Curriculum-Based Measurement probe generator — TEKS as the source, error analysis built in
Schultz C-SEP 2.0 Methodology
Subject
Oral Language TEKS aren't a separate strand — they live inside ELA §110.x under Listening, Speaking & Discussion (strands 1–2) and Response to Text / Oral Inquiry. Use the codes below as a starting point, or enter any OL-related standard manually.
Common OL TEKS — tap to copy
TEKS Code
TEKS Description
Additional Student Context (optional)
Grade Level
Select the student's instructional level, not necessarily their enrolled grade — out-of-level probes measure meaningful growth for students performing above or below grade expectations.
TEKS Standard
TEKS Code
TEKS Description
Probe Format
Administration
Known Error Patterns (optional — check all that apply)
Additional Student Context (optional)
⚠️ AI-generated probes are a starting point. Review each item for grade-level appropriateness and TEKS alignment before use with students. The diagnostician is responsible for all educational decisions.
📋 3 items per standard — three probes allow error pattern detection across multiple attempts. A single item can't distinguish a systematic error from a one-time slip; three items reveal whether a pattern is consistent.
📈 Baseline & progress monitoring — these probes establish meaningful baseline data at the student's instructional level. Re-administer the same TEKS standard over time to efficiently track growth and document response to intervention.
🤠 TEA State Resource
TIER Computational Fluency Progress-Monitoring System
TEA provides 20 ready-to-print math CBM probe forms per grade level (K–6), available in both English and Spanish. Timed computational fluency measures — ideal for progress monitoring and convergent evidence in dyscalculia evaluations.
Select a grade level and TEKS standard, then click Generate 3 Probe Items to create student-facing CBM probes with error analysis.
Generating probe items...
🗣️ Oral Language — The Foundation Beneath the Ropes
Oral language is not a separate rope — it is the soil all four ropes grow from. Recent research (Catts, Kamhi, Tomblin; DLD literature 2018–2024) has established strong predictive links between oral language skills and literacy outcomes, particularly for students at risk for dyslexia, dysgraphia, and DLD. Use this reference to understand how OL deficits surface across the academic ropes and what TEKS strands they underpin.
How OL Deficits Surface by Rope Domain
Phonological Awareness → Reading
Weak phonological memory and phoneme manipulation predict early decoding failure. Students who struggle to segment, blend, or manipulate spoken phonemes will not map them reliably to print. This is the OL–Dyslexia pipeline most strongly supported by research (Catts et al., 2005; NICHD).
📖 Reading🗣️ Language
Vocabulary (Gc) → Reading Comprehension
Oral vocabulary is the single strongest predictor of reading comprehension beyond early grades. A student with weak expressive and receptive vocabulary will decode fluently but fail to comprehend — the classic "word caller" profile. TEKS: vocabulary standards §110.x 3A–3D across all grade bands.
📖 Reading🗣️ Language
Oral Syntax → Written Sentence Construction
Students cannot write sentences they cannot first understand and produce orally. Weak oral syntax (short, simple spoken sentences) predicts weak written sentence construction. Students with DLD often present with both. TEKS: writing conventions §110.x 11C and composition TEKS K–8.
✏️ Writing🗣️ Language
Word Retrieval (Glr/RAN) → Fluency & Spelling
Slow or inaccurate word retrieval and rapid automatized naming (RAN) predict both reading fluency and spelling automaticity. Students with DLD and dyslexia frequently show RAN deficits alongside phonological weaknesses — the "double deficit" profile (Wolf & Bowers, 1999). TEKS: fluency §110.x 4A and spelling automaticity K–5.
📖 Reading✏️ Writing🗣️ Language
Academic Language (Gc) → Math Reasoning
Math word problems require parsing academic language, holding multi-step directions, and using mathematical vocabulary. Students with OL deficits often score higher on computation than word problem tasks — the discrepancy itself is diagnostic. TEKS: problem-solving and reasoning standards across all grade bands.
🧮 Math🗣️ Language
Listening Comprehension → The Simple View
The Simple View of Reading: Reading Comprehension = Decoding × Language Comprehension. Listening comprehension (LC) is the ceiling on reading comprehension once decoding is mastered. If LC ≈ Reading Comprehension → word recognition SLD. If LC is also weak → language comprehension deficit (DLD). TEKS: listening/speaking §110.x 1–2.
📖 Reading✏️ Writing🧮 Math🗣️ Language
Assessment implication: When a student underperforms on reading or writing tasks, assess oral language before concluding the deficit is print-specific. A student who also struggles on listening comprehension or expressive language tasks may have DLD underlying or co-occurring with dyslexia. The OL data is not separate from the SLD evaluation — it explains why the print-based deficits exist and how deep they go.
Key instruments: CELF-5 (Recalling Sentences, Formulated Sentences, Word Classes), WIAT-IV Oral Language composite, WJ-V OL cluster (Oral Vocabulary, Listening Comprehension), CASL-2, ROWPVT/EOWPVT, CTOPP-2 (RAN subtests for retrieval).
📚CBM Probe Library0
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