Introduction
The Benchmark Recreation Service Assessment at Southern Illinois University Edwardsville was designed to examine how students perceived campus recreation programs, facilities, staff, cleanliness, equipment, participation opportunities, and possible influence on enrollment or continuation of healthy activity. My role included reviewing responses, organizing information, and learning how survey evidence can guide decisions. The original reflection recognizes the value of teamwork and mentorship but assumes that an online questionnaire automatically produced valid information and that favorable comparison with peers proved success. A stronger assessment must examine purpose, sampling, response bias, confidentiality, question design, analysis, benchmarking, and how findings are converted into action. (Bresciani, Zelna, & Anderson, 2004)
Campus recreation is not only a collection of exercise rooms. Current professional standards describe collegiate recreation as supporting physical, social, educational, and developmental needs. Assessment should therefore measure both service quality and student outcomes without claiming that participation alone causes academic success or retention. (Council for the Advancement of Standards in Higher Education, 2024)
Purpose of the Assessment
The first purpose was service improvement. Administrators needed evidence about facility condition, staff interaction, program relevance, equipment, locker rooms, communication, and barriers to participation. A second purpose was benchmarking—comparing selected indicators with peer or national recreation departments. A third purpose was educational: participation in the project allowed me to practice survey administration, data analysis, teamwork, and communication.
These purposes should be separated because they require different measures. Satisfaction questions cannot by themselves show learning, health change, or influence on enrollment. A student may be satisfied with a clean facility but use it rarely. Another may value a program while remaining dissatisfied with crowded hours.
Defining the Audience
The primary audience was students, but “students” are not one homogeneous group. Undergraduates, graduate students, commuters, residents, international students, students with disabilities, varsity athletes, nonusers, and students with jobs may experience recreation differently. Staff and institutional leaders are secondary audiences because they use the results for planning and accountability.
An assessment that reaches only frequent users is likely to overstate satisfaction and miss the reasons others do not participate. Nonusers are especially important when the objective is access. The sampling plan should identify who was invited, how invitations were distributed, and which groups responded.
Survey Design
A good questionnaire begins with a map linking each question to a decision. If leaders cannot explain how an answer will be used, the question may not justify the respondent’s time. Items should use clear language, one idea at a time, and response options that cover realistic experiences.
Questions such as “How clean and welcoming is the locker room?” combine two judgments and should be separated. Satisfaction scales need consistent direction, and “not applicable” should be available when a respondent has not used a service. Open-ended questions can reveal issues that fixed categories miss, but they require a transparent coding method.
Demographic Questions
The original assessment asked about gender, ethnicity, race, sexual orientation, residence, previous institution, academic level, work hours, study hours, and grade-point average. These variables can reveal inequities, but they also create privacy risk. The survey should collect only information needed for analysis and explain why it is requested.
Small groups should not be reported in ways that allow identification. Inclusive response options and voluntary nonresponse are important. Sensitive questions should generally appear after core service questions, and data access should be restricted.
Online Data Collection
Online questionnaires are efficient and allow automated data capture, but they do not guarantee representative evidence. Students with strong opinions may be more likely to respond. Email fatigue, inaccessible design, mobile formatting, and distrust can reduce participation.
The project should record the invitation method, number invited, response rate, reminder schedule, and collection period. Accessibility testing, plain language, and compatibility with assistive technology are part of quality. Incentives, if used, should be modest and not linked to particular answers.
Sampling and Response Bias
A census invitation sent to all students can still produce a biased respondent sample. The team should compare respondents with the eligible student population on available characteristics such as class level or residence. Weighting may help in some circumstances, but it cannot correct every difference.
If only recreation-center users received the survey, conclusions must be limited to users. Statements about the whole campus would not be justified. Clear limits make an assessment more credible, not less valuable.
Reliability and Validity
Reliability concerns consistency. A group of items intended to measure staff service should produce a coherent pattern, and ambiguous items reduce reliability. Validity asks whether the instrument actually measures the intended concept. A question about satisfaction does not necessarily measure health, belonging, or learning.
Pilot testing with a small group can identify confusing language, missing options, and excessive length. Cognitive interviewing—asking students how they interpreted questions—can reveal meanings the survey designer did not anticipate.
Benchmarking
Benchmarking compares an institution with peers or a national dataset. NIRSA maintains benchmarking and institutional data resources for collegiate recreation. Comparison can show whether facility size, participation, staffing, or services differ from similar institutions. (NIRSA, n.d.)
A benchmark is not automatically a target. Institutions vary in enrollment, climate, budget, commuter population, facility age, and mission. A lower participation rate may reflect barriers, but it may also reflect differences in what is counted. Definitions and denominators must be aligned before comparison.
Analysis of Quantitative Data
Quantitative analysis should begin with data cleaning: checking duplicates, missing values, impossible responses, and inconsistent coding. Descriptive statistics can summarize distributions, not merely averages. A mean satisfaction score may conceal a polarized group.
Group comparisons should be planned and interpreted cautiously. Many tests increase the chance of finding a difference by accident. Statistical significance does not establish practical importance, and small samples may make estimates unstable. Confidence intervals and effect sizes can improve interpretation.
Analysis of Open-Ended Responses
Comments provide context about equipment, schedules, staff behavior, accessibility, and desired programs. The team should develop coding categories, review a sample together, and document how disagreements were resolved. Quoted comments must be de-identified.
The loudest comment should not become the entire conclusion. Themes should be considered alongside frequency, severity, feasibility, and other evidence. A rare safety concern may deserve urgent action even if it is not a common theme.
Learning and Development Outcomes
CAS standards require student-affairs programs to define and assess learning and development outcomes. Recreation programs may contribute to collaboration, leadership, wellbeing knowledge, self-management, and belonging. These outcomes require direct or well-designed indirect measures rather than assumptions. (Council for the Advancement of Standards in Higher Education, 2024)
For example, a leadership program could assess participants’ ability to plan an event, manage conflict, or apply safety procedures. Facility attendance alone does not demonstrate that learning occurred.
Relationship to Retention and Recruitment
The assessment asked whether recreation programs influenced students to attend SIUE or continue healthy pursuits. Self-reported influence is useful perception data, but it does not prove that recreation caused enrollment or retention. Students choose institutions for many reasons.
Stronger evaluation might combine survey data with participation records and institutional outcomes under appropriate privacy controls. Even then, selection bias remains because students who use recreation may differ before participation. Findings should use language such as association or reported influence rather than causal proof.
Role of the Advisor and Team
My advisor, Paula Lenhardt, contributed methodological guidance, data processing, report preparation, and quality control. The project showed that assessment is collaborative. Subject experts define meaningful questions, information-technology staff support systems, analysts interpret data, and program staff understand operations.
Mentorship was particularly valuable when choosing methods and translating numbers into conclusions. A student analyst should be encouraged to question assumptions rather than simply produce attractive graphs.
My Learning
I developed practical skills in organizing responses, checking data, comparing groups, interpreting charts, and communicating results. I also learned that analysis takes more time than expected. Cleaning and documenting data can be more demanding than calculating statistics.
The most important lesson was that a survey is not a neutral machine. Every choice—who is invited, how a question is written, which categories are reported, and what is omitted—shapes the result. Good assessment requires humility about what the data can support. (Bresciani, Zelna, & Anderson, 2004)
Using the Results
Results should lead to a prioritized action plan. Each action needs an owner, resources, a deadline, and a measure of completion. Examples might include revising hours, improving equipment maintenance, addressing cleanliness, redesigning communication, expanding inclusive programming, or studying an identified barrier.
Administrators should also tell students what changed. A “you said, we did, and we are still studying” summary demonstrates that participation mattered. Not every request can be fulfilled, but reasons can be explained.
Limitations
The likely limitations include voluntary response, uncertain representation, self-report error, cross-sectional data, and possible ambiguity in questions. The original reflection does not provide enough information about response rate or sampling to claim that results represented all students.
Benchmark comparisons may also be limited by different definitions. These constraints should appear in the final report so decision-makers do not treat precise numbers as stronger than the design allows.
Recommendations for Future Assessments
Future work should use a concise survey linked to decisions, include nonusers, test accessibility, report response patterns, and combine survey findings with operational evidence such as facility counts, program registration, maintenance records, and complaints. Focus groups or interviews can explore barriers identified quantitatively.
Assessment should be continuous but not burdensome. Existing institutional and NIRSA data can reduce repeated requests. A scheduled cycle can alternate broad program review with smaller targeted studies. (NIRSA, n.d.)
Conclusion
The Benchmark Recreation Service Assessment provided valuable experience in data collection, analysis, teamwork, and institutional decision-making. Its central purpose was not to produce favorable graphs but to understand how students experience recreation services and where improvement is needed. Online surveys offer reach and efficiency, yet their findings depend on sampling, design, privacy, response patterns, and appropriate interpretation.
Benchmarking can place local results in context, while CAS and NIRSA resources help connect facilities and programs with student development and professional standards. The project taught me that valid assessment requires more than technical calculation. It requires clear questions, ethical data practices, honest limitations, and a visible process for turning evidence into action. (Council for the Advancement of Standards in Higher Education, 2024; NIRSA, n.d.)
References
Council for the Advancement of Standards in Higher Education. (2024). Collegiate Recreation Programs Standards.
NIRSA. Research, Assessment, and Institutional Data Set Resources.
Bresciani, M. J., Zelna, C. L., & Anderson, J. A. (2004). Assessing Student Learning and Development. NASPA.
Portwood, S., et al. (2017). Minutes of the Special Meeting of the Board of Trustees, Southern Illinois University.
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