Using AI to Identify Literacy Gaps Quickly

When time is short, you need a fast way to see which skills most students are missing-decoding, fluency, vocabulary, or evidence-based writing. This workflow turns small artifacts into clear patterns you can teach the next day.

What youâ€â„¢ll build

• A 5-skill screen for reading/writing (decoding â€Â¢ fluency â€Â¢ vocab â€Â¢ comprehension â€Â¢ evidence).
• Prompt pack that turns exit tickets and short passages into actionable groups.
• Mini-lesson menu for the top three gaps.

Quick data sources (pick 1â€"2)

• 30â€"60 word cold read with one question.
• Sentence-combining or cloze item (vocabulary/structure).
• 3â€"4 sentence written response with a quote.
• High-frequency word probe (primary) or morphology sort (upper grades).

Core analysis prompt

ROLE: Literacy coach. Analyze student samples to surface patterns without grading.
INPUT: Grade [X], text difficulty [Y]. Samples below: 
[Paste 8â€"25 brief samples separated by ---]
TASKS:
1) Cluster students by the FIRST limiting skill (decoding, fluency, vocabulary, comprehension, evidence-based writing).
2) For each cluster list 2â€"3 observable features from the samples.
3) Recommend a 10â€"12 minute mini-lesson with a concrete routine and example.
CONSTRAINTS: Use neutral language. No labels. Output a table.

Output you want

GROUP | Limiting skill | Observable features | 12-minute mini-lesson
A     | Vocabulary     | Mis-uses of tier-2 words; context ignored | Frayer mini + sentence frames
B     | Evidence       | Quote missing or not linked | Two-column â€Å“claim â" ' quote â" ' becauseâ€Â drill
C     | Fluency        | Word-by-word reading; punctuation ignored | Echo read + phrase scoop marks

Mini-lesson menu (plug-and-play)

Vocabulary (Tier-2)

• Frayer micro: definition, example, non-example, student sentence.
• Context switch: swap a wrong word with a better fit and explain why.

Evidence-based writing

• Two-column organizer: Claim | Quote | Because with one modeled example.
• Sentence frames: â€Å“The text states â€ËœÃ¢€Â¦,â€â„¢ which shows â€Â¦Ã¢€Â.

Fluency

• Echo read one paragraph; mark scoops; one timed re-read.
• Whisper phones or partner feedback on phrasing.

Decoding / Morphology

• Blend drill with target pattern (e.g., CVCe â" ' make, time, late).
• Prefix/suffix sort with quick â€Å“meaning checkâ€Â.

Micro-case

Context: Grade 6, 22 students, informational text paragraph + 3-sentence response. AI clusters: Evidence (9), Vocabulary (7), Fluency (4), Other (2). Action: Two 12-minute stations across two days using the mini-lessons above. Result: Next-day exit tickets showed 70% correct evidence linkage; vocabulary misuse dropped by half.

Prompt pack

MAKE BULLETS: Convert each sample to 2 observable bullets (no judgment words).
DIAGNOSTIC: Decide the first limiting skill for each sample and justify with a quote.
LESSON WRITER: Draft a 12-minute routine with materials list and 2 checks for understanding.

Quality checks (1 minute)

• Is each cluster defined by one limiting skill?
• Do examples quote studentsâ€â„¢ words or text-not impressions?
• Does each mini-lesson name exact teacher moves and a quick check?

Resources

• Screen: 5-skill quick sort (teacher copy).
• Organizers: Claim-Quote-Because, Frayer micro, Phrase scoops.
• Prompt pack: bullets, diagnostic, lesson writer.

Bottom line: Small samples â" ' clear clusters â" ' tiny lessons that move the needle this week.