Top 10 AI Prompts and Use Cases and in the Education Industry in Billings

Billings educators and administrators need practical ways to boost student outcomes without adding more work - AI matters because it can personalize learning pathways and automate routine tasks like grading, scheduling, and progress reports so teachers reclaim time for targeted interventions; the University of San Diego catalog of University of San Diego examples of AI in education shows concrete classroom and administrative use cases, NSF-funded AI education projects and hands-on STEM activities demonstrate place-based AI activities that build STEM skills, and a local roadmap frames pilot steps for MSUB and Billings schools to start safely integrating AI tools in classrooms (Billings AI roadmap for schools and educators).

Bootcamp	Length	Early bird cost
AI Essentials for Work registration	15 weeks	$3,582
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Back End, SQL & DevOps with Python registration	16 weeks	$2,124

“The real power of artificial intelligence for education is in the way that we can use it to process vast amounts of data about learners, about teachers, about teaching and learning interactions.” - Rose Luckin

Selection prioritized prompts and use cases that match Montana's strengths and constraints: alignment with the state's growing photonics/optics and quantum supply chain, clear pathways to local jobs, and practical classroom fit for rural schools with intermittent broadband.

Criteria included workforce alignment (hands‑on, technician-ready tasks recommended by industry panels), low teacher overhead (automations or single‑lesson templates teachers can adopt), tribal and two‑year college inclusion, and measurable short‑term impact so districts can pilot with existing partners.

Recommendations and partners from the MSU Science Math Resource Center convening informed scoring - especially suggestions for apprenticeships, mobile “lab in a van” demos, and distributed quantum activity kits - and guided selection toward prompts that run as week‑long lessons or low‑bandwidth coaching scripts that reach remote students.

Read the full convening report and action steps on the Montana State University Science Math Resource Center convening report and review the local Billings AI roadmap to see how pilots map to these criteria.

Criterion	Why it mattered
Workforce alignment	Industry panels called for technician skills and internships
Rural accessibility	Must work with limited broadband and mobile outreach models
Teacher workload	Low‑prep prompts increase adoption in understaffed schools
Equity & partnerships	Includes tribal colleges, community colleges, and industry partners

“Just as light can be both a particle AND a wave, let us shed our ‘either/or' mentality moving forward and instead frame our reality as ‘both/and'.” - Tricia Seifert

Personalized learning paths turn raw assessment data into a clear, low‑prep remediation plan teachers in Billings can run on a weekly cadence: start with a short diagnostic, map each student to a modular path (Foundation → Core Concept → Application → Mastery), and let the system route practice, targeted mini‑lessons, and multimodal supports so teachers focus on high‑impact coaching.

Instructional design patterns from Google's Learn LM show how to frame prompts that capture student level, learning preference, and a specific goal to produce scaffolded lessons and adaptive quizzes, while commercial blended programs that combine practice tests with AI‑powered remediation report measurable gains (for example, Lumos cites 10–15% GMAS score improvements) - useful context when planning pilots for MSU Billings or district adoption.

The practical payoff: a teacher can reclaim class time by having the AI deliver just‑in‑time remediation and flag students who need human intervention, preserving the high‑touch support rural and tribal schools value.

For implementation templates, see Google's Learn LM labs and an overview of adaptive learning paths linked below.

Diagnostic score	Recommended action
≥ 85%	Advance to next module
70–84%	Review + focused practice + reassess
< 70%	Remediation: foundational review & reassess

“AI brings to the table the ability to turn learning into an active process where you can follow your curiosity.” - Ben Gomes

Automated lesson‑planning prompts can turn Montana's rich, site‑based resources into ready‑to‑use, standards‑aligned units. For example, instruct an AI with the following prompt to generate a complete lesson plan including objectives, materials, activities, differentiation, and assessment.

Build a 45–60 minute Montana State History lesson using the Montana State Parks 21 model lesson plans as source material; include objectives, materials (traveling trunks options), step‑by‑step activities, differentiation, and a short formative assessment.

That prompt maps directly to real offerings - teachers can anchor a unit on Bannack State Park (guided Bannack Tour and hands‑on Gold Panning where students even keep any gold found), tie in First Peoples Buffalo Jump talks and puppetry, or use a Museum of the Rockies virtual visit for pre/post work - while preserving park staff guidance and seasonal scheduling notes from the parks site.

The practical payoff: one machine‑generated lesson template reduces hours of prep, ensures IEFA and social‑studies alignment, and produces a low‑prep field‑trip packet teachers can adapt for remote or in‑class delivery.

Start with the Montana State Parks education resources for teachers and the Montana Heritage Center history and civics field trips as primary inputs.

Example component	Source / grade
Bannack: Gold Panning (hands‑on demo; students keep any gold found)	Bannack State Park - K–12
Bannack Tour (guided townsite history)	Bannack State Park - K–5
Buffalo Jump Talk (archaeology + oral traditions, 30–45 min)	First Peoples Buffalo Jump State Park - K–12

Montana State Parks education resources for teachers · Montana Heritage Center history and civics field trips

For Billings schools facing limited budgets and patchy broadband, on‑demand AI tutoring can deliver targeted, state‑test preparation without hiring a full roster of tutors: programs like Lumos' MAST Test Prep pair two full‑length practice tests with AI‑powered personalized remediation that claims to boost Montana test scores by “10% or more” and generates educator reports for triage (Lumos MAST Test Prep program details and study), while classroom‑built solutions such as Third Space Learning's voice tutor Skye use scaffolded “I do, we do, you do” lessons and live audio coaching so students verbalize reasoning during 30‑minute sessions and teachers receive transcripts and misconception flags to prioritize interventions (Third Space Learning Skye AI math tutor overview).

Evidence from a randomized trial shows AI that augments tutors raised short‑term mastery by about 4 percentage points (and 9 points for lower‑rated tutors), suggesting human+AI models are the pragmatic path for sustained gains and cost control (Randomized trial of AI‑assisted tutoring results).

The practical payoff for Billings: schedule short, supervised AI sessions for state test practice and use AI‑generated reports to target scarce teacher time where it moves the needle most.

Program / Study	Key metric
Lumos MAST Test Prep	Claims 10%+ improvement; standards‑aligned practice + AI remediation
Third Space Learning - Skye	Voice tutoring; reported 7 months growth in 14 sessions (tutor model); licenses start ≈ $5,000/school
Stanford / Tutor CoPilot study (reported)	+4 pp mastery overall; +9 pp for weaker tutors; est. AI cost ≈ $20/student/year

“The big dream is to be able to enhance the human.” - Rose E. Wang

Billings students and adult learners can turn local healthcare offerings into clear career pathways by combining short job‑shadow days, internships, apprenticeships, and post‑graduate residencies so a single five‑hour job shadow can be the first step toward a stable healthcare career in a system that employs thousands locally: Billings Clinic - an integrated, community‑owned health system with a 304‑bed hospital and more than 4,700 employees - publishes clinical rotations, one‑day job shadows (pre‑reqs include age 16+ and a parent signature if under 18), and residency tracks for nurses, pharmacists, and physicians that anchor local pipelines (Billings Clinic student training opportunities).

Community partners scale access: RiverStone Health coordinates over 200 student placements a year, while the University of Montana's career‑pathways model emphasizes stackable credentials, distance learning, and “grow your own” apprenticeships so learners don't have to leave rural communities (University of Montana Healthcare career pathways).

National apprenticeship infrastructure supports this local work - 37,325 registered healthcare apprentices served in 2024 and competency frameworks that map directly to local jobs - so districts can pilot short AI prompts that generate personalized local career maps, employer contacts, and application checklists to move students from exploration to paid training quickly (Apprenticeship.gov Healthcare resources).

Opportunity	What it offers	Local scale/contact
Job shadow	Observation day (max 5 hrs); career exploration	Billings Clinic - jobshadow@billingsclinic.org
Internship / AHEC	Hands‑on placements, nutrition & public health internships	RiverStone Health - ahec@riverstonehealth.org; ~200 students/yr
Apprenticeship / Residencies	Stackable credentials, on‑the‑job training, residencies	UM pathways + Billings Clinic residencies; national frameworks via Apprenticeship.gov

“Registered apprenticeship is an effective blend of job-related instruction and on-the-job learning that is designed to equip apprentices with the required skills and competencies for their occupation. Registered apprenticeship requires the participation of a team of mentors and supervisors guiding apprentices through structured on-the job-learning experiences.” - Danielle Copeland, Executive Director, H-CAP

An AI‑driven counselor triage script can help Billings schools standardize safety checks, prioritize risk, and expedite referrals by converting a teacher or counselor's notes into a structured intake that recommends next steps (safe‑watch, same‑day telepsychiatry, or YPHP referral), auto‑fills the Behavioral Health Clinic referral fields, and flags crisis indicators that trigger immediate contact with local resources; embed local routing rules so the script sends telemedicine cases to the Eastern Montana Telemedicine Network and lists the right pediatric pathway for ages 7–17.

This reduces paperwork and phone‑tag for overstretched staff while keeping human clinicians in the loop for all high‑risk cases. For implementation, map script outcomes to Billings Clinic's outpatient and crisis workflows and to youth services such as Yellowstone Boys and Girls Ranch to ensure appropriate residential or community referrals.

Resource	What to use it for	Contact / note
Billings Clinic Behavioral Health Clinic - outpatient behavioral health services in Billings	Outpatient counseling & referrals	Appointment referrals via primary care; call 406‑238‑2500
Billings Clinic Psychiatric Services - crisis triage, inpatient care, and telepsychiatry resources	Crisis triage, inpatient and telepsychiatry	Crisis lines: 406‑252‑5658, 1‑800‑273‑8255; text START to 741741
Yellowstone Boys and Girls Ranch (YBGR) - residential and community youth mental-health programs	Residential and community youth mental‑health services	Accepting referrals for youth services

“I feel like my life is mine, and Yellowstone gave it back to me.”

Automating routine attendance communications with short, repeatable AI prompts - for example, a template that drafts daily absence notices, routine follow‑up scripts, and an escalation note for chronic truancy - turns a backlog of paperwork into a predictable workflow so office staff and counselors can spend more time on high‑touch outreach; Billings education pilot steps for automating attendance communications.

Pairing that pilot with the local policy playbook keeps schools aligned with MSUB and district priorities as iterative policies are tested and scaled (Billings AI roadmap for schools and educators 2025), so the clear payoff is reclaimed staff capacity for student engagement rather than chasing paperwork.

Design a Montana‑ready prompt engineering workshop as a job‑embedded PD sequence: start with a one‑day, hands‑on kickoff that introduces prompt fundamentals and ethics (mirroring the “Prompt Engineering for Educators” webinar format), move into small‑group labs where teachers craft prompts tied to local standards and place‑based lessons (use the iLearnNH four‑step prompt framework: context, task, relevance, examples), and follow with classroom trials plus peer coaching so teams refine prompts against student work - this aligns with Montana OPI guidance that PD be sustained, data‑driven, and classroom‑focused and lets districts seek OPI renewal unit approval (OPI Billings events have offered up to 8 renewal units).

The practical payoff: a teacher team returns to school with a tested lesson template, a short rubric for AI outputs, and a concrete artifact that can be submitted for district PD credit, turning one training day into lasting classroom change.

For templates and state alignment, pair workshops with OPI's Professional Learning guidance and educator prompt libraries to speed local adoption.

Source	Workshop element reflected
Montana OPI Professional Learning guidance for educator PD and renewal units	Sustained, job‑embedded PD; renewal unit guidance
Prompt Engineering for Educators webinar (AI for Education) - hands‑on basics to advanced techniques	Hands‑on basics → advanced techniques model
iLearnNH Prompt Engineering hub - four‑step classroom prompt framework	Practical four‑step prompt framework for classroom use

"Prompt engineering is not just about using AI - it's about using it wisely, ethically, and creatively"

Formative assessment and learning analytics in Billings can move from spreadsheets to action when a district-grade prompt asks an AI to fuse attendance, interim assessment scores, behavior logs, and SEL check‑ins into an early‑warning risk ranking with suggested MTSS tiered interventions, owner assignments, and timelines - an approach Panorama advertises through its Solara AI platform and Student Success tools that combine multi‑dimensional data for targeted supports; districts that adopt this workflow see concrete wins (Panorama cites partnerships with 2,000+ districts and measurable outcomes such as an 8% drop in absences and automated teacher supports that produced 90 reading plans per teacher biannually), and the platform's privacy posture (SOC 2 Type 2, data‑privacy certifications) makes it practical for Montana leaders to pilot with state funding streams and professional development aligned to local MTSS goals.

Learn more about the Panorama Solara AI platform and Student Success tools to map an at‑risk prompt to Billings' MTSS rollout: Panorama Solara AI platform and Student Success tools.

Metric / feature	Panorama example
District reach	2,000+ districts supported
Student impact	15 million students reached; 8% reduction in absences
Teacher efficiency	90 reading improvement plans auto‑filled per teacher (biannual)

“Panorama is by far and away the easiest system to navigate I've used in my entire 20 year career in education.” - Jessica Cotter

Authentic assessment for Billings classrooms can use a structured oral viva to probe higher‑order thinking, reduce cheating, and produce defensible grades: design a question blueprint tied to learning outcomes, build a randomized scenario bank, and score every response with a clear rubric that lists criteria, model answers, and prompting rules so scorers know when follow‑ups cost points.

Research shows viva formats are especially strong for applied problem solving and depth of knowledge (University of Guelph oral assessment guidelines for educators), while clinical educators document rubric development and grading methods for assessing reasoning in viva exams (BMC Medical Education study on viva exam rubrics and assessment reliability); digital platforms and OSCE approaches demonstrate how short, structured stations, independent evaluators, and standardized checklists improve reliability and make it harder to game assessments (Examod guide to structured oral and clinical exams and reliability).

Practical next steps for Billings pilots: map two‑evaluator rubrics to state standards, record sessions for appeals and feedback, limit cohort size to maintain fairness, and reserve oral vivas for outcomes where synthesis and reasoning - not rote recall - matter most, so one well‑run viva gives teachers twice the diagnostic detail of a single written test.

Design element	Practical tip for Billings
Blueprint & question bank	Map questions to standards; randomize scenarios to prevent leakage
Rubric with model answers	Explicit criteria + prompting policy for consistent scoring
Multiple evaluators	Use two scorers or paired raters to raise reliability
Recording & appeals	Record sessions for student feedback and grade disputes

An ethical, bias‑aware content‑review prompt helps Billings districts catch culturally insensitive language, erase unintentional erasure of tribal perspectives, and surface rural‑access assumptions before lessons reach classrooms - use a prompt that scans curriculum drafts for stereotypes, missing local voices, and accessibility barriers, then returns line‑level edits, a short rationale, and suggested local sources to consult; pair that workflow with the practical pilot steps in Nucamp's Billings AI playbook to phase in reviews and policy checkpoints (Nucamp AI Essentials for Work registration and practical steps for Billings education leaders).

Tie results into district policy updates and teacher PD so private tutors and programs can redesign high‑touch offerings rather than compete on generic AI outputs (Nucamp AI Essentials guidance for tutors adapting to AI in education), and use the Complete Guide's iterative policy framework to document decisions and community review cycles (Nucamp AI Essentials for Work syllabus and Billings AI roadmap), so one reproducible prompt becomes the district's first line of defense against biased materials and costly community pushback.

To move from planning to impact, Billings leaders should start small, practical, and transparent: convene a cross‑functional pilot team (teacher, counselor, IT, tribal liaison) and trial one classroom‑level use case - attendance automation or the counselor triage script - to free administrative time and route students faster to supports; pair that pilot with clear syllabus language and student‑facing guidance using Arizona's UCATT recommendations on AI in teaching and learning (UCATT AI guidance for instructors from the University of Arizona) and document decisions in the local roadmap so community review and iterative policy align with district values (Billings AI roadmap for education (2025)).

Invest in practical staff capacity - Nucamp's AI Essentials for Work prepares educators to write safe, classroom‑ready prompts and run pilots with syllabus‑level policies in place (Nucamp AI Essentials for Work bootcamp registration) - so one reproducible prompt and a short pilot become the basis for scaling without overburdening teachers.

Program	Length	Early bird cost
Nucamp AI Essentials for Work bootcamp details	15 weeks	$3,582

Set clear guidelines about the use of AI and explain why.