Saturday workshop: Level-Up with Monthly Check-Ins

Level-Up with Monthly Check-Ins: A Lightweight Monitoring Loop for Continuous Program Improvement

with Qian Wang, PhD Student, and Adriana Cimetta, PhD, MPH, from Educational Psychology, College of Education, The University of Arizona

This session introduces a practical, low-burden approach for bridging monitoring and evaluation through streamlined Monthly Check-Ins. Drawing from Project CAN, a statewide initiative addressing digital inequities in rural and low-income Arizona communities. This session illustrates how a lightweight monitoring loop can replace complex project-management systems while still producing timely, actionable data for continuous improvement.

Project CAN partners work across diverse contexts to expand broadband access, strengthen remote learning supports, and deliver digital literacy and workforce development opportunities tailored to local needs. Early attempts to use a commercial project-management platform proved too time-consuming for partners, resulting in low adoption and inconsistent data. In response, the evaluation team developed a more accessible Monthly Check-In process that aligns with partners’ workflows and capacity while maintaining strong accountability and engagement.

The Monthly Check-In model uses short Qualtrics prompts or brief semi-structured conversations to capture five key areas: activities completed, plans for the next period, challenges, needed supports, and evaluation needs. The evaluation team synthesizes this information into ongoing feedback for partners and integrates findings into quarterly and annual reports, creating a real-time improvement loop that supports swift adjustments, strengthens relationships, and enhances data quality across a large, multi-site initiative.

This session will share insights from implementing this model, including how a low-burden system can sustain partner engagement, improve monitoring efficiency, and balance autonomy with accountability. Participants will leave with adaptable templates, design considerations, and strategies for implementing similar light-touch monitoring systems in their own evaluation contexts, particularly when working with distributed or capacity-strained partners.