Dyscalculia Evaluation Reference — Texas SLD

Framework & Identification Foundation

🔢 What Dyscalculia Is — and Is Not

⚠️ Schreuder TEDA 2026 — Emerging Clinical Framework

The identification framework used on this hub draws from Schreuder (TEDA 2026). It is an emerging clinical framework and is not a TEA-adopted standard. Texas does not currently have a separate eligibility category or TEA-approved determination protocol for dyscalculia. Eligibility is determined under IDEA categories by the multidisciplinary team. Use professional judgment.

✔Is a number processing deficit affecting automaticity, calculation, and foundational number sense

✔Is neurobiological in origin — present from early childhood; persistent despite adequate instruction

✔Can coexist with average or above-average intelligence; IQ is not a gate

✖Is not simply low math scores — the deficit must involve automaticity/fluency AND foundational number sense or calculation

✖Is not confirmed by low Math Problem Solving alone — applied math weakness may reflect reading, language, or reasoning demands, not core number processing

✖Is not caused by inadequate instruction, attention difficulties, or working memory weakness alone — these must be considered as alternative explanations

⚠May co-occur with dyslexia, ADHD, or DLD — each requires independent documentation of educational need

Source: Schreuder, TEDA 2026; Butterworth et al. (2011); Mazzocco (2007)

✅ The Three-Question Framework

Adapted from the Texas Dyslexia Handbook three-question model (Figure 4.1/5.3). All three must be addressed when dyscalculia is suspected.

Characteristics & consequences present?
• Difficulty with math fact automaticity — slow or inaccurate retrieval of basic facts under timed conditions
• Difficulty with foundational number sense — quantity, magnitude, place value, number relationships
• Procedural calculation weakness beyond what fluency alone explains
• Secondary consequences: avoidance, anxiety, slow multi-step work, difficulty with higher-order math

Underlying mechanism present?
Do these difficulties reflect a deficit in core number processing — including approximate number system (ANS), subitizing, magnitude comparison, and/or fact retrieval automaticity — rather than primarily reflecting language, reading, attention, or general cognitive demands?

Unexpected for age and ability?
Are these difficulties unexpected given the student's age, overall cognitive ability, and access to adequate, evidence-based math instruction? Is there documented lack of adequate response to math intervention?

Framework: Schreuder, TEDA 2026; adapted from Texas Dyslexia Handbook (2024)

Five Math Skill Domains — Evaluate Each Separately

📐 Domain Map — What to Assess and Why

A defensible dyscalculia evaluation maps data to each domain separately. A single low math composite is not sufficient — the pattern across domains determines whether a core number processing deficit is present versus a language-mediated, attentional, or reasoning-based math difficulty.

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Domain 1 — Math Fact Automaticity (Fluency)
Timed retrieval of basic addition, subtraction, multiplication, and division facts. The most direct indicator of a dyscalculia profile. Low fluency with adequate untimed calculation suggests the deficit is specifically in automatic retrieval, not procedural knowledge.

WJ-V Math Facts Fluency WIAT-IV Math Fluency (MFA/MFS/MFM) KTEA-3 Math Fluency

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Domain 2 — Computation / Calculation (Untimed)
Procedural algorithm execution without time pressure. Separates fluency deficit from procedural knowledge deficit. A student with dyscalculia typically struggles on both fluency and untimed calculation — not just timed tasks.

WJ-V Calculation WIAT-IV Numerical Operations KTEA-3 Math Computation KeyMath-3 Operations domain

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Domain 3 — Number Sense / Magnitude
Foundational understanding of quantity, magnitude comparison, place value, number relationships, and number line concepts. The approximate number system (ANS) underlies all of these. Deficits here are the most direct indicator of core dyscalculia — distinct from procedural or fluency weaknesses.

WJ-V Number Sense WJ-V Magnitude Comparison WJ-V Number Concepts cluster KeyMath-3 Basic Concepts domain Informal number line tasks

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Domain 4 — Math Reasoning / Problem Solving
Language-mediated applied math requiring reading, verbal reasoning, and multi-step planning. Low scores here alone do not indicate dyscalculia — they may reflect reading demands, language processing, or verbal reasoning weaknesses. Only confirm a dyscalculia pattern when Domains 1–3 are also involved.

WJ-V Applied Problems WIAT-IV Math Problem Solving KTEA-3 Math Concepts & Applications KeyMath-3 Applications domain

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Domain 5 — Relevant Cognitive Factors
Fluid Reasoning (Gf), Working Memory (Gwm), and Processing Speed (Gs) all contribute to math performance. Depressed scores in these areas do not rule out dyscalculia, but they require explicit consideration — a student with very low Gwm may show math automaticity deficits that are secondary to working memory load, not core number processing failure.

WISC-V WMI / PSI WISC-V FRI WJ-V Gwm / Gs / Gf clusters KABC-II Sequential / Simultaneous

Pattern rule (Schreuder framework): Dyscalculia pattern is supported when both math fact automaticity (Domain 1) AND at least one of Domains 2 or 3 are below average. Applied Problems weakness alone (Domain 4) does not constitute a dyscalculia pattern.

Source: Schreuder, TEDA 2026; Geary (2011); Butterworth et al. (2011)

Source note — Five-Domain Framework: The five-domain structure and pattern-identification rules on this page draw from Schreuder (TEDA 2026). The domain descriptions are also grounded in peer-reviewed math disability literature (Geary, 2011; Butterworth et al., 2011; Floyd et al., 2003). This page orients you to the framework — it is not a substitute for the TEDA training or the primary sources. Schreuder's framework is an emerging clinical approach and is not a TEA-adopted standard. Apply professional judgment in all eligibility decisions.

KeyMath-3 — Diagnostic Math Assessment

🗝️ When and Why to Use KeyMath-3

KeyMath-3 DA is the most comprehensive norm-referenced math battery available for dyscalculia evaluations. Unlike WJ-V, WIAT-IV, and KTEA-3 (which each cover math in a few subtests), KeyMath-3 maps the full scope of math skill development across 10 subtests organized into three areas.

Use KeyMath-3 when:

Math is the primary referral concern and a comprehensive picture is needed
Achievement battery math subtests are below average but the domain profile is unclear
You need to differentiate between Basic Concepts (number sense), Operations (calculation), and Applications (reasoning) deficits
Eligibility determination requires convergent data beyond one battery's math composite
Dyscalculia supplement is being generated and Domain 3 (number sense) data is absent

Untimed administration: KeyMath-3 is entirely untimed — it isolates conceptual knowledge and procedural understanding separate from fluency. Pair with a timed fluency measure (WJ-V Math Facts Fluency or WIAT-IV Math Fluency composites) to get the full dyscalculia domain picture.

Source: Connolly (2007); KeyMath-3 DA Technical Manual

📊 KeyMath-3 Structure

Three Areas — 10 Subtests:

Basic Concepts Area — maps to Domain 3 (Number Sense)
• Numeration — place value, number relationships, counting
• Algebra — patterns, functions, early algebraic reasoning
• Geometry — spatial reasoning, shapes, measurement concepts
• Measurement — standard/nonstandard units, estimation
• Data Analysis & Probability — graphs, charts, likelihood

Operations Area — maps to Domain 2 (Calculation)
• Mental Computation & Estimation — mental math strategies
• Addition & Subtraction — procedural multi-digit operations
• Multiplication & Division — procedural operations

Applications Area — maps to Domain 4 (Reasoning)
• Foundations of Problem Solving — basic applied reasoning
• Applied Problem Solving — multi-step, real-world math

Score structure: Subtests yield scaled scores (mean=10, SD=3); area scores and total yield standard scores (mean=100, SD=15). Area score splits are diagnostically meaningful — a student with Basic Concepts weakness but adequate Operations may have a number sense deficit without procedural breakdown, or vice versa.

WISC-V Cognitive Subtests Relevant to Dyscalculia

🧩 Working Memory & Processing Speed — The Cognitive Substrate

Working memory (Gwm) and processing speed (Gs) are the cognitive systems most consistently associated with math calculation and fluency difficulties. They do not cause dyscalculia, but they can independently impair math performance — and must be considered as alternative or co-occurring explanations.

WISC-V Subtest	CHC Narrow Ability	Math Relevance
Digit Span	Memory Span (MS) / Working Memory	Holding intermediate steps during multi-digit calculation; retaining place value while computing
Picture Span	Memory Span (MS)	Visual working memory; retaining spatial/quantitative information
Letter-Number Sequencing	Working Memory (MW)	Manipulating and reordering information — demands mirror multi-step math operations
Coding	Rate of Test Taking (R9) / Processing Speed	Symbol-association speed; closely analogous to math fact retrieval speed
Symbol Search	Perceptual Speed (P)	Visual scanning speed; contributes to fluency on timed math tasks
Arithmetic	Quantitative Reasoning (RQ) / Working Memory	Mental math under WM load — directly taps number processing and automaticity simultaneously; low score is highly relevant to dyscalculia profile
Figure Weights	Quantitative Reasoning (RQ)	Analogical quantity reasoning — measures number sense at a conceptual level without calculation demands

Key distinction: If WMI and PSI are both in the low range but achievement math scores are commensurate with those cognitive scores, the math difficulty may be primarily cognitive rather than a core number processing deficit. Dyscalculia is better supported when math automaticity and number sense scores are disproportionately low relative to overall cognitive ability.

Source: Geary (2011); Raghubar et al. (2010); Schreuder, TEDA 2026

🔍 Fluid Reasoning — Separating Dyscalculia from Math Reasoning Weakness

Fluid reasoning (Gf) underlies math problem solving and the ability to generalize math procedures to novel problems. Low Gf can produce low Applied Problems / Math Problem Solving scores without any core number processing deficit.

Relevant WISC-V subtests:

Matrix Reasoning — nonverbal inductive reasoning; visual pattern completion
Figure Weights — quantitative analogical reasoning; most directly math-relevant Gf subtest
Picture Concepts — categorical reasoning; conceptual abstraction

FIE application:

If FRI is below average and Math Problem Solving is the primary weakness → math reasoning difficulty consistent with general reasoning demands; does not confirm dyscalculia
If FRI is average but Math Facts Fluency and Calculation are both low → supports a specific math automaticity/calculation deficit not explained by reasoning — consistent with dyscalculia profile
If both Gf and math fluency/calculation are low → mixed profile; document both contributing factors

Arithmetic subtest (supplemental): When WISC-V Arithmetic is significantly lower than Digit Span and Letter-Number Sequencing, this suggests a specific number processing deficit on top of working memory demands — particularly useful for dyscalculia pattern documentation.

Source: Floyd et al. (2003); Schreuder, TEDA 2026

Math Anxiety — Differentiation & the mAMAS

😰 Math Anxiety vs. Dyscalculia — High Overlap, Distinct Mechanisms

Math anxiety and dyscalculia frequently co-occur and can produce nearly identical surface presentations — avoidance, slow performance, errors under time pressure, and low scores on timed tasks. Differentiating them matters for eligibility framing and intervention planning.

Dimension	Dyscalculia	Math Anxiety
Primary mechanism	Core number processing deficit — automaticity and/or number sense	Affective/cognitive interference — fear, avoidance, working memory disruption under math-specific stress
Untimed performance	Remains poor even with unlimited time and low-stakes conditions	Often improves substantially when time pressure is removed and environment feels safe
Math fact retrieval	Consistently slow and inaccurate — automaticity never develops	May know facts in low-stress contexts; blanks under pressure
Number sense / magnitude	Foundational deficits — difficulty comparing quantities, estimating, understanding place value	Number sense typically intact; conceptual understanding present when anxiety is managed
Response to low-stakes probing	Errors persist even in 1:1, low-pressure, familiar contexts	Performance often improves markedly in low-stakes 1:1 testing conditions
Self-report / behavioral	Student may not report anxiety — may report confusion, "not understanding," or "forgetting"	Student typically reports worry, racing heart, fear of being wrong; avoidance is affectively driven
Dual presentation appropriate?	Yes — dyscalculia can cause or worsen math anxiety through repeated failure experiences. Both can independently limit educational performance. Document each separately.

Sources: Carey et al. (2016); Ashcraft & Krause (2007); Schreuder, TEDA 2026

📋 mAMAS — Modified Abbreviated Math Anxiety Scale

The mAMAS (Carey et al., 2017) is a brief, validated 9-item self-report scale measuring math anxiety in children and adolescents. It is a modification of the Abbreviated Math Anxiety Scale (AMAS; Hopko et al., 2003), adapted for school-age populations. It is the most widely cited brief math anxiety measure appropriate for school-age students and can be incorporated into the FIE informal data package.

Structure:

9 items rated on a 5-point Likert scale (1 = not at all anxious → 5 = very, very anxious)
Two subscales: Learning Math Anxiety (learning situations) and Math Evaluation Anxiety (testing/performance situations)
Total score range: 9–45; higher = greater anxiety
Normed on students ages 8–18; brief administration (~5 minutes)

FIE use:

Administer as part of informal data collection when dyscalculia is suspected
Elevated mAMAS alongside low math fluency = possible dual presentation — address both in eligibility framing
Low mAMAS with persistent low math performance strengthens the dyscalculia interpretation (anxiety is not driving the deficit)
High mAMAS with adequate untimed math performance may suggest anxiety-primary presentation rather than dyscalculia

Where to find it: The mAMAS is freely available in the appendix of Carey et al. (2017), published in Frontiers in Psychology. It is not a commercial instrument — it can be printed and administered without licensing. Cite as: Carey, E., Hill, F., Devine, A., & Szücs, D. (2017). Frontiers in Psychology, 8, 11.

Source: Carey et al. (2017); Schreuder, TEDA 2026

Informal & Clinical Assessment

📋 Informal Data Sources

Math Fact Timed Probe: Present a 1-minute timed fact sheet for each operation (addition, subtraction, multiplication). Count correct facts per minute. Compare to grade-level expectations. Conduct dynamic assessment — after timing, allow unlimited time to complete; compare score to determine whether the deficit is in retrieval speed vs. procedural knowledge.

Number Line Task (informal): Ask the student to place numbers on a blank number line (0–100, then 0–1000 for older students). Significant clustering or inaccuracy in magnitude estimation is a direct indicator of number sense deficit — the most foundational dyscalculia marker.

Subitizing Probe: Flash dot arrays briefly (1–5 dots). Accurate, fast subitizing is a precursor to number sense. Difficulty subitizing beyond 2–3 dots is an early indicator of approximate number system (ANS) weakness.

Calculation Error Analysis: Analyze errors on untimed calculation tasks. Identify: procedural bugs (consistent wrong algorithm), fact retrieval errors (correct procedure, wrong fact), place value errors, and regrouping breakdowns. Error pattern informs instruction target.

CBM — Math Computation & Math Concepts/Applications: AIMSweb, DIBELS Math, or easyCBM probes provide curriculum-based evidence of math difficulty across multiple time points. Include to document intervention response history and real-world performance. Research supports both MCOMP (computation) and MCAP (concepts/applications) probes as strong predictors of math achievement — MCAP shows stronger correlations with comprehensive criterion measures (r = .654 vs. r = .528 for MCOMP; Codding et al., 2023, advance online publication). When CBM data is available, anchor formal scores to real-world performance: note how digits correct per minute on computation probes or accuracy on MCAP probes compares to grade-level benchmarks across multiple time points. This convergent pattern — low formal scores confirmed by low CBM probes — substantially strengthens the dyscalculia documentation.

Fluency vs. accuracy in CBM interpretation: A student who scores accurately on math probes but very slowly is NOT demonstrating mastery. Research (Codding & VanDerHeyden, 2020) shows that accuracy alone is an unreliable mastery indicator — students who have not achieved fluency (accuracy + rate) are likely to forget the skill. Report digits correct per minute, not just accuracy percentage, and compare to fluency-based benchmarks.

Framework: Schreuder, TEDA 2026; Geary (2011); Mazzocco (2007); Codding et al. (2023, advance online pub.)

👀 Behavioral Observations in Math Contexts

Document math-specific behaviors across settings. These observations directly support the "characteristics present" prong and inform FIE narrative framing.

Finger counting persisting beyond 2nd–3rd grade — strong indicator that fact automaticity has not developed; student is compensating with procedural counting rather than retrieved facts
Subvocalizing or mouthing during math facts — using verbal rehearsal to retrieve facts; indicates non-automatic retrieval
Avoidance and math-specific anxiety behaviors — task refusal, physical distress, or shutdown specifically during math (not other subjects) — may indicate math anxiety co-occurrence
Slow, effortful computation even on simple problems — hallmark of fluency deficit; student can solve but cannot do so automatically
Loses place in multi-step problems — may reflect working memory overload secondary to non-automatic fact retrieval
Difficulty with money, time, and measurement — applied number sense indicators; persistent difficulty here supports foundational number processing deficit
Strong verbal math vs. weak written math — if oral math responses are substantially stronger than written math, consider whether motor or written output demands are a confounding factor

Testing observation: Note whether the student uses fingers, tally marks, or other compensatory strategies during testing. These observations belong in the FIE behavioral observations section and directly support the dyscalculia pattern narrative.

Differential Considerations — What Else Looks Like Dyscalculia

⚖️ Ruling In vs. Ruling Out — Differential Profile Table

Multiple profiles can produce low math scores. The evaluator's job is to determine whether the pattern reflects a core number processing deficit or whether another mechanism better explains the data.

Profile	Math Fluency	Calculation (untimed)	Number Sense	Math Reasoning	Key differentiator
Dyscalculia	Low	Low–Below Avg	Low	Variable	Fluency + number sense deficits; does not resolve with time removal or language scaffolding
Math anxiety (primary)	Low (timed)	Often adequate untimed	Intact	Variable	Performance improves substantially in low-stakes, untimed, 1:1 conditions; mAMAS elevated
Working memory / ADHD	Low–Below Avg	Variable — more errors on multi-step	Often intact	Often below avg (multi-step)	Math difficulty is inconsistent; improves with structure, reduced load, verbal rehearsal; attention/EF measures also low
Language-based (DLD)	Often adequate	Often adequate	Often intact	Low (word problems)	Math reasoning weakness driven by language demands in word problems; calculation and fluency intact or near-average
Intellectual Disability	Low	Low	Low	Low	Global cognitive and adaptive behavior deficits; math weakness is consistent with overall ability level — not unexpected
Inadequate instruction	Low	Low	Variable	Low	Responds rapidly and meaningfully to evidence-based math instruction when fidelity is established; not truly treatment-resistant
Math-specific processing speed deficit	Low (math facts only)	Often adequate untimed	Often intact	Often adequate	Gs average on non-math tasks (Coding, SRF, SWF) but math fluency disproportionately low — deficit is specific to number-symbol automaticity, not global processing speed; supports dyscalculia-consistent profile

Documentation tip — name what you ruled out and why: In the FIE, explicitly address each alternative explanation with data. Use specific language: "Math anxiety was assessed via mAMAS and rated in the low range, making anxiety-primary presentation less likely." "Working memory scores fall in the average range, making WM load an insufficient explanation for the magnitude of math fluency deficit." "Processing speed is average on non-math tasks (Coding SS 112, Sentence Reading Fluency SS 106), indicating the math fluency deficit is specific to number processing rather than a global speed weakness." "Applied Problems weakness appears to reflect reading and language demands in word problems — Calculation (SS 95) and Math Facts Fluency are intact, indicating core number processing is not the deficit." This last pattern — reasoning low, fluency and calculation intact — is a math DNQ pattern: the data do not support dyscalculia, but may support a different eligibility area (reading comprehension, oral language, DLD). Name it explicitly.

Framework: Schreuder, TEDA 2026; Carey et al. (2016); Geary (2011); Schultz & Stephens, C-SEP (2015/2024)

Recognizing the Pattern — Clinical Profile Examples

🔢 Profile A — Math-Specific Fluency Deficit (Dyscalculia-Consistent)

This profile illustrates what a dyscalculia-consistent pattern looks like in real data — specifically the math-specific processing speed pattern where Gs is average everywhere except number automaticity.

Processing speed — non-math tasks: Average
Letter-Pattern Matching SS 112, Sentence Reading Fluency SS 106, Sentence Writing Fluency SS 107 — all average to high average. Global processing speed is intact.

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Math Facts Fluency: Very Low (SS 66, RPI 3/90)
Disproportionately low relative to all other processing speed indicators. This discrepancy — Gs average elsewhere, math fluency Very Low — isolates the deficit to number-symbol automaticity specifically.

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Calculation: Low (SS 68)
Procedural calculation weakness compounds the fluency deficit. Both automaticity and procedural execution are impaired — Domains 1 and 2 both involved.

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Applied Problems: Average (SS 94)
Language-mediated math reasoning is intact when language/Gc skills are strong — confirms the deficit is not language-based and not global. The math difficulty is specific to number processing.

Key interpretive move: The intact processing speed on non-math tasks is your most powerful exclusionary finding. It rules out global Gs deficit as the explanation and isolates the fluency weakness to number automaticity — the core dyscalculia mechanism. Name this contrast explicitly in the FIE. (Profile based on WJ-IV data pattern; Schultz & Stephens, C-SEP, 2015/2024)

💬 Profile B — Language-Mediated Math Reasoning Weakness (Not Dyscalculia)

This profile illustrates the most common math DNQ pattern: Applied Problems is low, but Calculation and Fluency are average or intact. The math reasoning weakness reflects language and comprehension demands — not a core number processing deficit.

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Calculation: Average (SS 95)
Procedural algorithm execution is intact. The student can perform math operations accurately when language demands are removed.

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Number Sense / Quantitative Reasoning: Average–High (SS 104)
Foundational number processing and quantitative reasoning are intact. Core number sense is not the deficit.

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Applied Problems / Math Problem Solving: Low (SS 74)
Language-mediated word problems are significantly below average. This task requires reading comprehension, vocabulary, and verbal reasoning — all of which are also impaired in this profile.

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Oral language / listening comprehension: Low
Story Recall SS 77, Oral Comprehension SS 74 — language deficits are the unifying explanation. Math reasoning is low because the word problem format depends on language comprehension.

FIE language: "Applied Problems weakness appears to reflect reading and language demands embedded in word problems rather than a core number processing deficit — Calculation (SS 95) and quantitative reasoning (SS 104) are intact, indicating number sense and procedural skills are not impaired. This pattern is consistent with the student's broader language comprehension profile and does not constitute a dyscalculia presentation." Eligibility consideration shifts to oral language and/or reading comprehension — not math calculation. (Profile based on WJ-IV data pattern; Schultz & Stephens, C-SEP, 2015/2024)

📋 Math DNQ — Writing a Defensible Non-Qualification in Math

A math DNQ is not a failure of evaluation — it is a well-documented finding that protects the integrity of special education eligibility. A defensible math DNQ requires the same rigor as a qualification: you must explicitly address every plausible explanation for the low math score and show why dyscalculia (or SLD-Math) is not the best explanation.

The three most common math DNQ patterns and how to write them:

Language explains the math reasoning weakness
Applied Problems / Math Problem Solving is low, but Calculation and Math Facts Fluency are average or intact. Write: "The student's difficulty with math word problems appears to reflect demands on reading comprehension and oral language rather than a core number processing deficit. Calculation skills are within the average range, indicating that when language demands are removed, math performance is adequate. This profile is consistent with the student's documented language comprehension weakness and does not meet the pattern expected for SLD in Math Calculation."

Cognitive ability explains the math performance level
All math scores are low, but cognitive composite is also low — math performance is commensurate with overall ability. Write: "The student's math scores are consistent with overall cognitive ability (GIA SS [X]). The math difficulty does not appear unexpected given the student's measured intellectual ability; there is no pattern of math-specific weaknesses disproportionate to overall functioning. This pattern is more consistent with ID or global cognitive needs than with a specific learning disability in math."

Instruction or response to intervention explains the gap
Math scores are low but the student responds meaningfully and rapidly to evidence-based math instruction when fidelity is established. Write: "Available MTSS data indicate that [Student] made [X] progress during [intervention name] when implemented with fidelity, suggesting the math gap reflects limited prior instructional exposure rather than a treatment-resistant learning disability. Continued progress monitoring within a structured math intervention is recommended prior to or in lieu of SLD determination in math."

DNQ does not mean no services: A math DNQ may still result in 504 accommodations, general education math intervention, or other support. The ARD committee considers the full data picture. The diagnostician's job is to document the pattern clearly and explain the most defensible interpretation — not to qualify or disqualify the student.

Framework: IDEA SLD criteria (34 C.F.R. §300.309); TAC §89.1040; Schultz & Stephens, C-SEP (2015/2024); Schreuder, TEDA 2026

Science of Math — Instructional Evidence & CBM-Math Validity

🔬 Science of Math — What the Research Says

The Science of Math (Codding, Peltier, & Campbell, 2023; VanDerHeyden & Codding, 2020) is a research-to-practice framework analogous to the Science of Reading — it advocates for grounding math instruction in cognitive science and behavior analytic research rather than unsubstantiated practices. Survey data indicate teachers continue to use unsubstantiated math practices as frequently as evidence-based ones, and fewer than 50% of teacher candidates can correctly answer basic questions about learning principles (Codding et al., 2023).

Core principles relevant to dyscalculia evaluation and ARD planning:

Conceptual understanding, procedural fluency, and fact automaticity are mutually reinforcing — not competing priorities. The National Mathematics Advisory Panel (2008) concluded that debates about their relative importance are misguided; all three must be built simultaneously.
Fluency = accuracy + rate. A student who is 100% accurate but very slow has NOT mastered the skill and is likely to forget it. True mastery requires fluency — the fast, accurate, and effortless execution of a math skill (Codding & VanDerHeyden, 2020). This distinction matters enormously for eligibility framing: a student who "gets the answers right but takes forever" is documenting a fluency deficit, not a conceptual one.
Explicit instruction for students with math difficulties has consistently strong evidence: the teacher provides clear models, the student practices extensively with feedback, and there are opportunities to think aloud and generalize (NMAP, 2008). This is the instructional need to name in ARD recommendations.
Fractions are the #1 gateway skill for algebra. NMAP (2008) identified fraction proficiency as the most critically underdeveloped foundational skill in U.S. students — directly relevant when evaluating upper-elementary and middle school students with dyscalculia profiles.

FIE/ARD application: When writing math needs statements, explicitly reference the type of instruction supported by research: explicit and systematic instruction, fluency-building practice, and concrete-representational-abstract (CRA) sequencing for conceptual targets. Naming the evidence base strengthens ARD recommendations and helps teachers act on Monday morning.

Sources: Codding, Peltier, & Campbell (2023), TEACHING Exceptional Children, 56(1), 6–11; VanDerHeyden & Codding (2020/2021), The Science of Math; National Mathematics Advisory Panel (2008), Foundations for Success, U.S. Dept. of Education

📈 CBM-Math — Validity Evidence for Screening & Evaluation

Curriculum-Based Measures in Mathematics (CBM-Math) are among the strongest tools for documenting real-world math performance across multiple time points — a key convergent data source for dyscalculia evaluations.

What the meta-analytic evidence shows:

A meta-analysis of 29 studies with 27,907 students (grades 2–8) found that both primary CBM-Math task types are strong predictors of mathematics achievement (Codding et al., 2023, advance online pub., School Psychology Review):

MCAP (Math Concepts & Applications): r = .654 — stronger predictor overall; most aligned with comprehensive math achievement outcomes
MCOMP (Math Computation): r = .528 — valid for screening; may underpredict for assessments with high language demands
Overall CBM-Math: average correlation r = .584 with criterion measures — in the strong-to-very-strong range for an educational screening tool
Middle school students showed stronger CBM-math correlations than elementary students — particularly useful for upper-grade dyscalculia evaluations
Concurrent administration (within 1 month of criterion) yields stronger correlations than predictive data across longer intervals

For dyscalculia evaluations: MCAP probes are particularly valuable because they tap applied number sense — most directly relevant to Domain 3 (Number Sense) and Domain 4 (Math Reasoning) in the five-domain framework. MCOMP probes document computation fluency in an ecologically valid, repeated-measure format. Include both when available. Note: MCOMP may underestimate math skill for students whose primary deficit is language-mediated reasoning rather than computation.

Using CBM as convergent data in FIE: When CBM-Math data is available from MTSS/intervention records, explicitly anchor formal score findings to real-world performance: "Math fluency scores in the Low range were consistent with curriculum-based measures showing [X] digits correct/minute, below the [grade] benchmark across [number] data points."

Source: Codding, R. S., Nelson, G., Kiss, A. J., Shin, J., Goodridge, A., & Hwang, J. (2023, advance online publication). A meta-analysis of the relations between curriculum-based measures in mathematics and criterion measures. School Psychology Review, 54(3), 275–290. https://doi.org/10.1080/2372966X.2023.2224055 (Advance online publication 2023)

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Texas Policy — Dyscalculia & SLD-Math Calculation / Math Problem Solving

Texas does not have a separate dyscalculia eligibility category. Students are identified under SLD — Math Calculation and/or SLD — Math Problem Solving under TAC §89.1040 and IDEA 2004. The term "dyscalculia" may be used in evaluation reports, eligibility documents, and IEP paperwork — this is explicitly permitted under the OSERS Dear Colleague Letter (October 23, 2015), which clarified that nothing in IDEA prohibits the use of the terms dyslexia, dysgraphia, and dyscalculia in these documents. Using the term does not create a separate eligibility category; it names the pattern of need within the SLD framework.

HB 3928 (88th Leg., 2023) addressed dyslexia and dysgraphia specifically; dyscalculia was not named in the statute. However, the same underlying principle applies — the OSERS DCL permits naming dyscalculia, and TEA has not issued guidance prohibiting it. The ARD committee retains authority to name the specific learning disability pattern in evaluation documents.

Eligibility determination: SLD in Math Calculation is appropriate when the pattern reflects automaticity and/or procedural calculation deficits. SLD in Math Problem Solving is appropriate when applied math reasoning is the primary area of adverse educational impact. Both may be identified simultaneously when the data support both areas. The multidisciplinary team — not the diagnostician alone — makes this determination, with the diagnostician providing the evaluation data and pattern analysis that informs the ARD committee's decision.

Schreuder framework caveat: The five-domain convergent pattern framework used on this hub (Schreuder, TEDA 2026) is a clinical organizational tool. It is not an official TEA-adopted protocol. Eligibility decisions must be grounded in the IDEA SLD criteria, the student's educational need, exclusionary factors, and the preponderance of data — not in a single framework's pattern threshold.

Sources: TAC §89.1040; IDEA 2004 §614; OSERS Dear Colleague Letter (October 23, 2015); HB 3928 FAQ (TEA, 2023); TEA Guidance for the Comprehensive Evaluation of SLD (January 2025); Schreuder, TEDA 2026

Dyscalculia Reference

Texas Policy — Dyscalculia & SLD-Math Calculation / Math Problem Solving