department and the following year was elevated to the Executive Director for Information Management, overseeing the Office of the Registrar and Information Technology in addition to the Office of Institutional Effectiveness.

In 2016, Justin Rose took over as the Director of Institutional Effectiveness and Dr. Ken Reaves became the Director of the newly formed Office of Research & Strategic Projects. Since then,

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the position of Data Tech & Reporting Specialist has been added to the office reporting structure, currently occupied by Jordan Kleinhenn. Dr. Cody Loyd has been promoted to CIO. Dr. Permenter is Vice President for Institutional Research and Effectiveness.

Institutional Research TodayWe broadly categorize the functions of IR at SEU in two categories: Research and Reporting.

Research is the function of gathering, organizing, analyzing, and the internal dissemination of institutional data of any kind. Recurring and ad hoc research requirements are crucial to the operations and strategic planning and assessment of strategic institutional priorities. Institutional Research & Effectiveness has made great strides in recent years in the democratization and accessibility of key data related to academics, enrollment, financial aid, student success, and learning analytics. Professional staff within the IR function at SEU rightly construe themselves as campus educators, who have a responsibility to share, teach, and develop competencies related to institutional knowledge with other stakeholders.

Reporting is the external dissemination of data through numerous governmental and private surveys, some of which are required and some of which are voluntary. Compliance with reporting requirements allows the institution to maintain its good standing with a number of organizations, some of which are indispensable to institutional aid, reputation, and prestige. Reporting is a baseline critical operation among all other IR operations at SEU. It may not always be the most important component of what the unit does, but it will likely always be the most urgent and the most non-negotiable in terms of delivery.

Institutional Research OperationsWithin the Office of Institutional Effectiveness, the operations of IR are organized around an annual external reporting project calendar, an internal reporting calendar and ad hoc data request ticketing system, and regularly iterated and ad hoc research projects. Research projects are generally conceptualized, designed, and implemented following the collection of requirements from institutional committee assignments, accreditation initiatives, departmental activities, assessment and planning cycles, internal research initiatives, and at the direction of university leadership. The Director of Institutional Effectiveness approves the regular research and reporting calendar concurrent with the approval of the assessment and planning calendar. Special research projects and time intensive data requests are also subject to approval from the director. The Data Tech & Reporting Specialist is responsible for the daily assignment, completion, and follow up of ad hoc and recurring data and reporting requests. The Director of Institutional Effectiveness works in conjunction with the Data Tech & Reporting Specialist, the Director of Research & Strategic Projects, the CIO, the VPIRE, and other stakeholders as applicable in the creation of business intelligence dashboards and reports relevant to the functions of IR.

Project management is generally facilitated via the Asana project management platform, which allows for broad, collaborative execution of major projects, as well as single tasks, within a dynamic Google-connected space. Other project management solutions may prove more

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useful in the future, but as a general rule, the best solutions are the ones that the majority of the organization has bought into and knows how to use.

Data requests are generally processed through the Teamwork ticketing system. As new tickets come into the system, they are assigned to the appropriate staffer. Initial acknowledgement is expected within 24 hours of reception. Turnaround time is generally expected to be less than a week, depending on the scope, scale, and nature of the request. Collaboration and questions for other staffers should almost always transpire via the notes feature, rather than direct responses which are also sent to the client. A ticket monitoring dashboard allows the Director and other members of the office to monitor response and turnaround times, and to remove barriers to customer satisfaction.

The official medium for communication at the university is SEU Gmail, but Google Hangout meets, Zoom calls, phone calls, Google Chats, text messages, and other internal collaborative communication platforms are frequent and encouraged modes of communication. Supervisors are responsible for clearly identifying how communication should be facilitated for each area of work, and direct reports are responsible for adhering to these expectations. The teams engaged in Institutional Research at SEU have long been the beneficiaries of strong, collaborative, and collegial communication, thanks in large part to a spirit of unity and cohesion, as well as a shared commitment to mutual respect and success, that pervades this sector of the university.

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The work of institutional research must be understood and appreciated for the profoundly important contribution it makes to the life of the university in particular, and to the sustenance of higher education in general. In fact, it resides at such a high caliber of responsibility and guardianship for the postsecondary landscape that a veritable canon of literature has emerged around it, seeking to better define and redefine the evolving nature of the roles, issues, and questions at play within institutional research. While this handbook cannot exhaustively examine that body of work, it will provide a brief overview of some relevant considerations for those seeking to develop a career in IR. Additionally, Appendix C offers a modest list of suggested resources that take up these matters in greater detail.

Duties and Functions of Institutional ResearchThe following is adapted from the list of Duties and Functions of Institutional Research, published by the Association for Institutional Research.

The professionalization of the field of institutional research (IR) has expanded rapidly in the past 51 years of AIR’s existence as the professional association for institutional researchers. In today’s economy, where data and information are valued and those who assist organizations in utilizing these data and information to make informed decisions are seen as assets, the field of IR looks to continue its importance in higher education institutions, systems, and organizations. The following list of Duties & Functions of Institutional Research was developed by AIR, with input from members, to continue the process of defining the function of IR to explain and assess our work. While not all offices of IR, or all institutional researchers, will necessarily be tasked with all the duties and functions listed, and some may be tasked with duties and functions not listed, an effective institutional research function at an institution, system, or organization will include all of these aspects.

Duties and Functions:

Identify information needs. This functional area reflects the iterative process of identifying relevant stakeholders and their decision support needs. It includes anticipating questions through review of data, information, and research and policy studies, including those related to institutional, state, national, and international conversations around higher education. It also includes assisting stakeholders in developing and refining research questions.

Institutional Research as a Profession

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Collect, analyze, interpret, and report data and information. This functional area reflects the technical tasks employed by institutional research to provide data, information, and analysis for decision support. It involves an understanding of the data available to answer pressing questions about student access and success and institutional operations and the process by which previously unavailable data are collected. The process of collecting and reporting required and requested data is encompassed in this area. This function also incorporates applied research methods to analyze data to provide information for decision making, including appropriate interpretation of analysis results.

Plan and evaluate. Planning may include operational, budgetary, and strategic planning in which institutional research collaborates with other units at the institution, state, or related organizations. It may also include program review, particularly for accreditation purposes. Formative and summative evaluation processes conducted at an institution use IR data and analysis for planning and decision making purposes.

Serve as stewards of data and information. This functional area highlights institutional research’s role in ensuring an institution-wide data strategy. Compliance issues such as privacy and security and ethical issues such as determining what data and information should be used for various purposes, and whether interpretations are correct and appropriately used, are also critical to this area. This area also includes the contribution of IR to data quality assurance activities. IR’s role in ensuring data are appropriately accessible and usable to those who need them to make decisions is inherent in this function as well.

Educate information producers, users, and consumers. This functional area encompasses the training and coaching related to the use of data, analysis, and information to inform decision making. Education can be focused on ensuring the ability to collect, access, analyze, and interpret information independently and in collaboration with other stakeholders. The function also includes a collaborative role in convening discussions related to information needs and connecting internal and external producers and users of data with one another for purposes of informing decision making. Scholarship to inform and improve data, information, and analysis for decision support is also included in this function.

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AIR Statement of Aspirational Practice for Institutional ResearchThe following language is excerpted from the Association for Institutional Research’s (AIR) Statement of Aspirational Practice for Institutional Research. It provides a glimpse into the future of the field and aligns directly with SEU’s ambitions for conducting meaningful, responsible, innovative institutional research that advances the discipline into the 21st century.

The demand for data to inform decisions in postsecondary education is greater than ever before. Colleges and universities have significantly increased capacity to collect and store data about student and institutional performance, yet few institutions have adequate capacity for converting data into information needed by decision makers. It is even more challenging for them to produce decision support on the fast timelines that decision makers often face. Is there a better way to organize institutional research? Are old models for institutional research positioned to meet the data-as-decision support demands of higher education today? The Statement of Aspirational Practice for Institutional Research grew out of IR practices already occurring at many institutions. First, there is increasing demand for decision support from faculty, students, program managers, and academic unit leaders—decision makers who have not been the primary customers of institutional research in the past. Also, recent advances in data distribution and analytic tools make it possible for a wide range of staff to engage in converting data into information. Simply stated, eager consumers and a ready talent base could expand IR capacity and the use of data in decision making. Increasing the availability and use of data-informed decision making models is a core goal of the Association for Institutional Research (AIR). Yet meeting the growing demand for decision support is hampered by the cost of resources needed to build such capacity. These realities served as the backdrop for conversations between AIR and the Bill & Melinda Gates Foundation, which led to the development of an aspirational statement about IR as decision support that focuses on student success. The Statement of Aspirational Practice for Institutional Research is not offered as a prescription, but rather as a discussion starter. Readers will find suggestions for creating institutional conversations at the end of this document. It is my hope that such discussion will be the beginning of new models for IR, broader use of data in decision making, and greater levels of student success.

Data are everywhere across institutions of higher education, and access to analytical tools and reporting software means that a wide array of higher education employees can be actively involved in converting data into decision-support information. As such, models of decision making are

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changing, which opens new opportunities for wise use of data resources. This Statement of Aspirational Practice for Institutional Research presents a hybrid approach in which offices of institutional research work in conjunction with other departments and units to produce an organization-wide institutional research function. This approach includes continuation of most current functions, reallocation of some resources, and the addition of new, focused approaches. Key to this vision are a broadened definition of “decision makers” supported by institutional research, an intentional structure and leadership for data capacities, and adoption of a “student-focused” paradigm for decision support. This approach builds on the 50-year collaborative nature of the institutional research field. It is a hybrid model of past traditions and new structures, founded on human resource capacities—within a dedicated office of institutional research and embedded in decision points across the institution—with focus on the collection, interpretation, and use of data to achieve an institution’s mission. The goal is for smart people to make smart decisions to improve student success.

Senior leaders have been, and will continue to be, priority consumers of data and information provided by the institutional research function. They are not, however, the only decision makers who impact an institution’s achievement of its mission. Other decision makers include students shaping their own experiences, faculty shaping their teaching and interactions with students, and staff shaping program designs and direct interactions with students. Top-down policies and structures alone do not ensure informed choices and commitments to successful pathways. Broadly engaging all stakeholders in data-informed decisions (tactical, operational, and strategic) is essential for institutional excellence. This hybrid model positions students, faculty, staff, and other decision makers as key consumers and clients of institutional research, and is foundational to a change agency vision of institutional research as a driver for institutional improvement.

Colleges and universities have responsibilities for assisting students in decisions about their educational pathways. These decisions include student choice to comply with institutional requirements and to select non-required pathway options. Students deserve access to usable information that is focused on their decisions, is of high quality, and is not so highly aggregated or obfuscated by higher education jargon to fail to be useful.

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Check-circle Activating Data-Informed Student Decision Making • Institutional research topics inform decisions students make (e.g.,

how to best use time, academic and extracurricular choices, and life decisions that impact collegiate success).

• Institutional research is produced and disseminated with students as the target audience and/or unit of analysis.

• The timing for release and promotion of institutional research products is intentionally aligned with the cycles of student decisions, which often differ from fiscal, multi-year strategic planning, and academic term calendars.

Faculty as Decision Makers Faculty members are the frontline in achieving an institution’s mission and they are the chief architects of the academic environment. Focused and intentional data management and institutional research provide timely and useful faculty decision support for curricula, teaching, and governance.

Check-circle Activating Data-Informed Faculty Decision Making • Faculty and faculty committees have access to data and information

to support decisions about policies and structures for which they have oversight.

• Individual faculty have access to data and information to support them in designing their work, with special emphasis on student learning outcomes.

Staff as Decision Makers Staff members have frontline responsibilities for fostering student development of academic and civic behaviors, establishing challenge and support structures for many student learning outcomes, and minding the safety and well-being of individuals in collegiate spaces. Disaggregation of data by unique subpopulations and robust data on out-of-class and life experiences informs planning, design, and implementation of student success initiatives and structures.

Check-circle Activating Data-Informed Staff Decision Making • Staff members and staff committees have access to data and

information to support decisions about policies and structures for which they have management oversight.

• Individual staff members have access to data and information to support them in designing their work, with special emphasis on disaggregation of data to address the unique needs of specific students.

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The complexity of modern higher education demands investment in leadership and staffing for strategic, tactical, and operational decisions. Use of data for institutional research cannot be restricted to one office. With greater access to data sources and data tools, and increased department-specific data, institutional research products are widely dispersed across higher education institutions already, even when a strong central office of institutional research exists. An increasing number of staff and mid-level administrators are expected to use data to inform decisions, and decision makers at all levels are establishing their own data collection processes and analytics. Where institutional research once took pride in being the “one source of the truth,” the reality is that the new role for institutional research is in coaching a wide array of data consumers, managing institution-wide data and analytical requirements, and orchestrating “the economics of institutional research” in balancing information supply and demand.

The greatest potential for building effective institutional research is leveraging talent across the institution. The function of institutional research connotes the institution-wide use of data and analytics, and not just the products of an office of institutional research. Building the function requires coaching and professional development of employees across the institution in a purposeful and intentional process that increases capacity for data-informed decisions to permeate the institution. Coaching must differentiate an “auto-pilot” “data driven” strategy from the intended “data-informed” strategy, which includes professional judgment, innovation, experience, theory, and wisdom in decision making. The goal is for data literacy to be as ubiquitous as expectations for writing, speaking, and computer skills. These are reflected in position descriptions and performance reviews.

Check-circle Activating a Networked Institutional Research Function • Data and analytic tools are available institution-wide to activate a

broad network of institutional research aligned with strategic, tactical, and operational decisions.

• Human Resource practices identify the data literacy skills required of employees who produce and/or use data and information in their work assignments.

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• Institutions provide training and continuing professional development of data-related skills for all employees. Institutions establish and support networks of data users and consumers who share good practices and collectively advocate for the data, tools, and dissemination methods required to meet the institution’s needs.

A Chief Institutional Research Officer (CIRO), at a commensurate level of others who manage valuable resources (e.g., Chief Financial Officer and Chief Information Officer), is prudent to provide leadership to build and maintain the institutional research function. This role is broader than a traditional director of institutional research in that the CIRO is responsible for the tactical and strategic direction of the institutional research function. The CIRO leads by supporting and coordinating all institutional research, institutional effectiveness, assessment, accreditation, mandatory reporting, business analytics, and other data-focused decision-support activities. The position assures an effective institutional research function, internally-driven and resourced through purchased and shared services. It requires a significant focus on building relationships with individuals throughout the institution, understanding data and information structures and capacities, and connecting disparate pieces of information.

Check-circle Activating Leadership for the Institutional Research Function

• The Chief Institutional Research Officer (CIRO) institutes strategic plans for growing and maintaining an institution’s analytic and data capacities.

• The CIRO communicates the value of data-derived information in a holistic model of decision making that includes professional judgment, institutional mission, and environmental factors.

• The CIRO is a leader of the institution’s data governance strategy. • The CIRO ensures that decision-makers have timely and useful

information.

In this aspirational vision of institutional research, data and analytics are transparent and are intentionally focused on improving the student experience. Many of the past successes in institutional research have focused on students—enrollment management, retention, engagement, and graduation rates. Yet that focus can be further enhanced by intentionally grounding institutional research initiatives and reports in a student-focused

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perspective. A key question to be addressed in all institutional research is “how does this exploration serve students?” An essential component of communicating these results is making clear their underlying student-centered purposes.

Check-circle Activating a Student-Focused Paradigm • The selection and design of institutional research is predicated on a

commitment to the success of all students. • Using expertise in communications, institutional reports demonstrate

effective strategies for “telling the data story” and intentionally connecting all exploration to the student experience, including learning outcomes.

• Institutional research avoids “silo” approaches that fail to recognize that students experience an institution holistically and not as individual administrative functions and units.

This Statement of Aspirational Practice for Institutional Research is not a prediction of a distant future; rather, it reflects changes that are already observable. It is not a critique of institutional research functions that have served higher education well over the past five decades. These ideas address and support the rapidly growing culture of data-informed decision making and provide a starting point for a new vision for institutional research in higher education. The ultimate goal is institutional engagement, not a prescription for a specific path of change. The future role of institutional research is creating demand for decision-support and balancing it with the supply of information to meet that demand. While celebrating the success of institutional research in shaping colleges, universities, and state and national educational policies, this aspirational statement is intended to promote active re-envisioning of the institutional research function needed for the short- and long-term future of postsecondary education.

Ethical Considerations in Institutional ResearchA final dimension of the profession that any aspiring institutional researcher should take seriously, at Southeastern University or otherwise, is ethics -- both in their disciplinary and generic senses. SEU is a Christ-centered, student-focused institution of higher education that requires adherence to the cultural values of its playbook. Christian ethical principles should guide the conduct, relationships, and work of a person of faith in any vocation. However, there are also nuanced and evolving field-specific ethical matters that require regular, discursive

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engagement and serious attention from the institutional researcher in order to advance and ensure equity, fairness, and other ethical priorities in a rapidly changing higher education landscape. To that end, the following Statement of Ethical Principles from the Association for Institutional Research is printed here to provide a broad overview of the shared commitments among the IR professional community.

The Association for Institutional Research affirms the following overarching principles regarding the use of data to facilitate insights and improve decision making. These principles guide us as we promote the use of data, analytics, information, and evidence to improve higher education.

We act with integrity:

We recognize the consequences of our work. The analytic algorithms and applications we build and/or implement, as well as the policy decisions incorporating information we analyze and disseminate, impact people and situations.

We acknowledge that the individuals whose information we use have rights, derived from both legal and ethical principles that can cross national borders. We make intentional efforts to protect their information from misuse or use that could cause them harm.

We protect privacy and maintain confidentiality when collecting, compiling, analyzing, and disseminating information.

We act as responsible data stewards. We secure the data and information over which we have control, following generally accepted guidelines and professional standards for physical and electronic security and data sharing.

We provide accurate and contextualized information. We do not knowingly or intentionally mislead the consumers of our information.

We deliver information and analyses appropriate to the questions being asked, to the quality of the data available, and to the context in which the questions are asked.

We seek to be fair and transparent, minimizing our own personal biases in our research assumptions, methodologies, and conclusions.

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We avoid conflicts of interest, and disclose them when unavoidable, particularly with third parties and vendors. We act in the best interests of our institutions, students, and stakeholders.

We strive to make our work accessible to those who need data, information, and analysis to generate insight and make decisions.

We share knowledge of the Institutional Research field and its application so we may facilitate insights and promote common understanding to our institutions and stakeholders.

We value lifelong learning and the enhancement of our field. We draw on and contribute to relevant and emerging scholarship and educate ourselves on developing trends. We utilize those methods and techniques for which we have, or can obtain, appropriate knowledge and capabilities.

We recognize that technological advancements have and will continue to impact our work. We remain committed to serving as educators and role models on the ethical use of data to benefit students and institutions and to improve higher education.

Approved by the AIR Board of Directors September 13, 2019

Institutional Researchers as Campus and Public EducatorsSociety has been moving toward greater reliance on technology, immediate data, and predictive analytics in nearly every aspect of life. This has become especially noticeable this year as medical experts, government leaders, and citizens monitor COVID-19. In higher education, we depend on accurate, timely, and relevant data for enrollment management in relation to recruiting new students and ensuring successful persistence of current students. In fact, student success writ large depends on data-informed decision making across the campus. Faculty and administrators use data to improve the quality of programs and seek the most effective use of resources.

To these ends, IR professionals not only provide the right data to campus clients and deliver research-based solutions to campus decision makers, but also function as educators to those we serve. This role is more or less formal depending on institutional context, but it is a responsibility held by everyone in the field. There are several ways that IR professionals can educate campus colleagues. First, it is helpful to inform campus constituents about what IR does. Getting beyond the intimidating myths fostered by compliance driven cultures or the hazy fog of vague assumptions about IR as a mere technocratic function of bureaucratic administration is an important requisite to removing barriers to understanding. For example, while faculty and

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staff may have a general idea about IR, it is important that they understand some of the critical operations of institutional research at the college or university, like the annual cycle of reporting. Thus, one option is to post an annual reporting calendar online or send the calendar to a wide range of colleagues across campus.

Working with IT or the campus webmaster to integrate the reporting calendar onto an easily accessible constituent-facing page can produce significant returns in overall campus knowledge of IR operations.

A second example of educating the campus is to develop a collection of various types of information about IR and make this available to campus clients. One such item could be a glossary. To illustrate, many have heard the term “FTE” mentioned, but how many are aware that FTE can have different meanings? A glossary that identifies institutional, state, and federal terms and definitions would be very valuable to the campus family. Another useful document that the IR shop can produce and make available to the larger campus community is an institutional research handbook. Such a handbook might include information such as a philosophy of IR (looking to AIR’s Statement of Aspirational Practice for IR is a good way to approach this), a history of IR at one’s institution, research and reporting timelines, relevant resources, and other helpful information. A handbook is a more time- and labor-intensive product than a glossary, but the return on investment in relation to stakeholder knowledge of IR functions and processes is significant.

Third, IR can teach campus peers by spending time with them. Whether this involves occasional workshops, panels, or informal lunch sessions, real “face time” can be especially helpful. IR staff can provide orientation talks about what they do and invite campus colleagues to ask questions. IR can voluntarily attend meetings even if not a standing member of a committee or task force so that if any questions come up, the IR representative can either clarify information or offer to collect the data. IR’s presence in various work groups can be quite helpful. If the IR unit’s institution is receptive to the idea and adequate resources are available, a professional development event or course led by IR is also an exciting way to directly provide education on the work of IR, and it allows for recognition and celebration of those who participate through innovative credentials like digital badges or competency certificates.

Similarly, IR professionals can educate the general public. One of the most common ways is by providing open access to selected documents on the IR website. To be sure, the fact book is likely the most popular such document. Fact books may be available as a single downloadable PDF/print document or in sections or chapters. With 24/7 online access from multiple devices today, people generally prefer to use an electronic fact book. Electronic/digital fact books are, by nature, interactive and designed for viewing on screens. While some digital fact books are created by hand from coders, many IR offices take advantage of visualization apps such as Tableau or Power BI.

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Social media also offers an often untapped avenue for IR to educate the public on matters relevant to institutional research, both in terms of data about the particular institution and higher education in general. Twitter, Instagram, Facebook, and other emerging social media applications do not have to be the exclusive domain of enrollment marketing and admissions. One simple approach to this is to register a Twitter account for one’s IR office (with appropriate approval, of course) and develop a calendar of scheduled tweets with relevant statistics from collected data, especially institutional surveys that offer interesting data and promote the strengths of the school.Another way that IR offices educate the general public is by posting links to original surveys of reported data to federal and state agencies. IPEDS and state accountability reports are public information, so it makes sense for IR offices to either make these documents available on their own websites or provide links to where public visitors can locate them. One advantage of doing this is that the IR office can then provide relevant commentary on how their respective institution fits into the context of the linked report(s), and it allows for pointing directly to reports that highlight institutional distinctions.

Last, but not least, IR professionals can educate the public through an open invitation to request data. An online request form is commonly used to collect data requests. There may be restrictions on external freedom of information requests, but providing summary level, aggregate data descriptive of the institution is useful to informing the general public about what makes the institution unique.

IR staff serve a valuable support role to the leadership of their respective institutions. Even though IR procedures might not be the most glamorous or exciting activities, IR fulfills a strategic function that can impact the direction of the institution for years to come. It is important that IR professionals offer campus stakeholders (whose familiarity with institutional research may fall on a spectrum of very little to a great deal of knowledge) the opportunity to learn more and engage with all that IR does to advance institutional priorities and promote student success. It is also critical that IR professionals take more time to consider their responsibilities as public educators at a time when the future of higher education is so tenuous.

Adapted from an article co-authored by Justin E. Rose and Eric G Lovik, published by the Association for Institutional Research

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Research

Research as a function of Institutional Effectiveness comprises all data capture, collection, modeling, analysis, visualization, and reporting conducted for internal university stakeholders. This includes major institutional projects like the annual Fact Book, regular internal reports like the Registration and AD2RE reports, maintained business intelligence dashboards like the Enrollment ATM and Registration dashboards, research support for regular departmental reporting requirements like those requested by the Business Office or Unrestricted Education Compliance, and any ad hoc reports requested by the Leadership Team, academic colleges or departments, or other departments on campus. We process hundreds of ad hoc data requests every year.

Research CategoriesOur office manages and analyzes a broad spectrum of types of data, the majority of which falls into one of eight categories.

Enrollment DataEnrollment data is inclusive of all information directly or indirectly related to the dynamics of student enrollment in courses, programs, and other curricular expressions of the University. In terms of Institutional Research’s engagement with this paradigm, work generally resides in two sub-categories: student enrollment data and course enrollment data. Records for student enrollment generally result in one record per student for a given year and term. Official Census data falls into this category; it is populated every semester by the Director of Research & Strategic Projects. The data is then cleaned and uploaded to the server. The data generally includes one row per student enrolled for that semester. The official census data can be found in the DM_Census table in SQL on the seu-bi server in the SEUDWStage database. Census data can be queried to complete a significant variety of data requests, research projects, or form the essential model of an enrollment dashboard. Additionally, official census data is used to complete mandatory external reporting projects.

Student enrollment data can encompass a large variety of information about each student: demographics; contact information; student type or delivery information; academic information such as major and minor program enrollment, hours enrolled, and GPA; and anything else that could be considered a part of an individual student’s record. This data can be more easily accessed via the DM_Census table in SQL on the seu-bi server. Other tables, containing more details about a students record for a given year and term, can be joined to DM_Census such as DM_CensusDemographics and DM_CensusStudentLife. These tables can be joined together using the DMCID field for guaranteed accuracy, as that field is the prime key for all official census tables.

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Course enrollment data, on the other hand, details Student-course-based enrollment data can be located using the student_crs_hist_v view in SQL on the Jenzabar server. Examples of common ad hoc requests in this category include number of courses enrolled by a student, a list of course names taken by a student, or a list of all students taking a specific course during a specified year and term.

Specific details about our census data is in Appendix A.

Course DataCourse data is based on the courses that take place during a given year and term. The data should contain one row for each course offered in a given year and term, and may include the course’s enrollment, credit hours, faculty information, schedule information, etc. This data can be found in the section_master_v table on the Jenzabar server. Examples of common ad hoc requests pertaining to this table and data set include courses taught by a specific instructor, course enrollment, and course begin and end dates.

Completion DataThe production, maintenance, and reporting of data related to the completion of degree programs at Southeastern University is integral to the successful operation of Institutional Research for a number of reasons. Numerous stakeholder groups rely on accurate, timely reporting of graduation data, including both external and internal groups. Among external entities, IPEDS is perhaps the most demanding and rigorous of accountability frameworks and repositories to which the IR office has regular and significant obligations. Other organizations like U.S. News & World Report, SACSCOC, Peterson’s, U-CAN, the College Board, ICUF, state authorization offices, and a myriad of others routinely request or require reporting on figures related to successful degree completion.

Internal offices that make use of completion data produced by Institutional Research include academic departments, University Communications, the Office of the Registrar, the Office of Academic Advising, Enrollment Marketing, Alumni Relations, University Advancement, and other SEU community stakeholders. This data is generally available via the annually published University Fact Book, as well ad hoc data requests through the IR ticketing system.

The primary dataset within SEU’s data warehouse that is most frequently queried for sourcing information related to completion of degree programs at SEU is degree_history, which is a table of the TMSEPrd database in the Jenzabar server. Degree history returns a record for each student enrollment in a credential offered by SEU, regardless of whether the student has attained the degree. It includes fields that indicate whether the degree is current, the degree-seeking status of the student, the division and degree code, date degree was conferred, major/minor/concentration/certification codes, entry and withdrawal dates, advising tree year codes, and relevant information about the diploma. For details on the degree_history table, see the description on page 22.

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Degree History is most often used by Institutional Research staff for internal purposes when a university office requires a list of graduates from a particular degree program or suite of programs for advancement purposes, public relations and university communications, to inform academic program review and planning, and student success efforts. Completion data is also crucial to conducting meaningful outcomes assessment for both academic and administrative units. Two of the three IPEDS collections (Fall and Winter) necessitate reporting on completion/graduation data each year. These data are produced through a series of SQL queries maintained by the Office of Research & Strategic Projects, though Degree History is still the driving table for the majority of these queries. Once executed, the data is generally compiled in an Excel workbook that then may be resourced for completing various reports.

Although Degree History is typically the driving table for queries related to degree completion, Southeastern University’s Institutional Research team also annually produces the Common Data Set (CDS), which functions as a comprehensive repository of data organized by a standard set of fields, shared by postsecondary institutions nationally. The CDS is then utilized as a source for completion of a number of major reporting requirements throughout the academic year. A major component of this dataset is completion data. Relevant fields include A5: Degrees Offered By Your Institution, B3: Persistence - Number of Degrees Awarded (During a Given Academic Year), and Graduation Rates.

Financial Aid DataThe Student Financial Services department and the Business Office conduct the majority of detailed, student-level reporting and operations related to or requiring the use of financial aid data. The primary source of this data is PowerFAIDS, a system with which Institutional Research has little interaction. At times, Student Financial Services and the Business Office will request needed auxiliary data in order to complete certain functions, and our IR team will provision that data through the ticketing system. Institutional Research also provides support and guidance on a number of projects related to financial aid data.

IR most frequently works with financial aid data to complete external-facing projects, especially with regard to Common Data Set and IPEDS. The Winter Collection of IPEDS includes the Student Financial Aid survey component, which calls for data entry related to the establishment of cohorts, loan information, income level, tuition figures, and military and veteran benefits. Common Data Set includes a Graduation Rates section that indicates the number of students eligible for or who have received Pell Grants and Subsidized Stafford Loans. CDS also includes a comprehensive financial aid data section, organized by need-based and not-need-based financial aid across a variety of factors.

On occasion, Institutional Research will provide assistance to Student Financial Services in a reporting and data analysis capacity, typically on matters related to student financial clearance as part of the institution’s efforts to ensure pathways to student success, as well as uninterrupted revenue streams. This reporting and analysis support usually takes the form of consultation on SQL scripting, business intelligence design, and automation. Historically, IR has developed and maintained reporting solutions related to financial clearance, but those processes have

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transitioned to a partnered solution between the Business Office, Student Financial Services, and the Salesforce administrator in IT.

Admission DataAdmission data consists of how a student has traveled through the admission funnel; this is tracked by Stages in Candidacy as well as “Sent to RE” dates. This data includes their intended, but not declared, major as well as year and term of enrollment, location, status, student type, and more. All Admission data is entered by Data Entry within the Admission department. Once a student is at the Deposited Complete stage, a student can be pushed through the AD2RE (Admission to Registrar) process. This process is run daily by the Assistant Registrar. Once a student has been pushed through the AD2RE process, they no longer belong to Admission, and are now the responsibility of the Registrar, as well as many other departments, to fully enroll the student into Southeastern University.

The majority of detailed data analysis is conducted by the Director of Research & Strategic Projects, usually through Power BI. Currently, the Enrollment ATM and Admission Funnel dashboards are used by the Admission department, IE, IR, Leadership, and other stakeholders to view detailed analysis pertaining to admission data. There are times when admission level data is requested from the Admission department to the Data Tech. This is often related to details about a student that is still within the admission funnel such as religion, high school location, etc.

External reporting related to Admission data is required by nearly all external annual reporting requirements such as CDS, IPEDS, ICUF, Peterson’s, U.S. News, and more. Admission data is also gathered for the Fact Book each year. The most commonly reported data points from admission data is number of applicants, enrollments/deposits, and demographics related to those populations.

Faculty DataFaculty data includes records for any personnel for a given year and term who are either active instructors or are currently employed in a non-instructional position but have faculty rank. There are a few types of personnel who fall into this category:

• Instructional Faculty: full- or part-time ranked personnel whose sole or primary responsibility is instruction. Sometimes adjuncts might be included in this term, although they do not have faculty rank.

• Non-Instructional Faculty: any personnel with faculty rank whose primary responsibility is other than instruction. This includes library faculty, Leadership Team, and other administrators with faculty rank These individuals are included in Faculty for the year and term whether or not they are teaching any courses.

• Adjunct faculty: any personnel with instructional assignments on a course-by-course contract, but who do not have faculty rank.

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Although they do not have rank, they may be listed with the rank of “Adjunct.”

Because of these subgroups, the exact definition of faculty can vary, depending on the specific needs of the person or group requesting the information. If someone simply asks for faculty and no further clarification can be obtained, it is best to assume that they mean only instructional faculty.

Faculty records include basic information, such as ID, name, contact information, and demographics; rank; college and department; degrees and whether they have a terminal degree; and details on whether they are staff or in one of the non-instructional groups, mentioned above. In Jenzabar EX, the FACULTY_MASTER table is used to produce faculty data. This can be connected to any table in Jenzabar that has a LEAD_INSTRUCTR_ID to further analyze faculty information.

Faculty data is used for the Fact Book, IPEDS, and other annual reporting. It is also used to produce detailed analysis relating to faculty numbers such as workloads, hours taught, etc.Faculty data are closely related to Staff data, which is discussed in the next section. See that section for some caveats regarding this relationship.

Faculty data is regularly sourced to complete the required 5-year statistical analysis of the Academic Program Review process (APR - see the Institutional Effectiveness Handbook, 3rd edition, and the Academic Program Review Handbook, 3rd edition, for detailed overviews of this analysis). Faculty data is also utilized for ROI modeling and other projects under the purview of Research & Strategic Projects.

Staff DataData regarding staff personnel at Southeastern are maintained primarily in the UltiPro datasets procured from Human Resources and managed by the Office of Research & Strategic Projects. This data includes components relevant to the analysis of human resources requirements, faculty and staff compensation, reporting assignments and roles, and seniority status. Staff data is typically used by Institutional Research & Effectiveness officers for reporting assignments, such as IPEDS and the annual Fact Book. Research & Strategic Projects uses the data for high-level reporting projects such as ROI modeling, financial projections, and the like. Institutional Effectiveness will occasionally make use of staff data for the purposes of program review or ad-hoc assessment. Some staff data resides in Jenzabar EX, but the most reliable, consistent data related to this data component should be procured from Research & Strategic Projects.

SEU’s Data Ecosystem: Jenzabar ERP & Business Intelligence DatabasesSoutheastern University’s data ecosystem has evolved from a simple relational database to a complex suite of servers, data warehousing, and business intelligence solutions. This suite includes the SEU ERP, Jenzabar EX, as well as the seu-bi server, which houses business intelligence databases like SEUDWStage and the LMS analytics platform D2L-DataHub.

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These databases and their primary use cases are described in detail below.

Jenzabar EX is our main data system for students, courses, enrollment, admission, completions, and advancement. We do not, at this time, work with advancement data, but for the other areas Jenzabar is the primary repository for live and, in some cases, historical data.

In many cases, views have been created that pull data from one or more tables and often reorganize it in a more useful way. For the query writer, views act just like tables. Where there is a useful view, it will be listed.

Here are some of the frequently used tables, views, and table sets:

Student Term SummaryThe Student Term Summary table (student_term_sum) is one of the primary tables used for student-based enrollment data. It includes a record for each student in each year and term. The one caveat is that when a student is enrolled for a semester but drops their enrollment, they are still listed in the table, but with zero hours enrolled. Thus, when this table is used alone, the most accurate data is obtained by including the argument “hrs_enrolled <> 0.”

However, this query would not capture everybody enrolled, since some master’s and/or Academy students are enrolled in zero-hour courses to complete their theses or coursework. Therefore, the most accurate way to ensure that all current students are included in a query, the Student Course History table (see below) should be used.

A variation of the Student Term Summary table is the Student Term Division Summary table (stud_term_sum_div). This table is similar to Student Term Summary, but has a row for each division that a student enrolls in for the year and term. This can create multiple rows if a student is simultaneously enrolled in undergraduate and graduate courses. However, it adds some useful fields, such as Term Hours Attempted, Term Hours Earned, and Term GPA. You can also pull a student’s Career Hours and GPA as of that year and term. To accurately capture student populations for most data requests, use the argument transaction_sts <> ‘D’ as this will exclude all courses dropped by a student in a given year and term.

Degree HistoryThe Degree History table (degree_history) is where a student’s degree information is listed. Anyone who has at some point been enrolled should have at least one record in this table, including non-degree students. Completions data will be based primarily on this table.

A student can have multiple rows in Degree History, however. Therefore, whenever using this table while pulling current enrollment info, it is important to use the cur_degree field. This field can only be marked “Y” in one record per student, therefore it will always eliminate duplicates. Occasionally, a student will have all Degree History records marked “N” in this field. (Usually this only happens with new students; once a student has a record marked as current, they will always

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have one or another marked current.) Thus anytime Degree History data is being added to a list of current students (such as from the Student Term Summary table), the number of students should be checked before Degree History is added to ensure that no students are being eliminated because no degree is marked current.

Other important fields that can be found in Degree History are Division, Date of Degree Conferral, majors and minors, and entry, re-entry, and exit dates. The field adv_tree_yr_cde is often called the Catalog Year and refers to the year of the catalog from which a student’s major requirements come. This is usually the year that the student declared their major.

An important related view is the Major/Minor Definition view (scf_Major_Minor_def_V), which contains definitions and important information for each major and minor code. Included are the major or minor’s description, CIP code, school and department code. This view could be added to a query multiple times, with each one connected to a different major or minor. Just make sure when joining Major 1 to use left join, otherwise anyone who has a NULL in that field will be excluded from the query.

Name and AddressName and Address (name_and_address) is a view combining Name Master (name_master), Biograph Master (biograph_master), and Address Master (address_master), with the latter being connected based on the address indicated in name_master.current_address.

This view provides essential identifying and demographic information for everyone in the Jenzabar database. It includes not only a student’s name and address, but email address (usually SEU email for current students), phone number, date of birth, Social Security Number, gender, religion, marital status, and more. It does contain a field for Ethnicity, but this is better found in the Ethnic/Race Report table (see below).

Ethnic/Race ReportAround 2007 or 2008, the Federal government released new guidelines on the reporting of race and ethnicity, creating new categories for race and an overarching ethnicity categorization of Hispanic or non-Hispanic. The new reporting guidelines were soon required for IPEDS and have been adopted by most other reporting organizations. For this purpose, Jenzabar created a new table, Ethnic/Race Report (ethnic_race_report).

However, since this time, Southeastern’s data ecosystem has created a view to better display ethnic/race data(ethnic_race_v). Using this, you will find the descriptions as well as the IPEDS values. The user should always defer to the IPEDS_Value_Desc field in this view as this is what is used in all demographic reports.

Student MasterThe Student Master table (student_master) is another valuable table when pulling student-level data. This table includes the student’s Location Code, Current Division, Tuition Code, Student

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Type Code (admitting_program), and Web Group (tel_web_grp_cde).

The Tuition Code indicates what tuition rate students are paying, and it is our main indicator of a student’s delivery (Online, Traditional, Extended Ed., etc.).

Student Division MasterThe Student Division Master table (student_div_mast) provides several important pieces of student-level data. This table can have one row per student, per division. Since it can have multiple rows per student, Division should usually be defined or matched with Degree History or Student Term Division Summary. It includes fields such as Hours Attempted, Hours Earned, and GPA, all broken down by Transfer, Local, and Career. It also lists up to three advisors for the student, by ID number.

Like the Student Master table, this table has a Class Code, but it is equally unreliable. However, from this table you can use the Career Hours Earned to calculate the student’s class if the class code is not already available in DM_Census. Student Division Master should also be used when data requests must include advisor information.

Section MasterSection Master (section_master or section_master_v) contains all of the basic information about every course iteration that has been or is being offered at SEU. Any list of courses would come from this table. Some important fields are the Course Code (which, in the view version, is also split up into individual components), Division Code, Institutional Division Code (which serves as the department/college code), Course Title, Section Status, Capacity, Enrollment, First Begin and Last End Dates, and Credit Hours. The Lead Instructor ID field can be used to add in faculty names by linking to Name and Address, or to filter to a list of classes taught by a specific faculty member.

Section SchedulesClosely related to Section Master is Section Schedules (section_schedules or section_schedules_v), which includes the schedule information for a course. It includes the Building and Room codes, individual fields for each day of the week, Begin and End Times, and Begin and End Dates. This table can be connected to Section Master by linking the Year, Term, and Course Codes.

Student Course HistoryAnother table that is related to Section Master is Student Course History (student_crs_hist or student_crs_hist_v). This table links course data with a particular student who took the course, and includes their grade. Another important field is Transaction Status, which tells if the course is Current (C), History (H), or Dropped (D). Any time you are pulling student course data, you should set the Transaction Status to <> ‘D’ to exclude drops, unless you are specifically looking for dropped course records.

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Note that this table also includes transfer courses and other outside credits like AP, IB, and CLEP, all of which are entered in special terms within a given year. If you want to pull all student course records for a year, you should still filter by term, but include multiple terms, so that you will exclude these external credits.

Room AssignThe Room Assign table (room_assign) lists dorm room assignments for students. Important fields are Session Code, Building Code, and Room Code. Generally, all traditional students should have a room assignment, but students living off campus will have a building code of ‘OFF.’ Non-traditional students may not have a record, so this table should generally be connected to other tables using a Left Join. This table is not often used, but could be helpful when fulfilling data requests for Housing or Ad Hoc requests for Leadership.

The Session Code combines the year and old term codes, with the old term code first. This table, then is slightly more difficult to link to other tables, where the year and term are separate fields, and are using more updated term codes. To join this table accurately, it is best to write the Session Code = into the join or the WHERE clause. (Ex. sess_cde = ‘FL2020’). This will give you a single room assignment matching a single Student Term Summary record.

CandidacyCandidacy is the main table for information on a student who is in the admission process. A candidacy record is delineated by the prospective student’s ID number as well as the year and term of their application. The table contains many common fields such as Division and Location Code. The Program Code (prog_cde) is the prospective student’s major of interest, although there are choices in this field that we do not offer as majors. The Department Code is used to label their delivery type (e.g. CA for Campus, ON for Online).

An especially important field is the Stage Code (stage), which indicates where in the admission process a prospective student is. This field can be connected to the Stage Configuration Table (stage_config), which provides a definition for the code, as well as the Stage Level, a broader category for the various stages.

Definition TablesIn many cases the tables in Jenzabar use codes to represent values. Some of these codes will become very familiar very quickly, such as Tuition Codes in the Student Master table or the Institutional Division Codes, which represent colleges or departments in several tables. For these codes, there is almost always a definition table somewhere in Jenzabar.

Table DetailThe Table Detail table (table_detail) is a mass definition table of sorts, with definitions for several different fields all combined in one table. The individual fields can be found by filtering the Column Name. For instance, if you limit Column Name to ‘state’ you will get just state and territory mailing codes and their definitions. Other useful definition sets in this table are Degrees and Exit Reasons.

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In a few cases, views have been created of more frequently used sets that are in Table Detail for the user’s convenience.

Location MasterAnother important definition table is Location Master (location_master). As our Extended Education programs continue to grow, we have more locations in use, and this table gives a definition for each location code, which can be linked to records from tables such as Student Master and Section Master.

SEU-BI (SEUDWStage) Tables and ViewsAlthough Jenzabar EX is a main database used for pulling data, there are a variety of tables and views that have been created on the SEU-BI, SEUDWStage server.

DM_CensusThis table is the go-to for any data related to enrollment within a certain term and year. It is a combination of many fields from Jenzabar, that will give you an entire look at a student’s enrollment during their time at SEU. Most commonly used fields are related to location, full time/part time, and term entry type (new, returning, FTIC, etc.) This table is very unique in that there are more DM_Census tables that can be connected to it for more data. A one-for-one join between all DM_Census tables can be made using the DMCID field.

As student’s change their majors over time, sometimes the major information in DM_Census will become outdated. DM_Census is created with a snapshot of student data on our census date. From there, students might change their major information, however. To ensure that the most up to date major is displayed for a student, I suggest joining the Degree History table from Jenzabar and using the Major1 from that table.

DM_CensusDemographicsThis table will show demographic, religion, and some financial aid characteristics (pell, first generation, etc.) about a student in a given year and term. As mentioned above, this table can be joined to the main DM_Census table via DMCID to see more details related to a student during a specific year and term.

DM_CensusStudentLifeThis table will give you student life/resident details about a student in a specific year and term. Again, this table can be joined to other DM_Census tables via the DMCID field. This table also gives you an athletic y/n field.

DM_CensusNewStudentThis is a very useful table in the DM_Census suite of tables. It will give you high school, test scores, and previous college information about a student for their incoming year and term only. This is why the table is called “new student.” This table can still be joined to any other DM_Census table by using DMCID. However, you will only see data for those that are “New” as defined in the main DM_Census table.

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BI_Registration_VThis view is updated each term to display students that have persisted from one semester to another, such as Spring 2019 to Fall 2020. There is only one semester-to-semester data set in the table at a time, which can be determined by looking at the “Persistence” data column. This view is extremely helpful and most often requested by faculty and Directors, especially when leading up to the Fall semester. It displays a single row for each student that was enrolled in the most recent term, and their status for the most upcoming term. One of the most helpful columns in this view is called “RegistrationStatus” that has four options for each student record: Graduating, Holds, Not Registered, Registered. This view is updated regularly by the Director of Research & Strategic Projects; upon updating, if a student has moved into a different status, their RegistrationStatus in the column will update as well. Other useful columns include extensive delivery and location columns, tuition code, year in school, degree and major information, as well as an athletic y/n column.

Currently, this view is used to run various Power BI reports such as the Enrollment ATM report maintained by the Director of Research & Strategic Projects, and the Registration: Contact List report maintained by the Director of Institutional Effectiveness.

SEU-BI (D2L-DataHub) Tables The following list of tables is not an exhaustive inventory of datasets available to users in the D2L-DataHub database, but it does comprise the essential tables used to deploy major existing business intelligence and learning analytics solutions. A full inventory and guide to Brightspace datasets and their relationships to each other can be found in the Data Hub - Administrator Guide, which can be accessed via the Office of Institutional Effectiveness Google Drive folder in the Learning Analytics Resources subfolder.

All GradesThe All Grades data set returns the grades for all gradable items for all learners in course offerings. This dataset is integral to a number of analytics solutions, including the Student Grade & Academic Risk Report, Learner Engagement, and Student Acknowledgement Quiz Completions.

Enrollments and WithdrawalsReturns enrollment status for all users in an org unit. This dataset is a useful driving table for queries where you might want to return a list of all learners, and then join other tables to add filterable information.

Instructor UsageThe Instructor Usage data set returns information about how instructors are using Brightspace Learning Environment functionality within their courses. This dataset is the driving table for the Instructor Engagement report.

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Learner UsageThe Learner Usage data set returns the activity for all learners in course offerings. This dataset is the driving table for the Learner Engagement report.

Awards IssuedReturns a list of all the awards that have been issued for your org units. This dataset is integral to the badging program at SEU.

Course AwardsReturns a list of all the awards that exist in each course for all your org units. This dataset is integral to the badging program at SEU.

Content User CompletionReturns information about specific user’s completion of content topics. This dataset is integral to the Learner Engagement report.

Content User ProgressReturns user progress records modified in the past three calendar years. Results are ordered from newest to oldest. This dataset is integral to the Learner Engagement report.

Discussion PostsReturns discussion posts posted in the past three calendar years. Results are ordered from newest to oldest. This dataset is a component of both the Instructor Engagement and Learner Engagement reports.

Grade ObjectsReturns a list of the grade objects created for your org units. This dataset is useful in determining whether a particular item exists in a given org unit’s grade book.

Org UnitsReturns details about all org units within your organization. This is an integral dataset to any Brightspace solution, as it provides content and contextual information relative to a given organizational unit.

Quiz AttemptsReturns details for each user quiz attempt for all your org units. This dataset is the driving table for the Quizzes Report.

Rubric Assessment CriteriaReturns details for all rubric criteria in rubrics. This dataset and the Rubric Assessment dataset are the driving tables for the Rubrics report.

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Rubric AssessmentReturns rubric outcomes that are associated with a competency. This dataset and the Rubric Assessment Criteria dataset are the driving tables for the Rubrics report.

Rubric ObjectsThe Rubric Objects data set returns information about the rubric properties. This dataset is a contextual table for the Rubrics report.

Rubric Object LevelsThe Rubric Object Levels data set returns information about the rubric levels in a rubric criteria. This dataset is a contextual table for the Rubrics report.

Survey AttemptsReturns details for each user survey attempt for all your org units. This dataset is the driving table for the new Course Evaluation dashboard, the new Student Acknowledgment Quiz Completions report, and any other report solution that looks at survey data from MyFIRE.

Fact BookThe annual Fact Book is among the more significant annual projects for Institutional Research, one which requires a large investment of time and personnel hours to successfully complete. It has evolved into a multi-department effort, coordinated by Institutional Research. The book includes a wide range of information about the university in an attractive and accessible format which is distributed to every office on campus including faculty. Essentially, the Fact Book is the primary public face of Institutional Research.

HistoryFrom 2007 to 2012, the Fact Book was published in 8½” x 11” size, and each copy was printed and bound by our office. In 2012 the cover was redesigned by Enrollment Marketing and professionally printed for the first time.

In 2013, the book was radically redesigned as a half-page, horizontal-bound handbook which was professionally printed. The redesigned version was created in Excel, allowing numbers to be auto-calculated through formulas that pull directly from census data. The 2014-15 edition saw a format update that more closely aligned with Enrollment Marketing’s design standards.

In 2015 Enrollment Marketing was given primary design control of the Fact Book. Our office provided an Excel file with all of the data and consulted on layout and data visualization. The collaboration has resulted in a vastly improved product.

Recently, much of this process has stayed the same. However, we no longer provide a simple Excel document. Instead, we have been instructed to print a copy of last year’s Fact Book and make hand-written notes for edits. While there is still an Excel sheet that populates most of the data totals for the Fact Book, mainly collected and cleaned by the Directed of Research &

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Strategic projects, we make notes on the copy and send a scan to Marketing. For areas like the Organizational Charts, we request updates from each department (via their admin, coordinator, etc.) and send these edits directly to Marketing in the various forms they might come in (digital, hand-written, minor updates, complete overhauls, etc.)

Plans for an online, dashboard-style Fact Book are underway and anticipated for initial implementation in the 2020-21 academic year.

ContentThe Fact Book can be divided into two main sections. The first portion of the Fact Book are various sets of general information, ranging from a list of board members to accreditation information to the academic programs that we offer. Some of these items rarely change, and some change every year. All of them should be checked every year. It is the responsibility of the Institutional Research office to check every single page of the Fact Book for verification or updates.

The second section is the Fall semester data, with enrollment data, Faculty & Staff data, and other data, including test scores, completions, and housing. All of these pages are updated every year, although many include longitudinal data that will still be included for a set number of years.

WorkflowThe Fact Book should be published by the first of November of each year, with an absolute deadline of the November Board of Trustees meeting. It cannot be completed much earlier than that because it relies on the timing of the official census data for Fall that is gathered, cleaned, and added to DM_Census by the Director of Research & Strategic Projects. However, the process should start in late Summer, by making contact with Enrollment Marketing, discussing updates and new additions, and preparing the data file (mainly those within the first half of the Fact Book.) We must make Marketing aware of the due date as well as how many copies we need printed. This will allow Marketing adequate time to finalize the layout and make changes before that. There will be a cycle of getting updated information, sending it to Marketing, receiving proofs from Marketing, reviewing the proofs to make sure everything was updated correctly, and sending notes back to Marketing.

The first half of the book involves a lot of gathering and verifying of information from a number of departments and individuals around campus. An updated list of Board members will need to be obtained from the Administrative Assistant to the VPIRE. Discipline-specific accreditations and Institutional Memberships will need to be verified by either the Director of Institutional Effectiveness or the CIO. Org Charts will also require updating and verification with each department; it is best to ask for these updates early in the process and give a specific due date. Receiving this information back can often take time as well as multiple reminders. Verify the list of sports and obtain updated athletic news from Athletics. Note that Athletic news should be based on the previous year, not news of an ongoing season.

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The Points of Excellence page is usually brainstormed with the VPIRE, CIO, and Director of Institutional Effectiveness and should include elements of broad interest. Figures for the Tuition, Room, and Board Comparison must be gathered from the SEU website; if any data is missing, an email to a Director in Financial Aid or Student Financial Services will need to be sent. The Academic Programs section will need to be verified and will need to be verified with data from major_minor_def_v for any organizational changes that have occurred. For most other pages in this half of the book updates should be obtained and verified with the appropriate individual or department on campus.

For the second half of the book, all of the data will come from the census or other data sets provided by the Director of Research & Strategic Projects. The Enrollment Summary will need to be adjusted if there are any new Master’s programs or undergraduate delivery types. Enrollment by Major will require an update if any organizational changes were made (e.g. departments or programs moving). This section, as well as Enrollment by State/Territory and International Enrollment will need to be updated and double checked once the final census data is in to ensure that all programs, states, territories, and countries are represented. Enrollment by Denomination and AG District will need to be adjusted to show the largest denominations and districts. Faculty pages and Completions will also need to reflect any organizational changes. All faculty related data comes from the Director of Research & Strategic Projects.

Other than these more specific changes, you will need to change headers and other references to the year and update longitudinal data sets to drop the oldest year and include the new year.

The PDF version of each Fact Book can be found on the Institutional Research Google Drive here: Research and Strategic Projects\@ File Cabinet\D - F\Fact Book

The PDF version of each Fact Book can also be accessed online by faculty and staff here: https://sfnet.seu.edu/departments/institutional-effectiveness/resources/

Data DictionaryThere are a number of terms particular to higher education in general and Institutional Research in particular. In some cases, terms are familiar, but the intricacies of how they work and how they are used in IR warrants explanation. This list is certainly not exhaustive, but hopefully will be a helpful start to the vocabulary of the field.CIP Code

“The Classification of Instructional Programs (CIP) provides a taxonomic scheme that supports the accurate tracking and reporting of fields of study and program completions activity.” It “identifies instructional program specialties within educational institutions.” NCES/IPEDS

The CIP Code is formatted as XX.XXXX, where the first two digits refer to a broad category of study, such as Business or Communication, while the last four digits refer to progressively more specific subsections of study within those categories.

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CIP codes can be assigned to faculty identifying teaching areas, departments, and even to every course. Currently, SEU uses them only to categorize majors and minors. In the Major Minor Definition table within Jenzabar a CIP Code is assigned to each major and minor code, but it is encoded without the decimal (i.e. XXXXXX).

The system was originally created in 1980, but the most recent revision was published in 2020. A database of all CIP Codes with detailed descriptions and crosswalk can be found at https://nces.ed.gov/ipeds/cipcode/Default.aspx?y=56

CohortA cohort is a particular group of students designated for monitoring or study. Upon matriculation every student is assigned to a cohort. If they return for a masters or doctorate they are assigned to another cohort. The most familiar cohort is the First-Time in College, FTIC, cohort. FTIC students are those who have never attended college since graduating from high school. This cohort of students is used for research and reporting retention, persistence and graduation rates. Other cohorts include Transfer, Freshmen Transfer, Graduate, Doctorate, Dual Enrolled and Non-degree. Once the official census is finalized for a semester, cohorts are assigned to all new students in Jenzabar and the Official Cohort table for tracking purposes.

Credit Hour“A unit of measure representing the equivalent of an hour (50 minutes) of instruction per week over the entire term. It is applied toward the total number of credit hours needed for completing the requirements of a degree, diploma, certificate, or other recognized postsecondary credential.” - NCES/IPEDS

Credit hour requirements vary by course and delivery type. This includes, but not limited to face-to-face, online, labs, field experience, internships/practicums, music performance, activity, etc. Details and definitions are in the College Catalog and Academic Affairs.

Generally, a degree requires a specific total number of credit hours, although the specific course requirements can make a degree in a specific discipline higher. So while a bachelor’s degree must be a minimum of 120 credit hours, most of our bachelor’s programs require between 125 and 130 hours.

DeliveryDelivery refers to the way in which course content is delivered to and consumed by the student. For instance, a course with a Traditional delivery -- a Traditional course -- meets face-to-face on the main campus during normal course times, over a full semester of 16 weeks. An Online course is conducted entirely or almost entirely through the online Learning Management System (LMS). Delivery can apply to a course or to a student; in the latter case it refers to how the student is designated or what the majority of their coursework consists of.

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DivisionThe Division designates the level of coursework or a degree, or of the student pursuing coursework or a degree. There are generally three division levels offered by colleges: undergraduate (including associate and bachelor’s degrees), graduate (usually master’s degrees), and doctoral (doctorate degrees). At SEU, the codes for these divisions are UG, GR, and DC, respectively. Every student, course, and degree is assigned a division. Also see the Student Division Master table for more information.

Full-TimeThe term Full-Time is used in enrollment as well as employment.

Full-Time is a designation of a student course load indicating that they are likely on track to finish a program in the prescribed amount of time. The number of credit hours required varies by division: undergraduates enrolled for 12 or more hours are full-time; for graduate students that number is 9 hours; and for doctoral students it is 6 hours. Anyone under these thresholds is considered part-time.

Full-time employees, whether Faculty or Staff, are those designated to work close to or equal to a forty-hour work week. For faculty, this generally equates to a 12-hour teaching load per semester, with advising and committee responsibilities.

Full-Time Equivalent (FTE)This is a way to count part-time members of a group of people, be they staff, faculty, or students, that provides a meaningful combination of full and part-time group. The most common method is the 1/3 Method, in which each part-time member is counted as 1/3 of a full-time member.

For instance, in Fall of 2014-15 we had 3,834 students, but 928 of those were part time. Therefore, our FTE enrollment number for that semester was 3,215.33, which we would usually round to 3,215. This method can also be used for staff or faculty.

NCES/IPEDS uses two different formulas when calculating FTE. To calculate Official Fall Enrollment FTE IPEDS uses fall headcount of FT and PT to calculate FTE. This method is also used by the Alliance. For Private, 4-year institutions calculate FTE by adding FT headcount to the PT headcount multiplied by 0.392857. Part-time graduate students are multiplied by 0.382059.

When calculating 12-Month Instruction Activity NCES/IPEDS uses a formula based on hours attempted by division. Total 12 month PT undergraduate hours are divided by 30. Graduate and doctoral PT hours are divided by 24. The PT FTE is added to the number of FT at each degree level.

Another method to calculate FTE is to divide a part-time student’s enrolled hours by the minimum full-time load (12 for undergraduate and 9 for graduate). Today, the FT count, plus 1/3 of the PT count is the most common method used today. It is the method most commonly used at SEU.

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Grade Point Average (GPA) Is a number between 0 and 4 based on the average of the numeric value of all earned grades. It can be calculated for a student, a cohort or other group of students. For each credit that a student attempts, they receive Quality Points based on their grade. For an A, for instance, a student will receive 4 Quality Points per credit hour, or 12 Quality Points for a 3-hour class. The GPA is calculated by adding all Quality Points earned and dividing by the credit hours. However, there is a special field called GPA hours for this purpose. This is because there are cases where Attempted Hours and GPA Hours will differ, for instance when a student receives a Withdrawal grade. A Withdrawal grade for a 3-hour course is worth 3 Hours Attempted, but zero GPA Hours, because the Withdrawal should not affect a student’s GPA.

When calculating GPA for a group, you should add all of the Quality Points for all students in the group and divide by the sum of GPA Hours for all students in the group. The alternative is to divide the sum of all the students’ GPAs by the number of students, but this method is an average GPA, not a group GPA. An average GPA would give the same weight to the grade of a student who took one course as to all five grades of a student enrolled for fifteen hours.

Graduation RateThe graduation rate is the percentage of a particular group of students (such as a freshman cohort or a racial/ethnic subset) who completed their degree program in a given amount of time. Usually, this is reported as a first-time, full-time freshman six-year graduation rate (representing 150% of the normal time for a bachelor’s degree) of a particular freshman cohort. Also sometimes reported are four- and eight-year graduation rates.

IPEDS and other organizations allow certain exclusions when reporting retention and graduation rates, which we have built into the Official Cohort table. These include students who died or were permanently disabled, those who left to join the military or serve in a church mission or foreign aid service. Students in these categories can be removed from the cohort, and the graduation rate is then calculated based on the adjusted cohort.

PersistencePersistence Rates are the percentage of a cohort or other subgroup returning from fall to fall with the exception of FTIC cohorts. While Retention Rates are an official measure of the percentage of FTIC students returning for their second fall semester, persistence rates are the percentage of students returning every fall from the original cohort. The calculation is the current number of students returning for the fall term, (Yr 2 to 3, Yr 3 to 4, etc) divided by the number of students in the original cohort. For all other groups, other than FTIC, persistence rates are calculated for 1st to 2nd year. This includes, Transfer, Dual Enrolled, and all grad students. Based on the length of the program, shorter grad programs are often calculated on a term to term persistence rate.

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Quality PointsSee Grade Point Average (GPA).

Race/EthnicityRace and Ethnicity can be defined a number of different ways, but almost all reports that we complete follow a particular set of categories established by the U.S. Department of Education. The categories used were updated in 2007 and implemented in IPEDS between 2008 and 2011. Therefore, you still may see the old categories in some reports and in older data. Here is a breakdown of the categories:

Old Categories New Categories

Hispanic Hispanic/Latino

American Indian/Alaska Native American Indian or Alaska Native

Asian/Pacific Islander Asian

Native Hawaiian or Other Pacific Islander

Black, non-Hispanic Black or African American

White, non-Hispanic White

Nonresident Alien Nonresident Alien

Race and ethnicity unknown Race and ethnicity unknown

Two or more races

Other than exact wording, the only changes are that the “Asian/Pacific Islander” category is split into two, and “Two or more races” is added as a new category.

The theory behind these changes, though, is a little more complex. Now, a person is recognized as having an ethnicity (either Hispanic or non-Hispanic) and a race (one of the other categories listed above). To incorporate this theory, Jenzabar added an Ethnic/Race Report table, rather than simply revising the categories in the Ethnic Group field in the Biograph Master.

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Retention RateThe retention rate is a percentage of students or a subset of students from one year and/or term that returned in a later period. The most common version is the Freshman Retention Rate, a commonly-reported metric, which is the percentage of first-time, full-time freshman from a Fall semester that re-enrolled for the following Fall semester.

Beyond the freshman retention rates, you could calculate retention rates for any group at any time in their college career. The calculation doesn’t change. But, because Retention Rate is a technical term. It is important to distinguish the official retention rates from other similar calculations. SEU has adopted the use of Persistence Rates to measure 3rd year, 4th year rates for FTIC. For all other cohorts of students, including transfer and graduate, rates are measured as persistence rates from year 1.

As with graduation rates, certain exclusions are allowed when calculating and reporting retention rates, including students who died or were permanently disabled, those who left to join the military or serve in a church mission or foreign aid service.

Return RatesReturn Rate is the percentage of students attending in one semester who return for the following semester. Return rates measure fall to spring and spring to fall. Return rates can be calculated overall or by various cohorts or subgroups of students. These are often used for financial and enrollment projections, budgeting and working with at risk student populations. Return Rates should not be confused with Retention or Persistence Rates. Return rates can be calculated by the number of students returning the following semester divided by the number enrolled at the end of the prior semester. One can also exclude students who graduate from the pool of students that could return. Circumstances often dictate which formula is used.

SATThe SAT is one of two major college entrance exams (the other being the ACT) that most students take for college acceptance and/or college placement.

Previously, the test included two main components (Verbal and Mathematics), each of which was calculated out of a maximum score of 800. So a perfect score on older versions of the test would be 1600. In 2005, the test was revised: the Verbal section was renamed Critical Reading and a Writing portion was added. The writing portion is also worth up to 800 points, so that a perfect score is now 2400. This is important because we occasionally have to report the combined Critical Reading and Mathematics scores, so that scores from the new version are comparable to scores from the old version. Often when we pull SAT data we have a column for each individual section score as well as two total scores: one using only the original two sections and with a potential total of 1600, and one with all three current sections and a potential total of 2400.

For analytic purposes the two component scores, 1600 max score, is used. This provides consistency in both analytics and results.

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Tuition CodeThe Tuition Code is a field in Jenzabar (student_master.tuition_cde) that designates the tuition rate a student pays. It also helps us to categorize students into delivery types, such as Online or Traditional. The field is used in the Student Census to help determine a student’s Group and Subgroup.

Web GroupThe Web Group code is a field in Jenzabar (student_master.tel_web_grp_cde) that allows a student to register for a particular group of courses, based on delivery type or registration period. For instance, students with the ON Web Group can register for undergraduate, online courses. Traditional seniors are given the code 04, which allows them to register earlier than other traditional groups. This code is usually related to the student’s Tuition Code, and in the Student Census process, the two codes are checked to make sure they do not conflict.

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Business Intelligence

In recent years, Southeastern’s Office of Institutional Effectiveness and Office of Research & Strategic Projects has developed a suite of business intelligence solutions to support organizational decision-making and continuous improvement efforts, as well as institution-wide student success initiatives. In general, these solutions are built in the Power BI platform, a Microsoft platform service that facilitates the generation, iteration, and dissemination of powerful analytics across the enterprise. Most of the dashboards and reports that comprise these solutions are built from data models in the SQL Server Management Studio, though some are supplemented by static Excel files and other sources. Below is a list of the major, sustained Power BI dashboards, along with descriptions of their purpose and use case scenarios. Also note the data models illustrated for reference.

Enrollment ATM: Reports the current semester enrollment as it stands “at-this-moment,” ATM. View summary enrollment, enrollment broken down by division, school, major, site, etc. Registration: View the current status of spring students as we look to the fall. Students are divided into graduating, returning, eligible to return, and has holds. Drill down to delivery, site, division, school, department and program/major.

RPG Dashboard: Descriptive and diagnostic analytics on the essential student success metrics at SEU: Retention (from Year 1 Term 1 to Year 2 term 1), Persistence (term to term), and Graduation (credential attainment). This report includes a detailed scorecard, as well as academic and demographic trends.

Assessment Dashboard: This dashboard functions like a portal in Power BI for academic and administrative leaders at SEU, comprising 8 report tiles which, when selected, open the corresponding Power BI reports. The following reports are included in the dashboard:

Rubrics: Dynamically integrated with the MyFIRE Learning Management System, this report displays up-to-date rubric averages and criteria subscale scores for any rubric assessed in the LMS in any course. Results are filterable by academic program, rubric, course, course section, and location. Trend scores are available on the second page of the report.

Quizzes: Dynamically integrated with the MyFIRE Learning Management System, this report displays up-to-date quiz averages and question item-level analysis for any quiz completed in the LMS in any course. Results are filterable by academic program, quiz, course, course section, and location. Item-level analysis includes course question average, points possible, and standard deviation.

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Academic Program Review: This multi-page report automatically generates the information solicited in the 5-year statistical analysis of the APR Handbook for those units currently completing the Academic Audit Self-Study portion of the review process. Data points include enrollment, graduation, student credit hours taught by faculty, full-time vs. part-time faculty statistics, faculty rank, DFW (Drop, Fail, Withdraw) analysis, grade distribution, and test scores. Data points are filterable by school, department, program, instructor, and other relevant variables.

ETS Proficiency Profile: Returns data from the nationally-benchmarked third-party general education proficiency measure. Students complete the 45-minute exam online and are assessed for proficiency in the following domains: critical thinking, reading, writing, and mathematics. They are also assessed on the following scales: critical thinking, humanities, mathematics, natural science, reading, social science, and writing. Data are filterable by credit hours completed, GPA range, student type, and gender.

Graduating Student Survey: Administered at the end of each term to graduating students, the Graduating Student Survey solicits information from students nearing the completion of their academic programs about their perspectives and relative levels of satisfaction with the range of services, resources, and experiences associated with their time at SEU. Data is displayed primarily as response distributions, as well as trend data, filterable by question category. Comments are included on the final report page.

Course Evaluation: Results of course evaluation scores from each term’s student rating of instruction are displayed in this report. On the first page, overall instruction and course design/experience scores are averaged in separate report page hemispheres, displayed as both trend lines and gauges with comparisons to institutional averages. The other report pages include a page that calls out instructors in red whose overall instruction ratings have either fallen below 4.0 on the likert scale or in green for those who scores have exceeded 4.5; a page that displays question item-level analysis; a page that displays response distributions; and a page that displays student comments for every course evaluated. Every page is filterable by year, term, school, department, instructor, course, course section, and location.

Student Satisfaction Inventory: Results from the semi-annual administration of Ruffalo Noel-Levitz’s (RNL) Student Satisfaction Inventory (SSI) are displayed in this report. The primary page returns a list of institutional strengths and challenges, determined by RNL analysts,

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for each year the survey has been administered. Strengths are those areas where student satisfaction is relatively high for questions where student sense of importance is also high. Challenges are those areas where a significant gap exists between students’ sense of importance and satisfaction. The second page displays a quadrant that maps the overall mean importance scores of a given category of the survey against its correlating satisfaction mean. Each category in the quadrant may be clicked on to filter the visual below it, which displays the response distributions for associated question items. The final page of the report displays satisfaction scores for all question items vs. satisfaction scores from participating institutions in the Council of Christian Colleges & Universities (CCC&U).

Thriving Quotient: The Thriving Quotient (TQ) report displays results of the administration of the TQ survey, administered semi-annually to SEU undergraduate students. The Thriving scores fall on a range of scales, from Academic Determination to Diverse Citizenship to Engaged Learning, and the like. It is a research-validated tool, designed to inform us about the degree to which students are flourishing as humans while in college, as opposed to just reporting satisfaction relative to services and institutional resources. The report’s sequential pages display response distributions for all question items, as well as student comments.

Student Grade & Academic Risk: View demographics for student populations that may be at-risk of academic probation or attrition in the coming term, based on current calculated final grades in MyFIRE (Brightspace). Student-level grade data, updated daily, and contextual information for intervention is included in this dashboard.

Instructor Engagement: Page 1 provides a rundown of every SEU instructor’s last access to their course in MyFIRE. Calls out those who have not accessed their courses in the last week. Page 2 returns critical metrics on any instructor’s engagement in MyFIRE (i.e. last access, last grade entry, discussion forum posts, rubric scores, student-level assignment grades and feedback by course). Updated daily.

Learner Engagement: A prototype of a forthcoming dashboard solution for monitoring student engagement in the learning management system. Currently, this report allows you to view any student’s activity metrics in MyFIRE, including time spent in content and assignment grades. Updated daily.

Transfer Dashboard: View trend data on transfer student enrollment, top transfer from institutions, geographical data, and key academic metrics for students who transfer in to SEU.

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Reporting

Reporting encompasses the surveys and questionnaires that we submit to external organizations and the tools, policies, and procedures we use to complete those reports. These reports range from those that are required for our financial aid and accreditation, such as IPEDS, to low-traffic college profile sites.

Reporting often overlaps with Research, since we are sometimes using the same data and definitions. Many of the data definitions that have become standardized within the field of Institutional Research stem from important reports such as IPEDS or US News.

Common Data Set The Common Data Set (CDS) is a collection of data (usually completed in Excel format) designed to simplify the reporting process for schools. The set contains commonly-agreed-upon data points to be reported to multiple reporting groups. In most cases, the group collecting the data will accept the CDS but asks for additional information as well. Organizations such as U. S. News and World Reports and Peterson’s can input the CDS data automatically, leaving less for the IR office to input manually.

The CDS is divided into ten sections:

A. General InformationB. Enrollment and PersistenceC. First-Time, First-Year (Freshman) AdmissionD. Transfer AdmissionE. Academic Offerings and PoliciesF. Student LifeG. Annual ExpensesH. Financial AidI. Instructional Faculty and Class SizeJ. Degrees Conferred

Items within these sections are numbered, and are commonly referred to by the letter of the section, plus the number of the item. For example, freshman high school completion requirements can be found in section C, and is item number 3; the item, then, may be referred to as C3 or CDS C3.

In addition to these data sections, there are sections for definitions and for changes from the previous year.

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Completing the Common Data SetThe blank CDS file can be downloaded from commondataset.org. While the file is available in several formats, we have always used the Excel format, which seems to be the most common version used industry-wide. We typically complete the CDS with the use of specific SQL queries, the Fact Book, and data from the Director of Research & Strategic Projects.

The following sections will briefly discuss the ten sections of the CDS and some tips for completing them.

A - General InformationThe General Information section consists of respondent information (A0) and general university information (e.g. address, academic calendar type) that will rarely need to be changed. Use the previous year’s data as a starting point.

B - Enrollment and PersistenceThis section consists of data that will come from the current year’s Fall census (B1-B2, B22), the previous year’s graduation data (B3), or freshman cohort data (B4-B11; items B12-B21 apply only to two-year institutions). All of these items are collected and maintained by the IR office for purposes outside of the CDS.

C - First-Time, First-Year (Freshman) AdmissionThe first item in this section, C1, counts new freshman students in the three main stages of admission. The final stage, counting students who enrolled, should come from the Fall census. The other two stages (applied and admitted) can be pulled using the SQL queries for CDS written by the Director of Research & Strategic Projects.

Items C2-C8 are in regard to admission requirements, and items C13-C22 cover admission policies. These items do not change frequently, but they should be checked for accuracy every year.

Items C9-C12 ask for data on the incoming freshman class, such as standardized test scores and high school GPA. Always refer to last year’s CDS (in every section) to see what areas might be skipped, and confirm if they should still be skipped or if we are now able to complete the portions due to better data collection and cleaning.

D - Transfer AdmissionItem D2 is similar to C1, but counting transfer students instead of new freshmen. The data would be gathered from the same sources as in C1.

tems D3-D11 cover admission requirements and policies for transfer applicants, while D12-D17 cover transfer credit policies. Like items C2-C8 and C13-C22, these items do not change frequently. However, they should still be checked every year. Items D3-D11 should be verified

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by Admission, while items D12-D17 should be verified by the Office of the Registrar. This can be done with the help of CIO or via email to the departments.

E - Academic Offerings and PoliciesThis section is very brief, covering special study options (E1) and areas of common requirements (mainly general education, E3). These are items that seldom change, but they should be checked for accuracy.

F - Student LifeItem F1 asks for several pieces of information regarding our freshman cohort and our undergraduates. All of these can be calculated from the Fall census.

Items F2-F4 cover available activities and housing options. These items do not change frequently, but should be verified.

G - Annual ExpensesThis section collects cost-of-attendance data. Note that these data should be for the following year, not the year in which you are reporting. In recent years, tuition and fees (G1 & G6) have not been available when the CDS is first being completed. If this is the case, be sure to enter an approximate date when these items will be available (usually between March and May of the academic year).

Items G2-G4 rarely change, but should be checked for accuracy when G1 is completed. Item G5 should be gathered from Student Financial Services; it may be available before tuition and fee data.

H - Financial AidItems H1-H6 come from an SQL query that runs on the PowerFAIDS database.

I - Instructional Faculty and Class SizeThis section covers faculty demographics, student-to-faculty ratio (using the ⅓ method), and class sizes. These items come from faculty data, course data, or a combination of faculty and student data. All of the sources are a part of the normal fall data collections and can be collected using the SQL queries written by the Director of Research & Strategic Projects.

J - Degrees ConferredThis final section breaks down undergraduate degrees awarded in the previous academic year by CIP category and degree level. It should be completed based on the completion data for the year in question.

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List of Reports – Alphabetical The following is an alphabetical list of annual reports that the IR Office is asked to complete. A separate section lists these reports by approximate due date.

Report Name Opens Due Priority

AAUP Faculty Compensation Survey Mid-Nov. Early Feb. Medium

ACT Institutional Data Questionnaire (IDQ) Early Feb. Mid-April Medium

Alliance for AG Higher Ed Data Report Early May Mid-June Required

Association for Biblical Higher Education (ABHE) Late Sept. Mid-Nov. Required

Association of Theological Schools (ATS) Report Late Sept. Late Nov. Required

College Board’s Annual Survey of Colleges (ACS) Mid-Nov. Mid-Feb. Medium

Common Data Set (CDS) Early Nov. Late Nov. Required

CSRDE Section 1 Retention Survey Mid-Jan. Early March Medium

CUPA-HR Mid-Dec. Mid-Jan. Medium

FETPIP Early March Late April Required

FL DOE Fair Consumer Practices Late Oct. Early Jan. Required

HEP Higher Education Directory Survey Mid-July Late July Required

ICUF Accountability Report Late July Early Aug. Required

ICUF Annual State College, Branch Site, and Online Degree Report Late May Mid-June Required

IPEDS Fall Collection Early Sept. Mid-Oct. Required

IPEDS Spring Collection Early Dec. Early April Required

IPEDS Winter Collection Early Dec. Mid-Feb. Required

NAICU Tuition Survey Early Aug. Late Sept. Medium

Peterson’s Annual Survey of Undergraduate Financial Aid Mid-Feb. Late April Medium

Peterson’s Interim Expense Update for UG Institutions Mid-Oct. Mid-Nov. Medium

Peterson’s Survey of Graduate and Professional Institutions Mid-Feb. Early July Medium

Peterson’s Survey of Undergraduate Institutions Late Jan. Early May Medium

Peterson’s Survey of Distance Learning Institutions Mid-May Late June Medium

Peterson’s Survey of Distance Learning Programs Early May Late June Medium

SACSCOC Financial Mid-June Late Aug. Required

SACSCOC Profile for General & Enrollment Information Mid-Nov. Mid-Jan. Required

SAT Validity Study Early Aug. Late Oct. High

Tampa Bay Business Journal Early Oct. Mid-Oct. Low

US News Best Colleges Early April Early June High

US News Best Online Programs Mid-Aug. Late Sept. Medium

US News Best Graduate Programs Early Nov. Early Dec. Medium

UCAN Update Early Dec. Early March High

Wintergreen Orchard House Early Feb. Early March Low

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List of Reports – By Due Date

Report Name Opens Due Priority

US News Best Colleges Early April Early June High

Peterson’s Survey of Graduate and Professional Institutions Mid-Feb. Early June Medium

Alliance for AD Higher Ed Data Report Early May Mid-June Required

ICUF Annual State College, Branch Site, and Online Degree Report Late May Mid-June Required

Peterson’s Survey of Distance Learning Institutions Mid-May Late June Medium

Peterson’s Survey of Distance Learning Programs Early May Late June Medium

HEP Higher Education Directory Survey Mid-July Late July Required

ICUF Accountability Report Late July Early Aug. Required

SACSCOC Financial Mid-June Late Aug. Required

NAICU Tuition Survey Early Aug. Late Sept. Medium

US News Best Online Programs Mid-Aug. Late Sept. Medium

IPEDS Fall Collection Early Sept. Mid-Oct. Required

Tampa Bay Business Journal Early Oct. Mid-Oct. Low

SAT Validity Study Early Aug. Late Oct. High

Association for Biblical Higher Education (ABHE) Late Sept. Mid-Nov. Required

Peterson’s Interim Expense Update for UG Institutions Mid-Oct. Mid-Nov. Medium

Association of Theological Schools (ATS) Report Late Sept. Late Nov. Required

Common Data Set (CDS) Early Nov. Late Nov. Required

US News Best Graduate Programs Early Nov. Early Dec. Medium

FL DOE Fair Consumer Practices Late Oct. Early Jan. Required

CUPA-HR Mid-Dec. Mid-Jan. Medium

SACSCOC Profile for General & Enrollment Information Mid-Nov. Mid-Jan. Required

AAUP Faculty Compensation Survey Mid-Nov. Early Feb. Medium

College Board’s Annual Survey of Colleges (ACS) Mid-Nov. Mid-Feb. Medium

IPEDS Winter Collection Early Dec. Mid-Feb. Required

CSRDE Section 1 Retention Survey Mid-Jan. Early March Medium

UCAN Update Early Dec. Early March High

Wintergreen Orchard House Early Feb. Early March Low

IPEDS Spring Collection Early Dec. Early April Required

ACT Institutional Data Questionnaire (IDQ) Early Feb. Mid-April Medium

FETPIP Early March Late April Required

Peterson’s Annual Survey of Undergraduate Financial Aid Mid-Feb. Late April Medium

Peterson’s Survey of Undergraduate Institutions Late Jan. Early May Medium

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Summary of Report ProcessesThis section explains briefly what each report requires and how it is submitted.

AAUP Faculty Compensation SurveyOpens: Mid-November Closes: Early FebruaryLevel: Medium PriorityCDS: Not ApplicableWebsite: https://research.aaup.org/Pages/Index.aspx

This survey asks for faculty counts and aggregate compensation, grouped by faculty rank and gender. Since 2012-13, this survey has been completed by the Human Resources office, which completes similar surveys for CUPA (see below) and CCCU. Occasionally, the HR Office will request a few data points from our office to fulfill this survey.

ACT Institutional Data Questionnaire (IDQ)Opens: Early February Closes: Mid-AprilLevel: Medium PriorityCDS: UnknownWebsite: http://act.org/idq/

The ACT Institutional Data Questionnaire (IDQ) is an annual survey of general information about enrollment, admissions, costs, financial aid, student affairs, and academic programs. By updating this survey we are providing more up-to-date information to students who take the ACT. In recent years, this survey has been completed by the Director of Research & Strategic Projects.

Alliance for AG Higher Ed Data ReportOpens: Early May Closes: Mid-JuneLevel: RequiredCDS: NoWebsite: http://colleges.ag.org/

The Alliance for AG Higher Education (Alliance) is a branch of the General Council of the Assemblies of God (AG) focusing on postsecondary institutions. As a member of the Alliance, we are required to complete the Annual Questionnaire (AQ). The name of this survey has changed over the years, but it will always refer to the Alliance, and mention a payment due.

With the questionnaire, we are to submit a check to pay the Alliance Service Fee. The calculation for this fee is at the bottom of the last page. This calculation should be done as soon as possible so that the check can be requisitioned.

As this report has changed over recent years, use the previous year’s submission as a reference

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for data points that have remained the same. In 2018-2019, the survey was emailed to the VP of Enrollment Management and the Executive Director of Student Financial Services. In 2019-2020, the survey was emailed to the University President and the Provost. The 2019-2020 survey collection also did not include any requested payment for the year, due to the economic crisis during the COVID-19 pandemic.

As soon as the survey is complete, obtain any necessary physical items such as payment or signatures so that it can be submitted promptly. Association for Biblical Higher Education (ABHE)

Opens: Late September Closes: Mid-NovemberLevel: RequiredCDS: UnknownWebsite: http://abhe.org

This survey was changed in 2018-2019 or 2019-2020 with updated instructions and data points to be gathered. The survey is split into four sections:

1. Tenets of Faith2. Admissions Statistics3. Enrollment, Faculty, Outcomes & Library Statistics4. Financial Statistics

The first section, Tenets of Faith, must be sent to the University President immediately upon receiving the survey, as the document must be signed by the President and emailed back to ABHE. This document, as well as the instructions and the survey due date, are emailed to support staff for the President for completion. Our office must verify that the document has been signed and returned by the President before the survey due date.

Section two and three are completed online. As Fall census data is pulled around the time of this report, the Director of Research & Strategic Projects must be made aware of this impending due date so that DM_Census data can be available for use in completing this survey. Other data sources such as Fact Book, CDS, IPEDS, etc. might be applicable. Data for the Library portion is requested by our office to the Library.

The fourth section is to be downloaded and sent to the Director of Accounting & Financial Reporting with instructions as well as due date information. Once this is received, it is to be emailed back to ABHE.

Association of Theological Schools (ATS) ReportOpens: Late September Closes: Late NovemberLevel: RequiredCDS: Not AcceptedWebsite: http://ats.edu

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Communication for this survey is sent directly to the Barnett College of Ministry and Theology. Our role in this survey has varied over the years from supplying some data points to pulling and entering all data into the online submission website. This report always includes two separate due dates within the submission. Section “e. Enrollment by Race and Gender” is always due before the rest of the sections. This will be noted in the instructions. Data for the survey is gathered with a series of SQL queries. Few portions of this survey will be completed by BCMT. They have always maintained excellent communication in what sections they need help with from our office, and which sections they are able to complete themselves.

College Board’s Annual Survey of Colleges (ACS)Opens: Mid-November Closes: Mid-FebruaryLevel: Medium PriorityCDS: AcceptedWebsite: http://collegeboard.org

The College Board survey updates our university’s institutional profile on their website. Their site, they claim, gets more than ten million hits annually.

College Board accepts the Common Data Set for most of the survey. CDS should be emailed to the survey contact at College Board once instructions for the survey are received. They will verify that our CDS has been entered, and questions outside of CDS must still be answered in their online platform.

CSRDE Section 1 Retention SurveyOpens: Mid-January Closes: Early MarchLevel: Medium PriorityCDS: Not AcceptedWebsite: http://csrde.ou.edu/web/index.html

The Consortium for Student Retention Data Exchange (CSRDE) is an organization created and controlled by the University of Oklahoma. They gather retention data from a number of institutions and produce a large report on the findings. As a participant, we receive a copy of the report, which contains a great amount of useful data on retention.

The survey asks for extensive retention and graduation data year by year on our last ten freshman cohorts, with subcohorts for gender and race/ethnicity. They also ask for a number of data on enrollment, freshman demographics (such as percent living on campus), average test scores, average first-semester GPA, and percent receiving federal aid.

The survey is completed as an Excel file and then uploaded to a secure dropbox, accessed by logging into the CSRDE website. This survey is completed by the Director of Research & Strategic Projects each year.

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CUPA-HR SurveyOpens: Mid-December Closes: Mid-JanuaryLevel: Medium PriorityCDS: Not AcceptedWebsite: http://cupahr.org

The College and University Professional Association for Human Resources (CUPA-HR) survey is completed annually by the Human Resources department. A few items must be obtained from our office, but they are all items we have already calculated: Total Expenses from the IPEDS Finance Survey; enrollment data (by Full-time/Part-time and undergraduate/graduate, as well as FTE); and Faculty counts. FETPIP

Opens: Early March Closes: Late AprilLevel: RequiredCDS: Not AcceptedWebsite: http://www.fldoe.org/accountability/fl-edu-training-placement-info-program

The Florida Education Training Placement and Information Program (FETPIP) is conducted by the Florida Department of Education. Each year, we report data on each of the previous year’s graduates. The information requested is nothing uncommon for a file of graduating students; the main difference is the formatting that FETPIP requires. For instance, the Date of Birth is requested as MMDDYYYY, rather than MM/DD/YYYY, or some other format. Entry date and graduation date are similar, but without the day, i.e. MMYYYY.

Using an SQL query built to properly format the items required makes this request fairly simple. The data will simply need to be saved into an Excel file, which will then need to be uploaded to the secure FTP site provided. This survey is completed by the Director of Research & Strategic Projects each year.

Florida Department of Education Fair Consumer PracticesOpens: Late October Closes: Early JanuaryLevel: RequiredCDS: Not Accepted

This survey is completed by the Compliance Coordinator each year.

This report is a part of the state of Florida’s Exemption from License process, and is sometimes labeled with that title instead of Fair Consumer Practices. In addition to Fair Consumer Practices documentation, we also submit a report on physical plant safety. The Physical Plant Safety Assessment for the previous calendar year (e.g. for 2015 we will submit the 2014 report) can be obtained from Safety and Security.

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The Fair Consumer Practices section asks for information on several consumer-related points (e.g. statements on credit transfer policy, student discipline policy, refund policy, etc.). Most of these can be copied from year to year, but if they reference a statement on the university’s website or in the catalog, these should be checked for accuracy.

The report will require some appendices, including tuition and fee schedules, a copy of all advertising (obtained from Admission), and a copy of the student handbook.

The final copy of the report requires the President’s signature, so this must be completed in a timely fashion. The report can be submitted via mail or email.

HEP Higher Education Directory SurveyOpens: Mid-July Closes: Late JulyLevel: RequiredCDS: Unknown

In recent years, this survey has been received via mail, addressed to the University President. It is extremely easy to complete online requiring little time or effort.

ICUF Accountability ReportOpens: Late July Closes: Early AugustLevel: RequiredCDS: Not Accepted

The Independent Colleges and Universities of Florida (ICUF) is an organization of private, not-for-profit Florida institutions that work together for a number of reasons, including responding to state data and transparency requests. This report was once rather cumbersome, but in recent years ICUF has done an excellent job of paring down the state’s requests, mainly by directing them to use IPEDS and other data resources.

The streamlined version of the Accountability Report is very simple, the most recent version asking for only nine data elements. These are entered into an Excel file, provided by email from the ICUF office, which is submitted by email back to the original sender.

Some data points relating to FRAG might need to be provided by the Director of Research & Strategic Projects due to permissions as well as data clean-up.

ICUF Annual State College, Branch Site, and Online Degree ReportOpens: Late May Closes: Mid-JuneLevel: RequiredCDS: Not Accepted

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This survey is more time consuming than it is difficult. It requires manually updating an Excel spreadsheet and emailing it back to the ICUF representative. The Excel spreadsheet has three tabbed worksheets to be completed, one each for:

1. A list of the state college/community college campuses where your institution has on-site programs (e.g., St. Petersburg College, Tallahassee Community College, etc.). If you have sites on multiple state/community college campuses (e.g., Saint Leo is on three of Pasco-Hernando State College campuses), please list those separately.2. A list of your institution’s satellite sites/branch campuses (not to include state/community colleges). For purposes of this report, we only need your physical sites located in Florida. 3. A list of your online degree and graduate certificate programs. You do not need to list individual courses but only the names of the fully online degree and certificate programs. Please use the IPEDS definitions for distance learning: Distance education course - A course in which the instructional content is delivered exclusively via distance education. Requirements for coming to campus for orientation, testing, or academic support services do not exclude a course from being classified as distance education. Distance education - Education that uses one or more technologies to deliver instruction to students who are separated from the instructor and to support regular and substantive interaction between the students and the instructor synchronously or asynchronously. Again, we only need the names of degree and graduate certificate programs, and not individual courses.

These instructions are provided by ICUF but might change in future collections of the survey. Always refer to the instructions received in each new survey opening. IPEDS

Opens: Early August Closes: Early AprilLevel: RequiredCDS: Not AcceptedWebsite: https://surveys.nces.ed.gov/IPEDS/Index.aspx

The Integrated Postsecondary Education Data System (IPEDS) is a data collection administered by the National Center for Education Statistics, a branch of the United States Department of Education. The IPEDS surveys are required for all institutions that participate in any Federal financial aid programs.

The collection is updated annually through a series of surveys, administered in three “collections,” the first opening in early September and the third closing in early April. Registration opens in early August, at which time the IC Header is available. This report is brief, and most of its questions are rarely updated. However, it is the responsibility of the Director of Research & Strategic Projects to complete the IC Header.

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Throughout the system you will receive notifications of potential errors, usually based on a range of likely value based on the previous year’s reported value. Most of these errors are nonfatal and can be cleared with a confirmation or explanation. A fatal error, however, must be fixed before the survey can be “Locked” for final submission. There is one exception in the Finance report, where a fatal error is given, but the number is correct. To give an explanation for a fatal error, you must call the IPEDS Helpdesk and explain the error.

The Keyholder for Southeastern University is the Director of Research & Strategic Projects while most data is pulled, cleaned, and entered by the Data Techniciatio & Reporting Specialist. Collaboration between all staff within IR and IE are vital to complete each portion of the surveys, as some data can only be retrieved by the Director of Research & Strategic Projects. It is also the responsibility of the Keyholder to run all “Run First” queries at the start of the Fall Collection so that all data needed is captured.

For a helpful overview of all survey components in the various IPEDS collections, go to https://nces.ed.gov/ipeds/use-the-data/survey-components.

IPEDS Fall CollectionOpens: Early September Closes: Mid-October

The Fall Collection consists of three surveys: Institutional Characteristics, Completions, and 12-month Enrollment.

Institutional CharacteristicsThis survey collects various pieces of information about the university. Much of this information does not frequently change. The main exception to this is student charges.

CompletionsThe Completions survey collects data on degrees awarded during the previous academic year (July 1 to June 30). All data will come from the Completions data file for the given year that is provided by the Director of Research & Strategic Projects.

This report is somewhat cumbersome to complete, since the main data table breaks down completions by CIP code, award level, gender, and race/ethnicity all at once. Other sections ask for graduates by first major, by second major, and by ethnicity. In these tables it is important to count a graduate only once, even if they earned two degrees (e.g. a BA and a BS, or a BS and an MEd). The final tables ask for all students who earned a given degree; here it is correct to count a student multiple times if they earned multiple degrees.

12-Month EnrollmentThis survey covers enrollment for the most recent full academic year. The survey consists of two parts. Part A consists of an unduplicated count of enrolled students, broken down by division,

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gender, and race/ethnicity. Part B asks for total credit hour activity (by division) and FTE estimates for the 12-month period. Data for this is pulled using the “Unduplicated Headcount” SQL query written by the Director of Research & Strategic Projects.

IPEDS Spring CollectionOpens: Early December Closes: Early April

The IPEDS Spring Collection consists of four surveys: Fall Enrollment, Finance, Human Resources, and Academic Libraries. This collection has the highest potential for complications, since for three of the four surveys we must heavily rely on other departments to gather the proper data. Thoughtful planning is key. Fortunately, this collection also has the longest time frame, and with proper planning and coordination it can easily be completed with a month or more to spare. As noted above, the collection is opened simultaneously with the Winter Collection, but it does not need to be addressed until January at the earliest. Begin by asking the Director of Research & Strategic Projects to request any needed data from the Human Resources department (see below for the Human Resources survey), sending the Academic Libraries portion to the Library staff, and sending the Finance portion (along with last year’s submitted survey) to the Director of Accounting & Financial Reporting.

Fall EnrollmentThe Fall Enrollment survey is the only component of the Spring Collection that relies completely on data that will have already been collected by the IR office.

Part A counts Fall enrollment, with separate tables for each combination of division and full- vs part-time. Each of these tables is also broken down by gender and race/ethnicity. Also included are tables that gather enrollment data for specific CIP code categories, such as Education, Business, and Mathematics.

A separate section within Part A breaks down enrollment by distance education status. For this, you must look at student course data to see whether they took all, some, or no distance education classes during the Fall semester.

In Part B, enrollment is broken down by age groups and gender. Part C asks for counts of first-time undergraduates by residence (mainly states and U.S. territories), with a subcount of those who enrolled within twelve months of high school graduation. Part D is a breakdown of the total undergraduate entering class.

Parts A through D can be completed almost exclusively with SQL queries written by the Director of Research & Strategic Projects. Part E asks for retention data based on the previous year’s freshman full-time and part-time cohorts. Part F collects the student-to-faculty ratio for the Fall semester. The data for both of these sections is often requested of the Director of Research & Strategic Projects due to the complicated nature of the data, to ensure its accuracy.

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FinanceThe Finance Survey is completed almost entirely from the annual Financial Statements, or audit, and not from any data files that we have otherwise collected and processed. In 2019-2020, a Director of Accounting & Financial Reporting was hired for the Business Office who now supplies the data for this section. Simply export a blank copy of this year’s Finance section, email it to the Director along with last year’s submitted section, and coordinate until all data is provided and clean within the survey platform.

Human ResourcesOf all the IPEDS surveys, the Human Resources has, for some reason, been the most prone to complications in recent years. The survey focuses on both Faculty and Staff data, which IPEDS refers to as Instructional Staff and Non-Instructional Staff, respectively. Staff data comes from the Human Resources department, while Faculty data is cleaned and provided by the Director of Research & Strategic Projects. The Human Resources section of IPEDS is the responsibility of the Director of Research & Strategic Projects due to its complexity, as well as for privacy reasons.

Academic LibrariesThe Academic Libraries survey was for years a separate survey from the IPEDS system. In 2014-15 it was added back to IPEDS, but since the survey had been completed by the library staff at many institutions, the option was given to add the previous contact for this survey as an IPEDS contact for the Academic Libraries component. At Southeastern, this survey is completed by a member of the library faculty, currently Glenn Pearl. In some years, Mr. Pearl completes this section without interaction or assistance from our office. In more recent years, our office has supplied a blank copy of the survey and emailed it to Mr. Pearl for him to fill out and return to us for data entry within the submission website.

The survey includes numbers about the library collection and circulation, expenditures, and interlibrary loans.

IPEDS Winter CollectionOpens: Early December Closes: Mid-February

The Winter Collection consists of five surveys: Student Financial Aid, Graduation Rates, 200% Graduation Rates, Admissions, and Outcome Measures.

The Winter and Spring Collections both open at the same time, but the Spring Collection closes considerably later. Best practice is to work on the Winter Collection immediately and save the Spring Collection until the Winter Collection is done. Taking Christmas break into account, you should have little trouble finishing the Winter Collection by mid-January, leaving plenty of time for the more time-consuming Spring Collection (see below).

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Student Financial AidThis survey centers around four groups of students:

1. All undergraduate students2. Full-time, first-time degree-seeking students3. Group 2 Students awarded any grant or scholarship aid from federal or state governments, or from the institution4. Group 2 students awarded any Title IV federal aid

The following parts of Section 1 will center on these groups, asking about the numbers of students and amount of aid awarded, as well as cost of attendance information. This is all information that can be ascertained from a combination of census and financial aid data, or from Student Financial Services.

Section 2 of this survey asks about students who receive GI bill benefits and the amount of aid awarded. This data will come from Student Financial Services.

Graduation RatesThis survey looks at graduation rates for a freshman cohort from six full years previous to the reporting year, broken down by gender and race/ethnicity. SQL queries written by the Director of Research & Strategic Projects are used to complete all sections of the Graduation Rates portion.

In Section 1, we are asked to make adjustments to the initial cohort, which was reported in the IPEDS reporting of the cohort year. The adjustment separates students who initially enrolled in a bachelor’s degree program from those who entered in another program, such as an associate’s degree. In Section 2, the completion times of the bachelor’s subcohort are reported, broken down by gender and race/ethnicity. There are separate columns for students who completed programs of various lengths.

Next, we must subdivide the completers by the amount of time it took them to finish, whether four years or less, five years, or six years. Finally, we must report exclusions. For us, this would primarily include students who died or became permanently disabled, or students who left for military or church mission reasons. In addition to these exclusions, there are columns for transfer-out students (which we have not previously reported), and students who are still enrolled. Transfer-out data is gathered by the Director of Research & Strategic Projects from NSC and is then uploaded to the server. Our office must check with the Director of Research & Strategic Projects as to when this data will be available for IPEDS use.

200% Graduation RatesThis survey is by far the simplest and quickest of all IPEDS surveys. It simply looks at the freshman cohort from eight years previous to the reporting year (which would have been reported in the Graduation Rates survey two years previous) and asks for an update to see if any more finished between six and eight years.

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AdmissionsThis section asks for some basic information about admissions considerations; counts of applicants, admissions, and enrollees; and SAT and ACT scores for incoming students. Some of this data can be found in CDS or the Fact Book, while other data points require the use of SQL queries written by the Director of Research & Strategic Projects.

Outcome Measures Outcome measures was a new survey component for the 2015-16 reporting year. The goal of the section is to gather data on cohorts beyond the traditional first-time, full-time freshmen cohort. The survey includes that cohort, plus part-time, first-time students; full-time, non-first-time entering students; and part-time, non-first-time entering students. For each category, it will ask for the cohorts to be divided into four categories: received award; did not receive award, still enrolled at institution; did not receive award, enrolled at another institution; did not receive award, enrollment status unknown. These data will be requested for the eight-year cohorts (matching the 200% Graduation Rates year).

This section also requires transfer-out data provided by the Director of Research & Strategic Projects.

NAICU Tuition SurveyOpens: Early August Closes: Late SeptemberLevel: Medium PriorityCDS: NoWebsite: http://naicu.edu

This survey consists of a link to a Survey Monkey submission and only contains a few questions pertaining to tuition rates. The tuition information requested can be found on SEU’s website.

Peterson’s Annual Survey of Undergraduate Financial AidOpens: Mid-February Closes: Late AprilLevel: Medium PriorityCDS: Mostly AlignedWebsite: http://www.petersonssurveys.com

Compared to other Peterson’s surveys, this one is quicker and easier to complete due to CDS being the main data source, along with one SQL query.

Peterson’s Interim Expense Update for Undergraduate InstitutionsOpens: Mid-October Closes: Mid-NovemberLevel: Medium PriorityCDS: Partially AlignedWebsite: http://www.petersonssurveys.com

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This survey is simply an opportunity to update the cost of attendance information in Peterson’s of Undergraduate Institutions.

Peterson’s Survey of Graduate and Professional InstitutionsOpens: Mid-February Closes: Early JulyLevel: Medium PriorityCDS: NoWebsite: http://www.petersonssurveys.com

This is one of the most difficult and time consuming surveys to complete, especially within the surveys from Peterson’s. It deals with Graduate program information that is not easily available to us, or is so detailed that it takes an extreme amount of time to obtain a single data point. There are many portions of the survey that are intentionally left blank due to them being too time consuming with unreliable data.

Peterson’s Survey of Undergraduate InstitutionsOpens: Late January Closes: Early MayLevel: Medium PriorityCDS: Partially AlignedWebsite: http://www.petersonssurveys.com

Peterson’s Survey of Undergraduate Institutions is an in-depth survey conducted annually. Where questions in this survey align with the Common Data Set, they are marked so. Other items they ask for are easily accessible from other surveys that we submit (e.g. endowment) or common knowledge (e.g. nearest major metropolitan area, nearest commercial airport). Other data points are produced with SQL queries.

Cost of Attendance data usually is not available when this survey is submitted, so we submit it during the Interim Expense Update.

Peterson’s Survey of Distance Learning InstitutionsOpens: Mid-May Closes: Late JuneLevel: Medium PriorityCDS: NoWebsite: http://www.petersonssurveys.com

Peterson’s has two surveys related to Distance. This survey asks for some general questions about our online offerings, as well as specific questions on each program that we offer online, such as program requirements, cost, and if there are any on-campus requirements.

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Peterson’s Survey of Distance Learning ProgramsOpens: Early May Closes: Late JuneLevel: Medium PriorityCDS: NoWebsite: http://www.petersonssurveys.com

This is the second Distance survey from Peterson’s. As of recent years, it has not been completed by our office. At times, it is sent directly to Unrestricted Education staff and it is their discretion to submit or not. When our office does complete this survey, it is extremely time consuming as we must gather information about the programs that are not readily available or known to us.

SACSCOC Financial Opens: Mid-June Closes: Late AugustLevel: RequiredCDS: Not ApplicableWebsite: http://sacscoc.org

The Financial Profile and Indicators is the second and final submission to SACS, our accrediting agency. Like the General & Enrollment Information survey (below), it is short but essential. It asks for several revenue figures split into two sections: one section uses IPEDS data and one section uses financial audit data from the Business Office. For 2015, a Documentation file was saved with copies of the relevant pages from both the IPEDS Finance Survey and the audit, with the relevant figures marked.

The survey is completed online and an email is sent to the University President to sign the submission electronically. Our office must make sure the President is aware of this incoming digital signature request. It is also good practice to request confirmation of signature completion from the President’s office.

SACSCOC Profile for General & Enrollment InformationOpens: Mid-November Closes: Mid-JanuaryLevel: RequiredCDS: NoWebsite: http://sacscoc.org

The Institutional Profile is one of two annual submissions to the Southern Association of Colleges and Schools Commission on Colleges (SACS-COC or SACS), our accrediting agency. It is a short but extremely important survey, requesting enrollment and FTE numbers and graduation rate data. It also requires the submission of contact information for the CEO (President), Institutional Accreditation Liaison Officer (VP-IR/EE), and Chair of the Board, with corrections made for updated information.

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The survey must be completed online once the data has been verified by the CIO or the Director of Institutional Effectiveness. From there, an email is sent to the University President to sign the submission electronically. Our office must make sure the President is aware of this incoming digital signature request. It is also good practice to request confirmation of signature completion from the President’s office.

SAT Validity StudyOpens: Early August Closes: Late October(Note that request for participation is sent out earlier in the year.)Level: High PriorityCDS: Not ApplicableWebsite:

The SAT Validity Study is a voluntary request of data on freshman cohorts and their college success. Each year we submit a new file for the previous year’s cohort, as well as updates on the previous cohorts, going back to the 2010 cohort.

Our office has benefited from the fact that this study includes a stipend based on the number of files that we submit. This survey is completed in entirety by the Director of Research & Strategic Projects.

Tampa Bay Business JournalOpens: Early October Closes: Mid-OctoberLevel: Low PriorityCDS: Not ApplicableWebsite: https://www.bizjournals.com/tampabay/

The Tampa Bay Business Journal’s Annual List of Colleges and Universities collects basic information about the university such as enrollment, cost, and location, as well as contact information for the President and other survey contacts.

The survey is very brief and should not take more than a few minutes to complete. SQL queries using DM_Census to produce the enrollment numbers are saved to the Google Drive.

US News Best CollegesOpens: Early April Closes: Early JuneLevel: High PriorityCDS: AcceptedWebsite: http://usnews.com

Out of all of the reports that are not technically required, this is certainly the most important. We have been ranked every year since 2011 (released in the Fall of 2010). Since then, our score has

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fluctuated, and our ranking has gone from 53rd in 2011 to 92nd in 2019, with a high of 36th in 2014.

A large portion of the survey can be completed by submitting the Common Data Set, although you must make sure that the US News staff uploads the data. In 2012, our CDS data was never uploaded, and it very likely contributed to a slight drop in the 2013 rankings. In 2015, we had some issues with data disappearing from their system after it had been uploaded. To ensure full accuracy with the CDS data, it can also be entered by hand into their online submission system using their CDS data point guide.

The data collection actually consists of three surveys: the Main Statistical Survey, the Finance Survey, and the Financial Aid Survey. In all of these surveys, fields that match a CDS question are marked with that question (e.g. CDS A1).

The Main Statistical Survey requests a number of items from the CDS: Enrollment, six-year cohort data, admission data, etc. Some items not on the CDS are: Income-based Graduation Rates, which asks for cohort data broken down by recipients of Pell Grants, Stafford Loans, or neither; specific admission policies; undergraduate alumni giving; faculty salary outlays (from AAUP Faculty Compensation Survey); majors and minors offered (by CIP code); extra- and co-curricular programs; study abroad countries; student papers; athletics; honors societies; clubs and organizations; Campus events; religious affiliations; overlap schools; international applicants; graduate career data; environment and transportation information; and social media links.

The Finance Survey is rather simple; it asks for data from the IPEDS Finance Survey, referencing the location of each figure requested.

The Financial Aid Survey asks for several CDS items such as annual expenses (i.e. cost of attendance), financial aid awards, and indebtedness. The only item that does not come from the CDS is Pell Grant data.

US News Best Online ProgramsOpens: Mid-August Closes: Late SeptemberLevel: Medium PriorityCDS: Not ApplicableWebsite: http://usnews.com

This survey focuses on programs that we offer online. The survey asks for: background information on our bachelor’s online offerings, admissions, tuition, course delivery, faculty, retention and graduation, and career outcomes data.

In previous years, this survey has been completed by our office, Unrestricted Education, Deans, and a combination at times. As of the 2019-2020 reporting cycle, the surveys were fully delegated to campus stakeholders to complete at their discretion. This survey contains the

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following sections: Online Bachelor’s, Online Master’s Education, Online Master’s Criminal Justice, Online Master’s Business, Online MBA.

US News Best Graduate ProgramsOpens: Early November Closes: Early DecemberLevel: Low PriorityCDS: Not ApplicableWebsite: http://usnews.com

This survey asks for information on our graduate programs. The survey asks for information on program background, admissions, tuition, course delivery, faculty, retention and graduation, and career outcomes.

In recent years, this survey has not been completed by our office due to the complexity of the data, the extreme amount of time to produce the data, and other higher priority reporting duties. This survey can be delegated to other stakeholders on campus as we see fit.

UCAN UpdateOpens: Early December Closes: Early MarchLevel: High PriorityCDS: Partially AlignedWebsite: http://members.ucan-network.org/seuniversity

Completing this survey updates our online profile on the UCAN website (link above) to reflect basic enrollment, retention, tuition, financial aid, campus life, and faculty data. In a way, it is a visual representation of the main data points from our yearly Fact Book. It is moderately time consuming as the survey contains a larger set of questions to answer. Portions of this rely on the IPEDS Winter submission being completed. The short due date time-frame between IPEDS Winter and UCAN can be more stressful to complete if there is a delay in IPEDS Winter submission. This survey also relies on data from our most recent Fact Book, CDS, and some SQL queries.

Wintergreen Orchard HouseOpens: Early February Closes: Early MarchLevel: Low PriorityCDS: Accepted

The Wintergreen Orchard House survey collects a number of items aimed at creating a profile for undergraduate students to learn about the school, similar to Peterson’s, US News, College Board, and others. They request general school information, admissions requirements and policies, freshman and transfer admissions and enrollment data, student body demographics, programs and services for learning disabled students, cost of attendance, financial aid, academic programs,

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student services and activities, and other items. The CDS can be submitted by email. Other data items can then be entered. Some more difficult items can be skipped; this survey is not valuable enough to spend an extensive amount of time completing.

However, this survey was bought out by Peterson’s in April 2020. In the press release, it is mentioned that Peterson’s will assume the annual undergraduate data collection, which will now be performed and delivered exclusively by Peterson’s beginning with the fall 2020 survey.

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Appendix A: Census Data

Column Name Description Data TypeDMCID Prime key varchar(25)

YrCde Academic Year char(4)

TrmCde Term Code char(2)

Semester Academic Semester varchar(10)

DivCde Code assigned to division level char(2)

ID_NUM Student ID Number int

HrsErld Sum of Hours Enrolled numeric(5, 2)

NumOfCrs Number of Courses Enrolled int

FTPT Full Time/Part Time char(2)

YrInSchool Year in School varchar(20)

LocCde Location Code char(5)

LocationDesc Location Description varchar(45)

LocTypeCde Location Type Code char(2)

LocationType Location Type varchar(35)

AdmDeliveryCde Admissions Delivery Code char(3)

AdmissionsProgCde Admissions Program Code char(5)

CandidacyType Candidacy Type char(1)

Cohort Academic Cohort char(5)

Cluster Cluster varchar(15)

TermEntryType Term Entry Type varchar(50)

NewReturning New or Returning varchar(15)

TuitionCde Tuition Code char(2)

TuitionLevel Tuition Level char(2)

DegrCde Degree Code char(5)

DegreeLevel Degree Level varchar(21)

Major1 Major 1 char(5)

Major2 Major 2 char(5)

Major3 Major 3 char(5)

Major4 Major 4 char(5)

Minor1 Minor 1 char(5)

Minor2 Minor 2 char(5)

DM_Census table -- Fields Returned:

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Column Name Description Data TypeMinor3 Minor 3 char(5)

Certification1 Certification 1 char(5)

Certification2 Certification 2 char(5)

Active Active (Y/N) char(1)

CurDegree Current Degree char(1)

NonDegSeeking Non Degree Seeking char(1)

DegreeLevelSort Degree Level Sort char(2)

DivisionSort Division Sort char(2)

LocationTypeSort Location Type Sort char(2)

RecordType Record Type varchar(15)

CensusDate Census Date date

CensusYr Census Year char(4)

CensusSemester Census Semester varchar(10)

DM_Census table -- Fields Returned (Continued):

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DM_CensusDemographics -- Fields Returned:

Column Name Description Data TypeDMCID Prime key varchar(25)

YrCde Academic Year char(4)

TrmCde Term Code char(2)

Semester Academic Semester varchar(10)

DivCde Code assigned to division level char(2)

ID_NUM Student ID Number int

Gender_Cde Gender Code (F/M) char(2)

Gender Gender char(7)

Ethnicity Ethnicity varchar(255)

DOB Date of Birth date

Age Age int

FirstGeneration First Generation (Y) char(1)

MKPK Missionary Kid/Pastor's Kid (Y) char(1)

ActiveDuty Active Duty varchar(1)

Veteran Veteran varchar(1)

Military Military varchar(1)

MilitaryStatus Military Status char(1)

CitizenshipStatusCde Citizenship Status Code char(1)

CitizenshipStatus Citizenship Status varchar(20)

CitizenOfCde Citizen of Code varchar(3)

CitizenshipCountry Citizenship Country char(60)

ReligionCde Religion Code varchar(4)

Religion Religion char(60)

AGDistrict Assemblies of God District varchar(60)

DomniCity Domni City (Origin) char(25)

DomniStateCde Domni State Code (Origin) char(2)

DomniState Domni State (Origin) varchar(75)

DomniZip Domni Zip Code (Origin) char(12)

DomniCountry Domni Country (Origin) varchar(75)

RecordType Record Type varchar(15)

CensusDate Census Date date

CensusYr Census Year char(4)

CensusSemester Census Semester varchar(10)

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DM_CensusStudentLife -- Fields Returned:

Column Name Description Data TypeDMCID Prime key varchar(25)

YrCde Academic Year char(4)

TrmCde Term Code char(2)

Semester Academic Semester varchar(10)

DivCde Code assigned to division level char(2)

ID_NUM Student ID Number int

ResidentCommuter Resident or Commuter varchar(45)

BldgCde Building Code char(5)

Building Building varchar(45)

Athlete Athlete char(1)

RecordType Record Type varchar(15)

CensusDate Census Date date

CensusYr Census Year char(4)

CensusSemester Census Semester varchar(10)

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Appendix B: Essential Institutional Research Software

SQLSQL (Structured Query Language) is a programming language used primarily for the management of data stored in a relational database management system. It is the primary data query coding language of the institutional researcher, especially at SEU, where the majority of our institutional data is stored in relational databases, like those found in the seu-bi or Jenzabar servers. Most IR professionals at SEU employ the Microsoft SQL Server Management System (SSMS) environment for designing queries and views, stored procedures, and other data-based solutions and projects. SQL is also a foundational language behind the majority of our business intelligence programming. A recommended supplement to the SSMS environment is the suite of SQL enhancement tools offered through Redgate software, specifically SQL Prompt, which fills in SQL script with predictive and suggested text. This will save the code writer a great deal of time and contribute to uniform, standardized expressions in the code.

Learning resources: https://www.w3schools.com/sql/; https://www.datacamp.com/courses/introduction-to-sql; Stephens, R. K., Jones, A., &amp; Plew, R. R. (2015). Sams teach yourself SQL: In 24 hours. Indianapolis, IN: Pearson Education.

SPSSSPSS Statistics is a software package used for interactive, or batched, statistical analysis. Long produced by SPSS Inc., it was acquired by IBM in 2009. The current versions are named IBM SPSS Statistics.

SPSS has a limited history of usage at SEU to date, but in recent years it has been utilized in a partnership between Research & Strategic Projects and the institutional methodologist to produce predictive analytics models of retention, persistence, graduation (RPG) and other student success-related metrics. An institutional license is available for SPSS users.

Learning resources: https://www.spss-tutorials.com/basics/; https://www.ibm.com/services/learning/course/

PythonPython is an interpreted, high-level, general-purpose programming language. Created by Guido van Rossum and first released in 1991, Python’s design philosophy emphasizes code readability with its notable use of significant whitespace.

Although it is increasingly popular for web development, some of its most useful applications lie in the advancement of analytics, hence its utility for the institutional researcher.

Learning resources: python.org; https://www.datacamp.com/courses/intro-to-python-for-data-science; https://brochure.getpython.info/

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RR is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R.R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes

• an effective data handling and storage facility,• a suite of operators for calculations on arrays, in particular matrices,• a large, coherent, integrated collection of intermediate tools for data

analysis,• graphical facilities for data analysis and display either on-screen or on

hardcopy, and• a well-developed, simple and effective programming language which

includes conditionals, loops, user-defined recursive functions and input and output facilities.

Learning resources: https://www.r-project.org/; https://www.datacamp.com/courses/free-introduction-to-r

Power BIPower BI is a business analytics service by Microsoft. It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards.

It has become one of the go-to services for analytics at SEU because of its relatively simple use, ability to connect dynamically to a significant range of data sources, and the powerful, clean UI it offers business users. The institutional researcher may find Power BI to be an attractive option for a variety of reporting and dashboard solutions, but it is important to first determine whether a more traditional reporting format, like Excel, or another platform, like InfoMaker, is more appropriate for a given project. Reports are designed in Power BI Desktop, which can be downloaded for free from Microsoft’s website. Data is imported either through a static dataset like an Excel workbook or a dynamic connection like SQL Server. Data modeling and cleaning are integral prerequisite steps before any significant visualizations are added to a report. The Power BI report designer should always consider the implicit or explicit stakeholder and/or solution requirements associated with the report under construction. Typically, a variety of filters will accompany a set of visualizations to allow for slicing and disaggregation of the data. Additionally, some reports require the use of row-level security via the introduction of roles within the role management section of Power BI Desktop. Once a report is ready for publication, it should be published to the appropriate Workspace in Power BI web service.

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After a report has been published to service, it should be reviewed for functionality and design specifications. Setting up a data refresh schedule is usually advisable for reports that import data from the seu-bi server gateway. Reports can be refreshed up to 8 times per day. After the refresh schedule has been applied, the report should be shared with the appropriate group of stakeholders. One should keep in mind that if row-level security has been added to a report, the report author will need to add users to roles in the Security section of the report’s dataset. This can be done inside of web service.

Learning resources: MS Dashboard in a Day (DIAD), Power BI Guided Learning, YouTube (Guy In A Cube), AIR pre-conference workshops

InfoMakerInfoMaker is a product that integrates and connects directly to Jenzabar, assisting to create a user interface for reports and data pulling that all staff on campus have access to.

Although InfoMaker is not used as much as it previously was, there is still a great deal that InfoMaker can do to assist the IR and IE offices. Creating reports in InfoMaker can allow an end user access and the ability to run a report at their leisure. This can allow IR and IE staff to delegate frequently needed data to the end user by creating a report that meets their needs, giving them access, and showing them how the report functions.

Reports can be created in SSMS using SQL for those that are more familiar with this language, and then placed into InfoMaker as syntax, as opposed to using the front end user drag-and-connect feature that is built into InfoMaker.

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All reports are saved to the Z: Drive under “Additional Reports.” From there, they are separated into many different folders based on departments (ie. AV for Advising, AD for Admission, RE for Registrar, etc.) Reports created by the IR and IE offices are saved into a “Data Requests” folder inside each departmental folder.

It is best practice to give the report a name in the top left corner, with a description below for more context to the end user. You can also add features such as page numbers, counts, etc. to the top right of the report. These features and others can be found on the top menu under Insert, Control. Note that some features require you to click on a data point in the “Detail” ribbon before using the Insert menu.

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Almost all reports for our campus should be created in Landscape, allowing for more data points to be shown on the report. Make sure that when in the design mode, you create a report that is fully viewable and functional to the end user by moving around data points and data labels.

There are many learning resources to help someone get started using InfoMaker. More detailed instructions on how our campus typically creates, stores, and uses these reports can be requested of the IE office or the Assistant Registrar. Detailed step-by-step instructions on how to create InfoMaker reports from scratch can be found at the below learning resource.

Learning resources: http://infocenter.sybase.com/help/index.jsp?topic=/com.sybase.infocenter.dc37788.1250/html/imgs/CCJBDCHG.htm

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Appendix C: Suggested Resources

Books & Published Research:

Baer, L. L., & Carmean, C. (2019). An Analytics Handbook: Moving From Evidence To Impact. Society for College and University Planning. doi:scup.org

Hossler, D., Bontrager, B., & Tom, L. (2015). Handbook of strategic enrollment management (Ser. Jossey-bass higher and adult education series). Jossey-Bass.

Howard, R. D., McLaughlin, G. W., & Knight, W. E. (2012). The Handbook of Institutional Research. San Francisco, CA: Jossey-Bass, a Wiley imprint.

Knight, W. E. (2003). The Primer for Institutional Research. Tallahassee, FL: Association for Institutional Research.

Leimer, C. (Ed.). (2009). Imagining the Future of Institutional Research. San Francisco, CA: Jossey-Bass.

Paulsen, M. B. (Ed.). (2016). Higher education: Handbook of theory and research. Dordrecht: Springer.

Swing, R. L., Jones, D., and Ross, L. E. (2016). The AIR National Survey of Institutional Research Offic-es. Association for Institutional Research, Tallahassee, Florida.

Tinto, V. (2012). Completing college : rethinking institutional action. University of Chicago Press.

Toutkoushian, R. K., & Paulsen, M. B. (2007). Applying economics to institutional research (Ser. New directions for institutional research, no. 132). Jossey-Bass.

Webber, K. L. (Ed.). (2018). Building Capacity in Institutional Research and Decision Support in Higher Education. Springer.

Organizations & Websites:

Association for Institutional Research (AIR) - airweb.org

Florida Association for Institutional Research (FAIR) - florida-air.org

The Integrated Postsecondary Education Data System (IPEDS) - https://nces.ed.gov/ipeds

Southern Association of Colleges and School Commission on Colleges (SACSCOC) - sacscoc.org

Southern Association for Institutional Research (SAIR) - sair.org

Society for College and University Planning (SCUP) - scup.org

Notes

Notes

Notes

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Southeastern University

Office of Institutional Effectiveness1000 Longfellow Blvd., Lakeland, FL 33801

Phone: 863.667.5703 Fax: 863.667.5200