Evaluation Services
In addition to education policy research, CEEP offers educational evaluation services, with expertise in various evaluation designs and methods that are suitable for an array of evaluation needs. CEEP’s evaluation wing is well suited to conduct rigorous, non-partisan, and high-quality evaluations for a range of actors and purposes. Following are some of the evaluation services available at CEEP:
- Development of evaluation plans, program theory, and/or logic models for program, policy, and/or practices.
- Summative, impact, and third-party evaluations of programs, policy, and/or practices.
- Formative evaluations geared towards supporting implementation teams in improving programs, policies, and practices.
- Evaluation capacity building workshops and trainings to develop internal evaluation capacities and capabilities.
For more information, please reach out at soeceep@iu.edu.
Current Projects
Internal University of Indiana School of Education small scale evaluation of the summer engagement experience for high school students.
The Full-Service Community Schools (FSCS) grants cater to supporting interventions that improve the coordination, integration, accessibility and effectiveness of services for children attending high-poverty schools, particularly high-poverty rural schools. This grant supports the implementation of the City Connects program in two Title 1A eligible schools in Jasonville, Indiana and seven community schools and two 21st Century Charter schools in Gary, Indiana. Each grant runs for five years, with the Jasonville evaluation starting in 2022 and the Gary evaluation starting in 2023. The City Connects intervention is designed and developed by Boston College and they are the key collaborators supporting the implementation of the intervention through Marian University’s Center for Vibrant Schools and the Shakamak School Corporation. Marian University has contracted the Center for Evaluation and Education Policy (CEEP) as an external evaluator to fulfill the requirement for the federal FSCS grant. Following a Results Based Accountability (RBA) approach, the purpose of this evaluation is two-pronged. The first is to gauge the program's efficacy and provide insights that can be used for continuous improvement of the program on an ongoing basis during program implementation. The second is to conduct an annual evaluation after each intervention cycle to provide insights for the proceeding intervention cycle.
The Excel Center (TEC) Noblesville is a small school among 19 TEC schools across Central and Southern Indiana. TECs are tuition-free public charter high schools for adults that offer an Indiana state-recognized diploma (Core 40, General). The program enables earning dual credits or an industry-recognized work certification. TEC Noblesville has an enrolment of 195 students, 72% of who are multilingual students. CEEP provides an external evaluation of TEC Noblesville’s education interventions to help identify areas of growth to support multilingual learners through the diploma-earning program, provide feedback on the life coaching model of TEC and on development and alignment of the courses for multilingual learners and recommend ways of growing by building community-based partnerships.
Past Projects
Professional Learning Communities (PLCs) rose to prominence in the 1990s to support and empower educators. Solution Tree’s PLC at Work model, which seeks to “empower educators to work collaboratively in recurring cycles of collective inquiry and action research to achieve better results for the students they serve,” systematizes collective staff development through continuous improvement cycles, an approach originally developed in management consultancy. This development process encompasses goal and standard setting, refinement of instructional skills, and other collaborative practices. These structured collaborative activities are designed to produce significant long-term outcomes, including increased student academic achievement, higher student engagement in learning, improved teacher retention, and the development of schoolwide collective responsibility for learning outcomes. Our evaluation focuses on improved academic achievement and teacher retention.
The evaluation used publicly available data from the Indiana Department of Education (IDOE) between 2014 and 2024 and deployed k-nearest-neighbor or k-NN, a machine learning matching algorithm to identify comparable schools. Program effectiveness was evaluated using difference-in-difference regression analysis.