CALT Reading Fluency and Decoding Development Flashcards

A student with dyslexia demonstrates accurate but labored single-word decoding and reads connected text at 68 WPM with 94% accuracy. According to Ehri's phase model, what is the most precise characterization of this student's decoding profile, and what instructional priority does it imply?

Answer: The student shows a fluency deficit despite adequate decoding accuracy, suggesting underconnected orthographic representations; instruction should emphasize repeated reading of decodable text to build sight-word automaticity.

A student with adequate accuracy but slow, effortful reading and below-benchmark fluency (typically 90+ WPM by late elementary) most likely has weakly specified orthographic representations — they can phonologically recode but have not formed the automatic orthographic mappings that allow fluent word recognition. This is distinct from still being in the full alphabetic phase (which would show accuracy errors). Ehri's model predicts that fluency emerges when repeated, accurate encounters consolidate orthographic representations into sight words. Repeated reading of decodable text directly targets this mechanism.

During a RAVE-O intervention session, an academic language therapist uses 'word webs' to build semantic richness around core words. Which theoretical mechanism BEST explains why this approach simultaneously supports decoding fluency, beyond its obvious vocabulary benefits?

Answer: Rich semantic connections create additional retrieval pathways for orthographic representations, reducing the threshold for automatic word recognition.

RAVE-O is grounded in the view that orthographic representations become more robustly stored when they are multiply connected — to phonology, morphology, semantics, and syntax. Wolf's connectionist framework holds that a word node with rich semantic links has a lower activation threshold, meaning it is retrieved more quickly and automatically. This directly supports fluency. Option D describes a compensatory guessing strategy, which RAVE-O explicitly rejects as a fluency mechanism. Option A misapplies working memory theory, and Option C incorrectly invokes the phonological loop as the operative mechanism.

A 4th-grade student reads pseudowords like 'strench' and 'squalp' accurately but reads real multisyllabic words like 'instrument' and 'conscience' with frequent errors and self-corrections. Which of the following BEST accounts for this dissociation?

Answer: The student has adequate phoneme-grapheme knowledge but relies on partial-cue reading for familiar-looking words, bypassing full phonological decoding.

This dissociation — strong pseudoword decoding paired with errors on real multisyllabic words — is a hallmark of partial-cue or 'glance-and-guess' reading. Because real words activate memory traces from prior (imperfect) exposures, the student short-circuits full phonological decoding and retrieves a similar-looking familiar word instead. Pseudowords have no such stored competitors, forcing full sequential decoding. Option B is plausible but RAN deficits affect fluency rate, not accuracy patterns in this way. Option C is incorrect because morphological processing issues would also affect pseudowords with affixes. Option D contradicts the strong pseudoword performance.

Research by Torgesen et al. (2001) on intensive intervention for older students with severe dyslexia found that decoding accuracy improved substantially but reading fluency remained significantly below age expectations. Which of the following BEST explains this persistent fluency deficit and has the strongest evidence base for addressing it?

Answer: Accurate decoding and automatic word recognition are dissociable skills; fluency requires thousands of additional exposures to build orthographic automaticity that intensive short-term intervention cannot fully supply.

Torgesen's landmark study demonstrated that even 67.5 hours of intensive, explicit phonics instruction could bring decoding accuracy near grade level, yet fluency remained impaired. The explanation with the strongest theoretical and empirical support is that automaticity requires massive amounts of practice with correctly decoded words — far more than any short-term intervention can provide. Share's self-teaching hypothesis and Ehri's orthographic learning theory both predict that each successful decoding attempt contributes incrementally to orthographic representation, and older students with histories of reading failure have profound 'print exposure deficits.' Option A overstates neurological constraints. Option B has no supporting evidence. Option D conflates RAN as a causal explanation when it is more likely a correlated marker.

An academic language therapist is interpreting a student's CTOPP-2 profile. The student shows average Phonological Awareness and Phonological Memory composite scores but a severely impaired Rapid Symbolic Naming composite. According to the 'double-deficit hypothesis' (Wolf & Bowers), which reading profile is this student MOST likely to exhibit, and what instructional adjustment is indicated?

Answer: The student likely has a single deficit affecting fluency more than accuracy; intervention should prioritize repeated reading procedures and timed fluency-building activities alongside ongoing phonics instruction.

Wolf and Bowers' double-deficit hypothesis identifies two partially independent core deficits in dyslexia: phonological processing and naming speed (RAN). Students with only a RAN deficit (single-deficit subtype) typically show adequate decoding accuracy but marked fluency impairment — their slow lexical access timing disrupts the automatic, fluent reading required for comprehension. This student's intact phonological scores and impaired RAN places them in the single-deficit (naming speed) subtype. Intervention for this subtype should directly target fluency — repeated reading, timed practice — in addition to continued phonics work, rather than intensive phonological remediation alone. Option B describes a double-deficit profile. Option D incorrectly dismisses RAN as irrelevant to reading.

A therapist is conducting an error analysis of a student's oral reading and notices the student consistently misreads vowel digraphs (e.g., reads 'bread' as /briːd/, 'great' as /grɛt/) but correctly decodes all consonant clusters and single vowel graphemes. This pattern is MOST consistent with which of the following and what does it suggest about instructional sequence?

Answer: Incomplete consolidation of the 'vowel team' layer of the alphabetic code; instruction should explicitly teach the multiple pronunciations of each vowel digraph using a structured, cumulative sequence before advancing to morphological analysis.

Vowel digraphs represent the most complex layer of the English alphabetic code because many (e.g., 'ea') have multiple pronunciations that must be learned as separate correspondences ('bread' /ɛ/ vs. 'bead' /iː/ vs. 'great' /eɪ/). A student who accurately handles consonant clusters and single vowels but consistently errors on vowel teams has progressed through earlier code layers but has not yet consolidated vowel team correspondences. This is a precise, instructional target within a structured literacy framework. The error pattern is systematic (not random), ruling out Option C. Option A misidentifies the locus — phoneme-level PA deficits present differently. Option D is incorrect; vowel digraph mastery is expected well before 5th grade.