Teacher Education Research Coordinator Job Description

Teacher Education Research Coordinators occupy a connective role that most people outside schools of education don't realize exists. They are the people who make sure a faculty member's research idea actually becomes a defensible study — with IRB approval, a data collection plan, institutional agreements, and a dissemination strategy that reaches someone beyond the journal's editorial board.

On any given week, the work might include drafting an IRB modification for a study that just added a district partner, cleaning a longitudinal dataset tracking 200 teacher candidates from admission through their first two years in the classroom, writing the methods section of a grant report due to IES, and preparing a slide deck summarizing findings for a state Title II advisory panel. The breadth is the point: coordinators who are genuinely useful in this role are people who can move between technical statistical work and clear policy communication without losing precision in either direction.

A substantial portion of the job involves managing relationships that sit outside the institution. University teacher preparation programs are increasingly required to demonstrate candidate effectiveness using outcome data from partner school districts — value-added models, observation scores, administrator surveys. Collecting that data requires sustained trust-building with district research offices, compliance officers, and sometimes union representatives who have valid concerns about how the data will be used.

Program evaluation is a parallel thread. Title II reporting alone generates significant data management work: tracking candidate completion rates, licensure pass rates by assessment, and graduate employment in high-need schools. Coordinators who understand the distinction between program monitoring and research-quality evaluation, and who can communicate that distinction to faculty who conflate them, add real value.

The role rewards people with genuine curiosity about what makes teacher preparation work, tolerance for the pace of institutional research, and the organizational discipline to manage multiple concurrent projects without losing track of deadlines. It is not a nine-to-five position during grant submission seasons or accreditation cycles.

Education:

• Master's degree in educational research, curriculum and instruction, education policy, or a closely related field (required at most institutions)
• Doctoral degree or ABD status preferred at R1 universities and IES-funded projects
• Coursework in research methods: survey design, regression analysis, qualitative methods, and mixed-methods frameworks

Research and technical skills:

• Statistical software: SPSS, Stata, or R for quantitative analysis; NVivo or ATLAS.ti for qualitative coding
• Survey platforms: Qualtrics, REDCap, or similar for instrument deployment and response tracking
• Data management: longitudinal dataset construction, codebook development, version control practices
• Literature synthesis: systematic review methodology, citation management with Zotero or Mendeley
• Federal reporting: Title II data submission, IES performance reporting formats

Compliance knowledge:

• IRB protocol preparation and management under 45 CFR 46 (Common Rule)
• FERPA research exceptions and data sharing agreement structure
• CITI training completion (Human Subjects Research — Social/Behavioral track minimum)

Preferred experience:

• 2–4 years in an education research, program evaluation, or policy analysis role
• Prior work as a teacher, instructional coach, or clinical supervisor in a teacher preparation program strengthens candidacy substantially
• Experience supporting federal grant projects (IES, OSEP, Teacher Quality Partnership grants)

Communication skills that matter:

• Ability to write for two distinct audiences — academic manuscript reviewers and district administrators — without producing the same document
• Comfortable presenting data to non-technical stakeholders including school board members, state officials, and teacher educators who distrust statistics
• Grant narrative writing: converting research design into budget-justified workplans that reviewers can follow

Demand for Teacher Education Research Coordinators is tied to three overlapping forces: federal accountability requirements, competitive grant funding cycles, and a growing institutional pressure on schools of education to demonstrate that their graduates actually improve student outcomes.

The Title II reporting mandate under the Higher Education Act has created a permanent, non-discretionary data management workload for every accredited teacher preparation program in the country. State education agencies have responded by building out their own data infrastructure, creating coordinator-level positions on the state side that mirror those at universities. This accountability infrastructure isn't going away regardless of federal education policy shifts — states have embedded it into their own licensure systems.

On the grant side, IES's Education Research grants and Teacher Quality Partnership grants continue to fund multi-year, multi-site teacher education studies that require dedicated coordinator support. Competition for these grants is intense, but institutions with strong research infrastructure — which requires coordinators to build it — win a disproportionate share of funding. The current emphasis on evidence-based educator preparation, accelerated by the What Works Clearinghouse's expansion into teacher preparation evidence reviews, is sustaining investigator and funder interest in this research area.

The AI factor is real and worth naming. Tools that automate parts of qualitative coding, survey analysis, and literature synthesis are reducing the hours required for certain coordinator tasks. This is not eliminating the role — it is shifting what coordinators spend their time on, away from mechanical data processing and toward study design, stakeholder communication, and critical evaluation of AI-generated outputs. Coordinators who adapt to these tools rather than resist them will find their productivity ceiling rises significantly.

For early-career researchers, the coordinator position is one of the better entry points into the field because it provides hands-on experience across the full research lifecycle — a preparation that purely academic paths through graduate assistantships sometimes skip. The salary ceiling is real: without a doctorate, moving into principal investigator or faculty roles is constrained. But the skills built in this position transfer cleanly into policy analysis, nonprofit research, and district data leadership — all fields with stronger hiring pipelines than many people expect.

Dear Search Committee,

I'm applying for the Teacher Education Research Coordinator position at [Institution]. I currently support research operations for the [Center/Department] at [Current Institution], where I manage IRB compliance and data collection for a four-year IES-funded study on mentor teacher effectiveness in urban residency programs.

The project involves longitudinal data from 340 teacher candidates across six district partners, and coordinating IRB agreements across institutions with different compliance offices has been the most technically demanding part of my work. I've developed a submission tracking system that keeps renewal deadlines from slipping and flags when data sharing agreements need to be updated as partner districts change personnel — which happens more often than the IRB office prefers.

The methods side of my background is in mixed-methods design. I ran the qualitative strand of our mentor effectiveness study: 80 semi-structured interviews with cooperating teachers, coded in NVivo across a team of three graduate assistants. When we piloted AI-assisted coding tools to test efficiency on a subsample, I found that the automated codes performed reasonably on surface-level themes but consistently misread the irony and hedging language that teachers use when describing classroom management challenges. We kept manual coding for that strand and used the AI output as a first pass only on the survey open-response items where the stakes were lower.

I spent four years as a secondary English teacher before moving into research, and I find that experience shortens the translation time between what the data says and what it means for preparation program faculty.

I would welcome the opportunity to discuss how my experience aligns with your program's research agenda.

[Your Name]