Many academic departments now engage in annual cycles of assessment of student learning as well as departmental services. Best practices in higher education, reinforced by regional accrediting bodies, among others, dictate that only when departments assess student achievement and departmental initiatives, integrate those assessments meaningfully, and link them to resource allocation (as applicable) can they truly move down a path of continuous improvement. Yet can those assessments alone, important as they are, answer all the questions that departmental faculty and administrators pose about students, faculty, resources, and services? As a supplement to those assessment data, a set of pre-established, mission-centered metrics provides a barometer of the department’s health and vitality while informing timely decision making in a rapidly changing environment both inside and outside academia.

In “Getting SMART with Assessment: ACTION Steps to Institutional Effectiveness” (Assessment Update, 24: 1), Sandra Jordan and I briefly mention this supplementary data as one of three components of a fully integrated annual program review, which we define as an annual cycle of institutional effectiveness that combines the assessment of student learning with the assessment of departmental operations and often includes other departmental data. Whereas that article primarily explores strategies for promoting, clarifying, and supporting effective assessment strategies, in this article I discuss an annual departmental data review—its process, advantages, and management—as a separate component of institutional effectiveness. Used effectively, an annual departmental data review ultimately intersects with and supports other planning and assessment documents to advance departmental decisions.

What is an annual departmental data review?

An annual departmental data review, conducted by the academic department with the assistance of the university’s Institutional Research office, is the collection, review, and use of data about the department’s students, faculty, programs, and operations. Depending on current priorities (institutional, divisional, college, and departmental), data points may vary but could include the following examples:

  • student retention rates in the department’s majors,
  • alumni employment rates,
  • number of faculty grant submissions,
  • student credit-hour production, and
  • student participation rates in departmental programs.

The departmental data review entails as many as five annual steps:

  • a collection of data provided by Institutional Research or by the department (depending on the data source);
  • a review of the data by the entire department;
  • a written response to the data about future decisions, initiatives, and interventions to improve departmental services, programs, and outcomes;
  • a review by the dean, provost, and other academic leaders with attention to cross department, cross college, and even cross division synergies, opportunities, and challenges and with consideration of enhanced support (human, financial, technological, and so forth) as needed; and
  • an archive of data reviews for that year and across time.

What are the advantages of an annual departmental data review?

An annual data review has four interrelated advantages:

  • An annual data review allows the department to respond quickly to changing environmental conditions. Space does not permit a thorough discussion of all the fast-paced changes that universities face. Changes in technology, accreditation, accountability, federal regulations, state support, and student demographics (to name just a few) pose challenges at every turn. In response to these challenges, departments need a repository of metrics, indicators, and other data. Based on careful review of those data, departments can make timely decisions and interventions. For example, a history department reviews disappointing data on student retention from the second to third years in the major and, in response, plans to implement enhanced advisement practices.
  • An annual data review permits the department to monitor data over time. Admittedly, one year’s data are often not enough to justify a new initiative or to ascertain a current initiative’s effectiveness. However, an annual data review displays a trend in the making. For instance, a sudden increase in credit-hour production in the accounting program may justify hiring additional adjuncts in the short term, but, over time, steady increases in credit-hour production may support a formal request for a full-time faculty member.
  • An annual data review integrates with planning and assessment documents. Departmental data can join assessment data to create a fuller picture of the department, its programs, and its students. For example, biology students’ low participation rates in study abroad programs (as indicated in the data review) coupled with biology students’ lackluster achievement of global learning outcomes (as recorded in the report on the assessment of student learning) may inspire a collaborative project between the biology faculty and the study abroad office to promote students’ global awareness. This initiative might contribute to strategic plans to increase study abroad rates at the institution overall.
  • An annual data review serves as a vehicle for regular departmental conversations. One of the best uses of departmental data is to hold departmental meetings with faculty. Sharing and discussing these data can inform faculty, reduce misperceptions about student demographics and achievement, and clarify the mission and vision for the department. In addition, reviewing these data can promote creative solutions to improve departmental practices, student success, and faculty experiences.

How can an annual departmental data review be effective without becoming burdensome?

Departmental faculty and administrators are inundated with so many requests and duties that the thought of another report can be daunting. Three basic principles can alleviate the perceived burden of a data review: 

  • Limit the data. Departments should review only data that align with planning priorities—at the departmental, college, divisional, and/or institutional levels—and any other data that the department truly needs to inform its decisions.
  • Provide the data. An office such as Institutional Research should collect as much of the institutional data as possible and provide them in a standardized format, such as a dashboard or a series of graphs and charts, to reduce departmental workload.
  • Incorporate the data review into routine departmental business. A new report will not seem extraneous if it becomes part of the annual institutional effectiveness cycle (mentioned above) and part of regular departmental meetings and retreats.

The 21st-century university cannot escape the need to make data-informed decisions—and the urgency to make those decisions rapidly. An annual departmental data review should be integrated into a comprehensive institutional effectiveness program. Those data, if reviewed annually and used effectively, can advance departmental decision making.        

Eric Daffron serves as vice provost for curriculum and assessment at Ramapo College of New Jersey. Prior to that position, he served as administrator and faculty member at Mississippi University for Women.

Reprinted from Academic Leader, 32.10 (2016): 2, 8. © Magna Publications. All rights reserved.