FoxFish
Instructional design

Differentiated Instruction with AI: A Practical Playbook

Three concrete moves to differentiate without writing three versions of every assignment, plus a sample week showing how it fits a real schedule.

June 1, 2026 7 min read

Differentiated instruction is one of those phrases that everyone agrees with and almost nobody has time for. The traditional version — three or four versions of every assignment, hand-leveled by ability group — is a recipe for teacher burnout. AI doesn't solve that problem by magic, but it makes three specific moves much cheaper. Here's the practical playbook.

Move 1: Same content, three reading levels

Take the core reading passage or word problem set for your lesson and ask the AI to produce three versions: on grade level, one band below, one band above. Same vocabulary you're teaching, same standards, different syntactic density. Students work on the same skill at their access point.

In FoxFish, set the topic identically and change only the grade selector. The model adjusts vocabulary and sentence length while keeping the same content focus.

Move 2: Same topic, three Bloom's levels

Instead of three reading levels, vary cognitive demand. A "Remember" version of a question for a student building confidence, an "Apply" version for the on-target student, an "Analyze" version for the extension group. Add "lean toward Bloom's level X" in the extras field when generating to push the AI in that direction.

  • Foundational: "Identify the main idea of paragraph 2."
  • On grade: "Summarize paragraph 2 in one sentence."
  • Extension: "Compare the main idea of paragraph 2 with the author's overall thesis."

Move 3: Diagnostic-then-personalize

Assign a 10-question diagnostic on a unit's prerequisite skills. Look at the per-student missed-question report. For students who missed the same two skills, generate a 5-question targeted practice on those skills alone — same topic, custom focus. This is the differentiation move that most depends on AI, because hand-writing personalized 5-question sets for 25 students every week is impossible.

FoxFish's per-student dashboard surfaces this automatically — it summarizes strengths and weaknesses from attempt data so you don't have to comb the gradebook to find the pattern.

A sample week

  • Monday: Diagnostic — 10 questions, mixed prerequisites for the unit.
  • Tuesday: Whole-group lesson on the on-grade target.
  • Wednesday: Three-version practice (reading-level differentiated).
  • Thursday: Mini-lesson on the most-missed prerequisite from Monday's diagnostic; targeted re-practice for that subgroup.
  • Friday: Short summative on the week's focus skill.

Total teacher prep with AI assistance: roughly 30 minutes versus 2+ hours hand-leveling. The students don't care which approach you used; the results show up in the formative data either way.

What AI still doesn't differentiate well

AI is great at varying reading level and Bloom's level. It is not good at differentiating for IEP accommodations that depend on knowing the specific student (sensory needs, behavior plans, processing speed), or for cultural relevance in a specific community. Those are still yours. Use AI for the volume problem, not the relationship problem.

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