Achieving Optimal Enrollment in an Online IDT Master's Program Using Performance Improvement

Shari Danielle Cruz

In this action research study, I focused on using performance improvement (PI) to address a performance problem at an online instructional design and performance technology (IDPT) master’s degree program in an instructional design technology (IDT) department at a public university. The problem was that enrollment in the program had been below expectations for several years. To address this problem, I used the International Society for Performance Improvement’s PI/human performance technology (HPT) model (Van Tiem et al., 2012) as the guiding framework. This model included conducting five PI phases: (a) performance analysis (PA), including organizational analysis (OA), environmental analysis (EA), gap analysis (GA), and cause analysis (CA); (b) intervention selection, design, and development; (c) intervention implementation and maintenance; (d) evaluation; and (e) change management. During PA, the OA informed optimal performance and the alignment of the focal program’s vision, mission, values, goals, and critical business needs, but the EA informed actual performance. I collected extant data as sources for both OA and EA insights and elicited data via interviews with department faculty, administration, and supporting staff and via a questionnaire to students. I analyzed OA and EA data simultaneously via coding. I manually assigned structural and descriptive codes to the data during first cycle coding and created a codebook. Then, I recoded the data as I transitioned each unit of analysis to a sticky note in Mural’s virtual whiteboard tool. After establishing intercoder agreement, I followed Saldaña’s (2021) codes-to-theory model in second cycle coding, using memos and codes to condense data into categories via pattern coding. Last, I themed the data categorically based on the research questions and synthesized the themes into key insights. PA revealed two key OA insights and six key EA insights. Using Rothwell’s (2005) six-cell GA tool, I identified eight performance gaps, which I reframed as opportunities to take an appreciative inquiry lens aligned with guidance from Cooperrider and Whitney (2005). I facilitated a meeting where the stakeholders prioritized four opportunities based on criticality. Then, I facilitated a second meeting to conduct the CA, where I presented the performance factors leading to the critical opportunities. Using SAM (Marker, 2007), I traced performance factors to their root causes. I reframed those root causes as key opportunities, resulting in the following list: (a) establish succinct communication about the department and program, highlighting the unique strengths and clarifying the focus on adult learning; (b) develop a marketing plan for the program, showcasing all touchpoints with individuals in the enrollment funnel and highlighting where the messaging should be updated and how the outreach could be improved; and (c) generate a list of future recruiting and marketing opportunities and potential return on investment, identifying how they could leverage specific additional resources. I began the intervention selection process by aligning the model used for root cause analysis, SAM (Marker, 2007), with an intervention classification system (Sanders & Thiagarajan, 2005). I selected three interventions based on their ability to address the root causes of the performance opportunities: a strategic messaging report, a student communications flowchart, and a program marketing plan. Then, I designed, developed, and implemented each intervention based on evidence-based practices and established frameworks and tools. I relied heavily on efficient stakeholder collaboration to ensure sustainability (Dublin, 2007). In the strategic messaging report, I presented branded statements and key terms to describe the department’s and program’s unique qualities and strengths. In the report, I presented a marketing framework identifying the most influential factors for students selecting a higher education program based on the marketing P frameworks established by similar studies (Ivy, 2008; Kania, 2024; Marsden, 2019; Stack, 2009). I used the following factors to guide the report’s design: program/product, program quality/prominence, prospectus, personal performance, place, price, and people. The student communications flowchart was an editable flowchart that visualized the touchpoints for communications with potential students in the program’s enrollment funnel, specifying the person or department responsible for each touchpoint. In the program marketing plan, I included a message campaign plan to implement new strategic communications across the flowchart. It was accompanied by a project management tool to carry out the plan. I conducted a formative, summative, and meta evaluation of all three interventions (Dessinger & Moseley, 2006), but due to project time constraints, the stakeholders would carry out the confirmative evaluation. Therefore, I also included a robust confirmative evaluation plan for all three interventions and six supplemental data collection tools. Last, I included a spreadsheet with suggestions for requesting and allocating future resources. Positive results from the summative evaluations (i.e., stakeholder satisfaction and progress toward optimal enrollment) indicated project success. Stakeholders will use the confirmative evaluation to determine if optimal enrollment is reached, with enrollment data reviews occurring every semester. Stakeholders will conduct reviews after 6 and 18 months. This study’s findings have significant implications for the organization and other similar programs, including the sustainability and viability of the program and department.

Achieving Optimal Enrollment in an Online IDT Master's Program Using Performance Improvement

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Achieving Optimal Enrollment in an Online IDT Master's Program Using Performance Improvement

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