# Mathematical Science Teachers, Postsecondary

> Teach courses pertaining to mathematical concepts, statistics, and actuarial science and to the application of original and standardized mathematical techniques in solving specific problems and situations. Includes both teachers primarily engaged in teaching and those who do a combination of teaching and research.

- **SOC code:** 25-1022.00
- **Canonical URL:** https://singulariki.com/roles/role-25-1022-00
- **Also known as:** Instructor, Mathematics Instructor (Math Instructor), Mathematics Professor, Professor, Adjunct Mathematics Instructor, Assistant Professor, Associate Professor, Math Teacher
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Compile, administer, and grade examinations, or assign this work to others.
- Evaluate and grade students' class work, assignments, and papers.
- Prepare and deliver lectures to undergraduate or graduate students on topics such as linear algebra, differential equations, and discrete mathematics.
- Maintain student attendance records, grades, and other required records.
- Prepare course materials, such as syllabi, homework assignments, and handouts.
- Plan, evaluate, and revise curricula, course content, and course materials and methods of instruction.
- Maintain regularly scheduled office hours to advise and assist students.
- Initiate, facilitate, and moderate classroom discussions.
- Conduct research in a particular field of knowledge and publish findings in books, professional journals, or electronic media.
- Keep abreast of developments and technological advances in the mathematical field by reading current literature, talking with colleagues, and participating in professional conferences.
- Select and obtain materials and supplies, such as textbooks.
- Collaborate with colleagues to address teaching and research issues.

**Emerging tasks** (O*NET):
- Hire adjunct faculty.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Mathematics _(knowledge)_
- Mathematics _(essential_skill)_
- Mathematical Reasoning _(ability)_
- Education and Training _(knowledge)_
- Speaking _(essential_skill)_
- Oral Expression _(ability)_
- Number Facility _(ability)_
- Reading Comprehension _(essential_skill)_
- Active Listening _(essential_skill)_
- Instructing _(transferable_skill)_
- Oral Comprehension _(ability)_
- Written Comprehension _(ability)_

**Skills in demand:**
- Mathematics _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Instructing _(Specialized Skill)_
- Deductive Reasoning _(Common Skill)_
- Active Listening _(Common Skill)_
- Writing _(Common Skill)_
- Learning Strategies _(Specialized Skill)_
- Inductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- English Language _(Common Skill)_
- Active Learning _(Common Skill)_
- Complex Problem Solving _(Common Skill)_

**Tools & technology:**
- Google Docs _(hot technology)_
- Microsoft Access _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Visual Basic _(hot technology)_
- Microsoft Visual Basic for Applications VBA _(hot technology)_
- Microsoft Word _(hot technology)_
- SAS _(hot technology)_
- Structured query language SQL _(hot technology)_
- Learning management system LMS _(in demand)_

## AI exposure & outlook

- **AI task-overlap index:** 83rd percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 90th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 63rd percentile (Moderate) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 87th percentile (High) — source: microsoft_applicability.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 2.3% growth (About average); 4.4k annual openings; 58.9k → 60.2k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $79,350; 48,820 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** 32% automation, 65% augmentation (usage-weighted).
- **Autonomy median:** 3.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** task iteration.

**Tasks most handed to AI here:**
- Evaluate and grade students' class work, assignments, and papers. _(25.7% of measured AI use; validation)_
- Advise students on academic and vocational curricula and on career issues. _(23.7% of measured AI use; task iteration)_
- Provide professional consulting services to government or industry. _(12.8% of measured AI use; task iteration)_
- Compile, administer, and grade examinations, or assign this work to others. _(10.6% of measured AI use; directive)_
- Prepare course materials such as syllabi, homework assignments, and handouts. _(3.8% of measured AI use; directive)_
- Compile bibliographies of specialized materials for outside reading assignments. _(2.9% of measured AI use; directive)_
- Initiate, facilitate, and moderate classroom discussions. _(2.6% of measured AI use; learning)_
- Plan, evaluate, and revise curricula, course content, and course materials and methods of instruction. _(2.2% of measured AI use; task iteration)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me evaluate and grade students' class work, assignments, and papers.
- Help me advise students on academic and vocational curricula and on career issues.
- Help me provide professional consulting services to government or industry.
- Help me compile, administer, and grade examinations, or assign this work to others.
- Help me prepare course materials such as syllabi, homework assignments, and handouts.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-25-1022-00_