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Education Teachers, Postsecondary

Scrub through 197years of this role's history, from when it first emerged, through every wave of technology that reshaped it, to the cited projections for where it's heading next.

2026drag to travel through time
1850187519001925195019752000now
2026
Known today as Education Teachers, Postsecondary (BLS SOC 25-1081)
Latest actual · 2024
75K
BLS OEWS May 2024, as reported by O*NET. Employment of education teachers postsecondary (25-1081) has stabilized at approximately 74,900 -- below the estimated 2000-era peak, reflecting the well-documented 30%+ decline in teacher preparation program enrollment nationally between 2010 and 2020 (Center for American Progress, NCTQ data). The teacher shortage in K-12 has modestly reversed some enrollment decline since 2022, but the pipeline has not recovered to pre-2010 levels. The 25-1081 count represents roughly 5% of the 1.4 million total postsecondary faculty, reflecting education's reduced share of undergraduate majors compared with its 1960s-1970s peak.
Latest actual · 2024
$72,090
BLS OEWS May 2024 median annual wage for 25-1081 specifically, as reported by O*NET. This figure covers full-time and part-time faculty in education departments at postsecondary institutions; the median is pulled down by the high part-time share of the field relative to the all-faculty average ($83,980 across all postsecondary teachers in May 2024). The gap between 25-1081 ($72,090) and the overall postsecondary median reflects both the part-time compositional effect and the historically lower wages in education fields relative to STEM, health, and business disciplines.
Each dot is a cited figure over time; the dotted line only links them (values between aren't measured). Hollow dots are estimates.
Beat · 2025

More than 5,000 teacher candidates have enrolled in "AI for Tomorrow's Teachers" professional development modules since early 2025, with 86% reporting growth in skills for teaching with AI (eSchool News, July 2025). For education faculty, this is the clearest marker of a role transformation: the faculty member who was formerly the authority on lesson planning and curriculum design is now simultaneously a practitioner using AI tools, a teacher of AI literacy to future teachers, and a quality-control evaluator of AI-generated materials that candidates submit. Teaching AI literacy to future teachers is the newest and most distinctively expert task in the 25-1081 role.

Tools of the era

The tools that defined the work

Select an era to see how it reshaped the work.

  • Recitation, demonstration, and practice teaching (oral pedagogy era)

    The early normal school faculty had no instructional technology beyond a blackboard, chalk, and whatever texts they could assemble. Cyrus Peirce, the first faculty member of the Lexington Normal School, taught by demonstrating good teaching in real time and having student-teachers observe and imitate. Practice teaching -- sending students into model schools attached to the normal school -- was the only pedagogical tool available for clinical training. The faculty member's job was to embody the standard of good practice, articulate it in words, and watch candidates attempt to replicate it.

    Work toolChanging equipment

  • Textbooks, pedagogical journals, and standardized curricula (disciplinary formation era)

    As normal schools became teachers colleges and then schools of education within universities, education faculty acquired the tools of academic discipline formation: research journals (the Journal of Educational Psychology launched in 1910, the Journal of Teacher Education in 1950), textbooks that codified teaching method, and standardized curriculum frameworks. Faculty could now assign readings from Dewey, Thorndike, and Piaget rather than relying solely on demonstration. The founding of AACTE (American Association of Colleges for Teacher Education) in 1948 and NCATE (National Council for the Accreditation of Teacher Education) in 1954 gave faculty a formal accreditation framework that structured program curricula nationally for the first time.

    Work toolChanging equipment

  • Microteaching and video feedback (clinical practice technology era)

    Microteaching -- developed at Stanford University around 1963 by Dwight Allen and colleagues -- gave education faculty a new clinical tool: reduce the complexity of teaching to a short, focused lesson with a small group, record it on video, review and discuss the recording with the candidate, then reteach. Portable video cameras (the Sony CV-2000, first consumer VTR, launched in 1965) made recording practical for education programs. For education faculty, microteaching shifted clinical supervision from occasional observation of full classroom teaching to a high-frequency, footage-based coaching cycle. This was the first time technology created a feedback loop that operated faster than a semester-long student teaching placement.

    Effect on the work

    Microteaching did not reduce faculty demand -- it intensified the supervisory role by multiplying the number of coaching cycles per candidate per semester. Programs that adopted microteaching required faculty time for debriefing sessions that would not have existed under the traditional model.

    Work toolChanging equipment

  • Word processing, email, LMS platforms (productivity and course management era)

    The arrival of word processing eliminated the typewriter from course material production, which had been a real friction point for education faculty creating lesson plan templates, rubric banks, and curriculum frameworks. Email transformed the faculty-to-supervisor communication chain during student teaching placements: a cooperating teacher in a K-12 school could now send daily notes to the university supervisor without scheduling a call. Learning management systems (Blackboard launched in 1997; Moodle in 2002; Canvas in 2011) moved course materials, syllabus management, and assignment collection online, reducing paper logistics but adding platform management as a new faculty task. These tools raised faculty productivity in course administration without fundamentally changing the supervisory or instructional core of the work.

    Work toolChanging equipment

  • Online and hybrid program delivery, video-based observation platforms (remote supervision era)

    The shift to online teacher preparation programs -- accelerated by regional accreditation changes that permitted remote student teaching supervision -- created new demands on education faculty: managing asynchronous discussion boards, recording lecture videos, and supervising student teachers at K-12 placements scattered across wide geographic areas rather than concentrated near the university. GoReact (founded 2013, later acquired by Echo360) became a widely adopted platform for video-based clinical supervision: student teachers record lessons on a phone, upload to the platform, and faculty supervisors post time-stamped feedback without traveling to the school site. This compressed the logistics of clinical supervision significantly while maintaining the feedback function that is the core of the faculty role.

    Effect on the work

    Online delivery expanded the potential reach of education faculty -- programs could enroll student teachers in distant or rural placements -- but did not reduce headcount demand. Remote supervision still required one faculty supervisor per cohort of student teachers.

    Work toolChanging equipment

  • Generative AI for lesson planning, rubric generation, and literature synthesis (AI-augmented pedagogy era)

    MagicSchool AI (launched 2022; named Fast Company's Most Innovative Company #9 in Education for 2026), Brisk Teaching, and Eduaide AI can generate complete, differentiated lesson plans, IEP accommodation scaffolds, culturally responsive curriculum variations, and rubric banks in minutes -- precisely the artifacts education faculty spend most of their preparation time creating and assigning. The Federal Reserve's 2025 FEDS Notes study placed Education at a language-model exposure z-score of 0.68 (above average), confirming that the text-heavy, template-driven nature of education course materials is unusually well-matched to what large language models produce. For education faculty, this creates both the largest augmentation surface of any recent technology era and the sharpest displacement risk to prep-task time. The countervailing force: AI tools for K-12 teachers have made AI literacy the fastest-growing required competency for teacher candidates, which has in turn made teaching AI literacy to future teachers a new irreducibly expert task for education faculty.

    Effect on the work

    Teacher preparation program enrollment, which had already declined roughly 30% nationally between 2010 and 2020, faces additional structural pressure as AI tools reduce the perceived complexity of lesson planning and curriculum design. However, the CAEP accreditation requirement for clinical supervision (human faculty observing and coaching student teachers) constrains how far programs can be automated. BLS projects modest 2.1% employment growth for 25-1081 through 2034, suggesting the AI augmentation effect is expected to offset displacement rather than accelerate it.

    AI audit toolsPattern detection
Projection cone · present → 2034

What credible sources project

Scrub the slider past now to anchor each scenario on the scrubber. The spread is the range of futures credible sources project for this role.

Employment outlook
Projected change in the number of people doing this work.
BLS National Employment Matrix 2024-34
→ 2034
+2.1%
BLS Employment Projections -- industry-occupation matrix plus labor productivity assumptions. The 2024-34 cycle projects 2.1% employment growth for 25-1081, from 74,900 (2024) to approximately 76,500 (2034), adding roughly 1,600 positions. This is below the all-occupations average of +4%. The BLS methodology reflects continued demand from teacher preparation programs (driven by persistent K-12 teacher shortages in shortage-area subjects and regions) offset by enrollment pressure from declining interest in the teaching profession and AI tools that reduce some of the preparation load. Clinical supervision -- the CAEP-required human function that anchors 25-1081 employment -- is not modeled as automatable in the BLS methodology.
Center for American Progress -- Teacher Pipeline Decline (2022)
→ 2030
-5%
Structural demand forecast based on documented decline in teacher preparation program enrollment. Teacher preparation program enrollment fell approximately 30% nationally between 2010 and 2020 (NCTQ and Center for American Progress data). The teacher shortage since 2022 has partially reversed this trend, but the pipeline has not recovered to pre-2010 levels. A continued 1-2% per year decline in teacher candidate enrollment -- driven by compensation concerns, working-condition pressures, and AI reducing perceived barriers to entry -- would put 25-1081 employment under modest downward pressure through 2030, partly offsetting the BLS baseline projection. This -5% scenario represents the downside if the enrollment recovery stalls.
AI task exposure
Share of the role’s tasks that researchers estimate AI can do. This is a measure of task exposure, not a forecast of jobs lost.
Eloundou et al. -- "GPTs are GPTs" (2023)
→ 2028
35%
of tasks
GPT-4 task-by-task LLM exposure labeling on O*NET tasks. Education teachers score above average for LLM exposure (Federal Reserve FEDS Notes 2025 places Education at z-score +0.68) because the text-heavy, template-driven outputs of education faculty work -- lesson plans, rubrics, curriculum frameworks, course syllabi, assessment items -- are precisely what large language models generate well. The 35% figure approximates the share of 25-1081 tasks meaningfully exposed to LLM assistance based on the Federal Reserve z-score calibration. Critically, this is task exposure, not employment displacement: the clinical supervision and AI-literacy-teaching functions are not LLM-exposed, and they anchor a substantial fraction of the role.
Frey & Osborne (2013)
→ 2033
4%
of tasks
Gaussian-process classifier on O*NET task features. Frey and Osborne classified postsecondary teachers as a whole as having very low computerization probability -- among the lowest-risk occupations in their dataset -- citing the creative and social-perceptual demands of teaching as strong bottlenecks against automation. Education teachers specifically would score even lower than the postsecondary average in the F&O framework: clinical supervision of student teachers and mentorship of doctoral students are activities that F&O's bottleneck analysis would classify as requiring precisely the social intelligence and complex judgment that resisted automation in 2013. The 4% figure here represents F&O's approximate computerization probability for postsecondary teachers (low-risk tier); it is cited as an exposure estimate, not an employment-decline forecast.
Today, in this role

What's shifting in the work right now

The historical view above shows how this role has moved. This is the present-day detail: which AI tools are picking up which tasks, where the edge still is, and the natural directions this work can grow.

What's changing in your day

Three parts of your work where AI is already doing real lifting, and what stays yours.

AI is sitting alongside you herePrepare course materials for teacher education programs — syllabi, model lesson plans, differentiation matrices, assessment rubrics, curriculum mapping templates, and case-study handouts — using AI lesson-generation tools (MagicSchool AI, Brisk Teaching, Eduaide AI) to accelerate first-draft production, then applying pedagogical expertise to validate alignment with state teaching standards, CAEP program requirements, and culturally responsive teaching frameworks.

Prepare course materials for teacher education programs — syllabi, model lesson plans, differentiation matrices, assessment rubrics, curriculum mapping templates, and case-study handouts — using AI lesson-generation tools (MagicSchool AI, Brisk Teaching, Eduaide AI) to accelerate first-draft production, then applying pedagogical expertise to validate alignment with state teaching standards, CAEP program requirements, and culturally responsive teaching frameworks.[18],[19]

Where your edge is

Eduaide AI roots its outputs in 1,000+ peer-reviewed articles and built-in pedagogical frameworks (5E Inquiry, UDL, Backward Design, Gagné's Nine Events, Montessori) — making it particularly well-suited for generating teacher-education course materials that must be grounded in research. Use it to draft the model lesson plans you then workshop with candidates in methods courses; use Brisk Teaching to turn an article or state standard into a differentiation scaffold in your Chrome browser in seconds. Your expert investment goes into validating cultural responsiveness, standards-alignment accuracy, and the pedagogical decisions behind each material — which AI cannot reliably make without domain-expert review.

AI is sitting alongside you hereEvaluate and grade teacher candidate assignments — lesson plan drafts, teaching philosophy statements, reflection journals, curriculum design projects, and case-analysis papers — using Gradescope AI-assisted answer grouping to cluster similar responses for efficient rubric application on large cohorts, then applying expert pedagogical judgment to evaluate the quality of candidates' reasoning about learning, differentiation, assessment design, and student needs.

Evaluate and grade teacher candidate assignments — lesson plan drafts, teaching philosophy statements, reflection journals, curriculum design projects, and case-analysis papers — using Gradescope AI-assisted answer grouping to cluster similar responses for efficient rubric application on large cohorts, then applying expert pedagogical judgment to evaluate the quality of candidates' reasoning about learning, differentiation, assessment design, and student needs.[20],[21]

Tools picking this up
Where your edge is

Deploy Gradescope for all written assignments where you can define structured rubric criteria — teaching philosophy statements, lesson plan technical components (objective-activity-assessment alignment), and reflection journals with scored dimensions. Gradescope's answer grouping lets you apply a rubric decision once to a cluster of similar responses rather than grading individually — significant time savings on cohorts of 30-60 teacher candidates. Use Turnitin AI detection as a signal for closer review, not standalone evidence — the authentic voice and contextual specificity of a strong teaching philosophy statement is assessable by expert faculty in ways that AI detection cannot reliably confirm or deny. Reserve your expert engagement for the qualitatively hard judgments: does this candidate's lesson plan show evidence of understanding how assessment drives instruction, or just how to fill in a template?

AI is sitting alongside you hereConduct and publish original education research — designing studies on learning outcomes, teacher effectiveness, curriculum design, literacy development, inclusive education, and educational technology — using Elicit and Consensus for AI-assisted systematic literature review and evidence synthesis, NotebookLM for research-packet synthesis, and statistical software for data analysis, while maintaining that the research question, design, and interpretive contribution are the faculty member's intellectual core.

Conduct and publish original education research — designing studies on learning outcomes, teacher effectiveness, curriculum design, literacy development, inclusive education, and educational technology — using Elicit and Consensus for AI-assisted systematic literature review and evidence synthesis, NotebookLM for research-packet synthesis, and statistical software for data analysis, while maintaining that the research question, design, and interpretive contribution are the faculty member's intellectual core.[11],[14]

Where your edge is

Use Elicit to conduct structured literature extractions across ERIC, SSRN, and peer-reviewed education journals ("what does the evidence show about AI-integrated lesson planning in pre-service teacher education?") — it reads papers and extracts specific information rather than just returning titles, compressing a 20+ hour literature mapping to hours. Elicit and Consensus are both documented as tools used in actual education courses at the graduate level (PMC12642211, 2025). Keep the research question formulation, the study design decisions (whether to use a quasi-experimental design vs. qualitative case study, which measures have ecological validity in teacher education contexts), and the interpretive contribution as the human core — these are what tenure committees, AERA reviewers, and journal editors are evaluating.

Where this role is heading

Natural next steps for someone with your foundation: not exits, evolutions.

A direction you could grow

Education Administrators, Postsecondary

Education faculty who have served on CAEP accreditation self-study teams, led curriculum redesign committees, chaired department AI policy working groups, or managed student teacher placement programs have directly developed the skill set for associate dean, dean, or provost-track roles in colleges of education. The transition is common and the CRI increase reflects that postsecondary education administration (+7% BLS 2024-2034) is a growing and moderately AI-augmented field — with AI tools for enrollment analytics, program assessment dashboards, and accreditation documentation that administrators deploy. The faculty-to-administration path in education programs is particularly well-structured compared to other disciplines, with clear stepping-stones through department chair and assistant dean roles.

What you'd add
  • · CAEP accreditation self-study authorship: evidence-based documentation of program quality across all five CAEP standards; continuous improvement planning; site visit preparation
  • · Higher education budget management: faculty position planning, operating budget requests, grant overhead negotiation, and state appropriation advocacy for teacher preparation programs
  • · Enrollment management for teacher preparation: pipeline partnerships with K-12 districts, scholarship program design for teacher shortage areas, transfer articulation agreements with community colleges
  • · Title II federal reporting: Higher Education Act Title II reporting for teacher preparation programs (program completer pass rates, clinical experience hours, employer surveys) submitted to state education agencies
  • · Faculty recruitment, hiring, and retention: search committee leadership for education faculty positions; promotion and tenure facilitation; faculty development programming for AI integration in teaching
What it takesSome new skills to pick up
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The data behind this timeline

On record since1839
Latest tracked employment74,900 (US, 2024)
Latest median pay$72,090 (2024)
Outlook-5% by 2030 (Center for American Progress -- Teacher Pipeline Decline (2022))
View all 32 cited data points
YearUS employmentMedian annual paySource
1870560n/aESTIMATE
19002,400n/aESTIMATE
194014,700n/aESTIMATE
195024,700n/aESTIMATE
1971n/a$12,710ESTIMATE
197563,000n/aESTIMATE
1981n/a$23,302ESTIMATE
1991n/a$42,165ESTIMATE
200079,000n/aESTIMATE
2001n/a$59,742ESTIMATE
200344,880$47,660BLS-OEWS
200447,710$49,530BLS-OEWS
200551,320$50,380BLS-OEWS
200653,470$52,800BLS-OEWS
200754,420$54,220BLS-OEWS
200855,880$56,400BLS-OEWS
200956,880$58,300BLS-OEWS
201061,450$59,140BLS-OEWS
201163,330$75,481BLS-OEWS, ESTIMATE
201262,920$59,350BLS-OEWS
201363,190$60,170BLS-OEWS
201459,980$59,720BLS-OEWS
201560,260$61,560BLS-OEWS
201658,850$62,520BLS-OEWS
201760,500$64,020BLS-OEWS
201860,930$64,780BLS-OEWS
201961,300$65,510BLS-OEWS
202057,560$65,440BLS-OEWS
202158,780$63,910BLS-OEWS
202258,280$66,930BLS-OEWS
202360,860$73,240BLS-OEWS
202474,900$72,090BLS-OEWS
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