How can AI help Montana evaluators write teacher evaluations?
How can AI help Montana evaluators write teacher evaluations?
Montana runs teacher evaluation the way it runs a lot of things: locally. There's no single statewide rubric that every district must use. Instead, the local board of trustees runs the evaluation, and the Office of Public Instruction publishes a state model — Montana-EPAS — that districts can adopt or adapt. The useful thing to know about EPAS is what it's built on: the Charlotte Danielson Framework for Teaching. That's where AI fits. It can help draft the teacher-practice write-up — mapping observation evidence to the right Danielson component and putting it in the framework's own language. What it can't do is run the district's summative process or replace an evaluator's judgment. This post walks through where AI helps, where it doesn't, and what to look for.
What Montana's system actually is
Montana's evaluation requirements live in the Administrative Rules of Montana, ARM 10.55.724, part of the state's Standards of Accreditation. The rule sets minimums rather than a single instrument. The local board of trustees must ensure periodic written evaluations of all regularly employed instructional staff under contract. Each employee has access to the evaluation instrument, the opportunity to respond in writing to the completed evaluation, and access to their files, and the evaluation is implemented as part of the district's integrated strategic action plan.
To help districts meet the rule, the Office of Public Instruction — working with the state's education associations and the teachers' union — publishes model evaluation instruments. A district that adopts and uses one of the published models is construed to have complied with the rule. But using a model isn't required: a district can use its own instrument and process as long as they substantially conform to the rule's requirements.
Montana-EPAS and its Danielson roots
The state model is the Montana Educator Performance Appraisal System, or Montana-EPAS. It's a standards-based, professional-growth system for evaluating teachers and school leaders, and its teacher rubric draws its conceptual basis from the Danielson Framework for Teaching, adapted for Montana schools.
Because EPAS is Danielson-based, its teacher rubric is organized into the four familiar domains:
Planning and Preparation. Knowledge of content and pedagogy, knowledge of students, coherent instructional design, and designing student assessments.
Learning Environment. A culture of respect and rapport, managed procedures and routines, clear expectations, and a space that supports learning.
Instruction. Clear communication, strong questioning and discussion, engaging students in the work of learning, and using assessment to adjust in the moment.
Professional Responsibilities. Reflection on practice, accurate record-keeping, communication with families, professional growth, and contribution to the school community.
Montana doesn't mandate a single set of rating labels. EPAS uses a professional-growth rubric, and a district using Danielson typically works from its four levels — Unsatisfactory, Basic, Proficient, Distinguished — while a district using its own instrument may use different terms.
Three ways to comply
It's worth being concrete about the local-control piece, because it shapes how any tool has to behave. A Montana district can meet ARM 10.55.724 in one of three ways: use the state model, Montana-EPAS; adopt one of the state-approved model instruments the Office of Public Instruction publishes; or use its own instrument and process that substantially conform to the rule. All three are legitimate, and the shared thread across most of them is a Danielson-aligned view of professional practice — which is what makes a Danielson-based tool useful statewide.
After the observation: where the work piles up
The observation itself is familiar work for an experienced Montana evaluator. The write-up that follows is where the hours go: taking fragmentary observation notes and organizing them as evidence against the right domains, settling on a defensible level for each, and drafting written feedback a teacher can act on — and, because the rule requires a written evaluation the teacher can respond to, doing it in a form that will stand up as the record.
Where AI helps with the Montana write-up
The strongest fit between current AI and Montana's system is that teacher-practice documentation.
AI handles three parts of it reliably. First, it turns fragmentary notes into coherent, evidence-anchored prose in the framework's language — the difference between "kids explained their reasoning to each other" and a sentence tied to the instruction domain. Second, it maps evidence to the right component, including evidence that supports more than one. Third, it holds consistency across a caseload, so the same quality of evidence lands in similar territory from teacher to teacher rather than drifting with the hour of the night.
For Montana specifically, the value is drafting in the Danielson framework's own language behind EPAS and toward your district's levels, so the written evaluation is ready for the record rather than something you have to translate first.
Where AI doesn't help — and what stays with the evaluator
The honest scope follows from how Montana built the system.
AI cannot run the district's summative process. Montana evaluations combine formative and summative elements and include an assessment of the educator's effectiveness in supporting student learning; those decisions, and the employee's opportunity to respond in writing, are the district's under ARM 10.55.724.
AI cannot supply an evaluator's professional and local judgment — what the evidence really shows, how a teacher's year unfolded, how a rating fits the context. That stays with the evaluator, who remains the last set of eyes on every rating and comment.
And general-purpose AI in particular has no built-in understanding of how Montana works. Paste notes into a consumer chatbot and it will invent components, assume a single statewide rubric that doesn't exist, and reach for rating labels your district may not use. For a written evaluation a teacher can formally respond to, those errors are the kind that surface at the worst possible moment.
What to look for in an AI tool for Montana
A few questions worth asking before committing a tool to this work.
Does the tool actually know the Danielson domains behind EPAS, or does it produce generic "good teaching" language?
Does it draft toward your district's instrument and labels rather than assuming a single statewide scale?
Does it produce a clean written record that fits ARM 10.55.724 — one the teacher can read and respond to?
Does it stay in its lane, drafting the teacher-practice write-up and leaving the summative process to your district?
Where does your observation data live? Is it stored on the vendor's servers, or used to train models?
How EvalScribe handles Montana evaluations
EvalScribe is built around the four Danielson domains behind Montana-EPAS. An evaluator captures notes by typing, dictating, or photographing handwriting (Smart Scan OCR converts it to text), EvalScribe maps that evidence to the component it supports, and drafts a rating and evidence-anchored feedback for each — using the framework's own language and drafting toward your district's rubric levels. Every rating and comment is fully editable before you finalize it, and the evidence stays traceable to the note it came from, which is what makes the written evaluation defensible.
Two scope notes, because Montana's structure calls for them. First, EvalScribe drafts the teacher-practice write-up. The district's summative process — combining formative and summative elements, any local measure of the educator's effectiveness in supporting student learning, and the employee's opportunity to respond in writing — is run by your district under ARM 10.55.724, not the app. Second, because Montana-EPAS is Danielson-based and EvalScribe is built around the Danielson Framework, it fits districts using EPAS, the Danielson Framework, or a Danielson-aligned local instrument most directly. Confirm your district's adopted model.
Beta testers report saving 30 to 60 minutes per evaluation versus writing the documentation by hand. Across a full caseload — and Montana's small districts often mean one administrator carrying many evaluations — that adds up to dozens of hours back, hours that can go to the conversation the evaluation is meant to support. More detail on the Montana workflow is available at evalscribe.com/montana.
Frequently asked questions about Montana evaluations and AI
What evaluation model does Montana use? Montana is local-control. The state model, Montana-EPAS, is Danielson-based, but districts may use EPAS, another state-approved model, or their own conforming instrument. EvalScribe is built around the Danielson Framework behind EPAS.
What is Montana-EPAS? The Montana Educator Performance Appraisal System — the state's professional-growth model for evaluating teachers and leaders, with a teacher rubric based on Danielson.
Does Montana require a specific rubric? No single statewide one. ARM 10.55.724 sets minimums; districts choose EPAS, a model instrument, or their own conforming instrument and set their own labels.
Does EvalScribe run the whole evaluation? No. It drafts the teacher-practice write-up; the summative process stays with your district.
Can I use it with our own instrument? Often, yes — many Montana instruments are Danielson-aligned because EPAS is. Confirm your district's instrument, or email [email protected].
If you're evaluating teachers in Montana, see how EvalScribe drafts in the Danielson domains behind EPAS at evalscribe.com/montana. Questions, or a school or district license? Reach the team at [email protected].
References
Montana Office of Public Instruction, Educator Evaluation (ARM 10.55.724; model instruments and the substantial-conformance option)
Administrative Rules of Montana, ARM 10.55.724 — Evaluation (local board of trustees; periodic written evaluations; right to respond in writing)
Montana Office of Public Instruction, Montana-EPAS Teacher Evaluation Guide (the state model; Danielson as the conceptual basis; the four domains)
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Page maintained by Anthony D. Neely, Ph.D. — practicing K-12 educator with nearly 20 years in the classroom, 2025–2026 Walker County Distinguished Teacher of the Year, and co-founder of EvalScribe. Framework details verified against the Montana Office of Public Instruction's educator evaluation guidance, the Montana-EPAS guides, and ARM 10.55.724.
Last updated on August 2, 2026.
