CMJ Summer Internship 2026 Potential Projects
Please note that this document is updated weekly through January 15th to reflect additional projects and mentors.
PROJECT 1: As It Should Be: Black Student Academic Excellence in High School (Project Ongoing)
This research-practice partnership investigates the mechanisms behind Black student academic success at Southland College Preparatory Charter High School, a high performing, predominantly Black public charter school in Illinois. Using a mixed methods design, including interviews, focus groups, observations, surveys, and a lottery based natural experiment, the project seeks to understand how school environments and practices contribute to educational excellence. A key feature of the work is the inclusion of Southland students as trained researchers and co-authors, helping to shape the study and share its findings. The goal is to build a replicable, evidence based model for advancing Black student achievement across public high schools.
Skills Sets (in development or mastered)
- Qualitative research experience (design and analysis of interviews, focus groups, observations)
- Survey design, administration, and statistical analysis
- Strong academic writing and communication skills
- Ability to collaborate effectively with community partners and student co-researchers
Mentor: Dr. Darnell Leatherwood
PROJECT 2: Mapping and Exploring Variation in Black Student Academic Outcomes in U.S. Public School Systems (Project Ongoing)
This research project investigates the extent and nature of district-level variation in Black student academic achievement and growth across the United States. In this project we ask: Which districts are most effective for Black students, and under what conditions? Using hierarchical linear modeling and population level test score data from the Stanford Education Data Archive (SEDA), the study will generate empirical Bayes estimates of three key academic outcomes for Black students in grades 3–8 (Note: this work is ongoing and the next phase of analysis includes the analysis of conditional models, prior work focused on unconditional models):
- Academic Achievement: Average district level performance in math and ELA relative to national grade level norms
- Improvement Rate: Average annual academic change across cohort over time
- Learning Rate: Average annual academic growth within cohort over time
In prior work (Leatherwood, 2024), I showed that there is tremendous heterogeneity in district level academic outcomes for Black students nationally. This phase of the project seeks to begin exploring the mechanisms behind this variation.
Skills Sets (in development or mastered)
- Proficiency in statistical software (R, Stata) and multilevel modeling
- Experience managing and analyzing large, complex datasets
- Data visualization for research and policy audiences
- Strong literature review and synthesis skills in educational equity
Mentor: Dr. Darnell Leatherwood
PROJECT 3: Promoting Equity and Research Using Adaptive Testing to Support Individualized Instruction at Scale (Project Ongoing)
This project will build a national collaborative network of researchers, educators, and administrators across K-16 STEM education to develop a Mid-Scale Research Infrastructure (MSRI). This network will use a community-based participatory framework to co-design and implement large-scale, inclusive data collection for research and instructional improvement. As we expand, the LASSO platform will incorporate AI-driven adaptive assessments and diagnostic tools, enabling ethical, personalized, and scalable data collection that supports individualized STEM learning, especially in rural communities.
Skills Sets (in development or mastered)
- Quantitative data analysis (large-scale, multi-level datasets)
- AI and machine learning for adaptive assessment development
- Community-based participatory research methods
- Understanding of ethical data collection and privacy practices
Mentor: Dr. Darnell Leatherwood
PROJECT 4: Data Driven Infrastructure for Advancing Equity: A Systems Level Study of BYMOC Outcomes in Chicago (Project starting in March 2026)
This proposed study investigates how coordinated data infrastructure and capacity building interventions can drive population level change in outcomes for Boys and Young Men of Color (BYMOC) in Chicago. Anchored in the My Brother’s Keeper Alliance (MBKA) initiative, the study examines the implementation and impact of three interrelated strategies:
- MBK Universal/Unified Survey: a quarterly data collection tool capturing organization level data on organizational capacity, activation on MBKA milestones, and organizational needs;
- Brilliance & Excellence (B&E) Certification Program: a five module intervention to strengthen CBO capacity, data usage, and alignment with population level strategies. The program enables the tracking of neighborhood level organizational change across regions of the city;
- ChiOY (Chicago Opportunity Youth) Initiative: a longitudinal case management and intervention model integrating mentoring, wraparound supports, and shared data systems to monitor individual level change in real time.
Using a mixed methods design, the study will evaluate how these tools affect organizational practice, cross sector coordination, and youth outcomes. Quantitative data from surveys and administrative records will be integrated with qualitative data from focus groups, interviews, and implementation logs. Together, these data allow for the analysis of both systematic shifts at the neighborhood level and longitudinal progress at the individual level, ultimately allowing us to potentially say something about population level change for youth in the city of Chicago.
Skills Sets (in development or mastered)
- Expertise in mixed methods research and integration of qualitative and quantitative data
- Survey development and longitudinal data analysis (R, Python, or Stata)
- Experience conducting and analyzing focus groups/interviews
- Strong skills in translating research findings into actionable presentations for diverse stakeholders
Mentor: Dr. Darnell Leatherwood
PROJECT 5: Designing Performance-Based Assessment Tasks for Semiconductor and Microelectronics Engineering
This project focuses on developing performance-based assessment tasks aligned with engineering and related STEM subfields. The work supports needs identified through NSF-funded projects and Purdue collaborations (e.g., nanoHUB, SCALE). The goal is to design tasks that capture engineering problem-solving, teamwork, communication, and applied technical competencies in realistic contexts.
The intern will contribute to:
- Reviewing existing competency frameworks in semiconductor and microelectronics engineering.
- Drafting performance-based scenarios, task prompts, scoring rubrics, and evidence models aligned with ECD principles.
- Developing construct maps, task specifications, and alignment matrices to ensure coherence between competencies, evidence, and task features.
- Assisting with validation planning, including identifying sources of evidence for scoring, fairness, and task comparability across tracks or subfields.
- Preparing short write-ups, figures, or visual design assets that communicate task logic and evidentiary reasoning.
Takeaways:
Students will develop strong applied assessment design skills and gain exposure to cutting-edge STEM workforce initiatives. This work may support co-authored conference presentations (e.g., NCME, NERA, AERA, or engineering education venues) or co-authored papers on performance assessment or competency modeling in STEM.
Skill Sets (in development or mastered):
- Understanding of performance-based assessment and evidence-centered design
- Basic familiarity with STEM or engineering competencies
- Ability to design tasks, rubrics, and validity/evidence arguments
- Visual and technical writing skills for task design
- Skills in technical communication and interdisciplinary collaboration
- Ability to produce diagrams, process models, or visual task elements
- Strong academic writing and synthesis abilities
Mentor: Dr. Maria Elena Oliveri
PROJECT 6: Advancing Sociocognitive and Sociocultural Approaches to Measurement through an Edited Volume on Evidence-Centered Design (Project Ongoing)
This project centers on the development of a scholarly edited book honoring the legacy of Dr. Robert J. Mislevy and advancing sociocognitive and sociocultural approaches to educational measurement. The volume brings together leading scholars across assessment, learning sciences, psychometrics, AI, and STEM education. Chapters address Evidence-Centered Design (ECD), sociocognitive and socioculturally responsive assessment frameworks, fairness and validity models, AI-based assessment innovations, and modern measurement approaches.
The intern will support the writing, organization, and conceptual integration of chapters by:
- Conducting literature reviews on sociocognitive theory, fairness, ECD, validity, and emerging psychometric methods.
- Drafting and editing chapter sections, summaries, and conceptual diagrams.
- Assisting with the editorial workflow, including managing chapter drafts, reviewer feedback, and timelines.
- Supporting the development of repositories of ECD and related resources for wide dissemination
Takeaways:
Interns will gain deep experience in scholarly writing, conceptual synthesis, and book production. There may be opportunities to co-author sections, contribute figures, or participate in conference presentations at venues such as NERA, NCME, or AERA related to ECD, fairness, or sociocognitive assessment.
Skill Sets (in development or mastered):
- Strong academic writing and synthesis skills
- Knowledge of psychometrics, fairness, validity theory, and ECD
- Literature review and conceptual integration
- Organizational and editorial workflow skills
- Ability to create conceptual diagrams or visual models
Mentor: Dr. Maria Elena Oliveri
PROJECT 7: Evaluating Measures
This project features the use of Item Response Theory (IRT) methods to develop and refine a measure of women’s sleep quality, supplementing this work with factor analyses (as needed). The project will also feature the use IRT methods to refine existing measures of cognitive ability among older populations, using an existing large-scale dataset.
Skillsets:
- Proficiency in R-studio, with the mirt and/or lavaan packages (psych package is a possible replacement for lavaan if needed). Proficiency in MPlus instead of R & these packages is acceptable.
- Proficiency with IRT models for polytomous responses (e.g., questions that are attitudinal with Likert-type response scaling) and for dichotomous responses (i.e., classic correct/incorrect responses), as well as factor analyses.
Mentor: Dr. Matthew Diemer
Project 8: Curriculum, Assessment, & Professional Learning Data Analysis and Impact
Chicago Public Schools has provided all schools with a freely available high-quality PK-12 curriculum, including instructional materials, curriculum-embedded assessments, and professional learning. Over the last year, the district has developed an implementation framework and aligned Impact Model, and is working to understand how teachers are using the curriculum and the impact of professional development. This project would support the district in creating descriptive statistics to understand curriculum and assessment use at different levels (varied by teacher, school, content area, grade level, network etc.) and understand if and how professional learning is having an impact on teacher practice and use of the materials.
Skills desired: proficiency in data cleaning, analysis & visualization software (CPS tends to use Google Apps Script, PowerBI, SAS/SQL); multilevel models.
Mentor: Dr Sasha Klyachkina, Department of Student Assessment & MTSS
Project 9: Science Curriculum and Assessment Review
As Chicago Public Schools is working to provide all students with freely available K-12 science curriculum, we are reviewing and customizing OpenSciEd for Chicago Public School’s high-quality curriculum and assessment criteria. This project would support CPS’ review of science curriculum-embedded assessments, including making recommendations for revisions.
Skills desired: assessment design; science content knowledge; preferred: experience/expertise with developing 3-dimensional assessment tasks
Mentor: Dr Sasha Klyachkina, Department of Student Assessment & MTSS
Project 10: Social Science Curriculum and Assessment Review
As Chicago Public Schools is working to provide all students with freely available K-12 social science curriculum, we are developing an in-house social science curriculum aligned to our social science inquiry arc, high-quality curriculum and assessment criteria. This project would support CPS’ review of social science curriculum-embedded assessments, including making recommendations for revisions.
Skills desired: assessment design; social science content knowledge; preferred: preferred: experience/expertise with developing inquiry-based social science tasks
Mentor: Dr Sasha Klyachkina, Department of Student Assessment & MTSS
