**Johnsburg CUSD 12 · Johnsburg, Illinois**

Ringwood Primary School, a public elementary school, used LitLab’s curriculum-aligned decodable texts to close the gap between phonics instruction and fluent, independent reading.

![Ringwood Case Study at a glance](https://storage.googleapis.com/litlab-assets/blog/2026_4_16_ringwood_case_study/image1.png)

[**👉 Read the full case study here**](https://storage.googleapis.com/litlab-assets/Shareables/LitLab_Ringwood_case_study.pdf)

## 2025–26 School Year

Ringwood Primary School, part of Johnsburg Community Unit School District 12 in Johnsburg, Illinois, serves approximately 300 students across grades K–2.

Like many schools implementing structured literacy, Ringwood’s educators had adopted UFLI Foundations as their core phonics curriculum, but they faced a persistent gap: students were learning phonics skills in isolation and struggling to translate that into fluent reading.

In the 2025–26 school year, Ringwood partnered with LitLab to provide teachers with curriculum-aligned decodable texts that directly reinforce UFLI lesson objectives.

After one semester of implementation, a comprehensive survey of 20 educators revealed striking results across every dimension measured: student skills, teacher satisfaction, and instructional alignment.

This case study presents the full picture of Ringwood’s implementation: the challenge, rollout strategy, measured impact, and teacher feedback.

---

## Results at a Glance

![Ringwood Case Study Results Survey Graphic](https://storage.googleapis.com/litlab-assets/blog/2026_4_16_ringwood_case_study/image2.png)

## The Challenge: Phonics Skills Without Transfer

Ringwood’s instructional leaders identified a familiar pattern: students performed well during explicit phonics instruction but struggled to apply those skills when reading connected text.

The gap between “knowing the sounds” and “reading fluently” was persistent across grade levels.

![Director of Curriculum and Instruction reading impact quote](https://storage.googleapis.com/litlab-assets/blog/2026_4_16_ringwood_case_study/image3.png)

This is a well-documented challenge in structured literacy implementation. Phonics instruction
teaches students to decode individual words, but the transfer to fluent reading requires extensive
practice with texts that are well-aligned to instruction. Without that bridge, students develop
decoding strategies but struggle to translate it into fluent, automatic reading.

Ringwood needed decodable texts tightly aligned to their specific phonics programs’ scope and
sequence, not decodables aligned to a different phonics program. And they needed students to
actively practice reading aloud those decodables so that they could apply exactly what they’d just
been taught.

---

## The Solution: Curriculum-Aligned Reading Practice

LitLab stood out to Ringwood’s leadership because of its direct, lesson-level alignment to Ringwood’s chosen phonics program, UFLI Foundations. Rather than offering a generic library of decodable texts, LitLab maps every story to specific UFLI lessons, ensuring that students encounter only phonics patterns they have already been taught. This tight curriculum alignment was the decisive factor in adoption.

> “The decodables were able to focus on the UFLI skill of the week… it has strong decodability rather than students being introduced to words they have not been taught to decode yet.”  
> — Dawn Barrett

Beyond alignment, LitLab provided Ringwood teachers with tools to personalize and differentiate instruction. The custom story generator allowed teachers to create decodables featuring student names and interests, a feature that Dawn specifically credited with boosting engagement. The digital student practice mode gave students the ability to read independently on Chromebooks and iPads. And the platform’s print-ready formats made it easy for teachers to send decodable texts home for additional practice.

Critically, 95% of surveyed teachers agreed that LitLab saves them time finding high-quality instructional materials. Time that was previously spent searching for decodables that matched their scope and sequence, often unsuccessfully, was able to be repurposed and put towards students.

## Lightweight Rollout, Wide Classroom Impact

Dawn championed a thoughtful approach for Ringwood’s rollout to best fit their small district size while minimizing disruption and building internal expertise. LitLab offered Ringwood a virtual onboarding at the beginning of the school year. Dawn prioritized this training for Ringwood’s two MTSS (Multi-Tiered System of Supports) leaders. These leaders became the school’s resident LitLab experts, and brought LitLab to their teaching staff.

This lightweight approach worked. Ringwood’s teachers reported high ease of use across all dimensions, with 95% of teachers saying that it was easy to find stories, and 85% reporting that it was easy to assign practice aligned to their curriculum

## Flexible Use Across Grade Levels and Settings

One of the most notable findings from Ringwood’s implementation is how naturally teachers adapted LitLab to different instructional contexts across the foundational literacy continuum:


👉 **Second Grade:** Teachers used LitLab decodables primarily as independent center work, giving students the autonomy to read curriculum-aligned texts on their own during literacy rotations.

👉 **Kindergarten and First Grade:** Teachers used LitLab in small-group instruction, reading decodables together with students in guided contexts to scaffold fluency development.

👉 **SPED, Title I, and MTSS:** Specialists used LitLab to supplement intervention sessions. One SPED resource teacher noted that she gives students choices among several LitLab books and that “they like having control over that portion,” building agency alongside skills.

👉 **Multilingual Learners:** Ringwood’s ML teacher reported that her students “are always asking
me to print off more books for them to practice at home,” a strong signal that the texts are accessible and engaging even for students navigating a new language.

👉 **Home Practice:** Multiple teachers reported sending LitLab decodables home with students, extending practice beyond the school day. One first-grade teacher shared that her “students love the decodables and share they practice them often at home.”


---

## Impact: Stronger Student Outcomes and Actionable Data

Teachers reported impact across six dimensions:

| Student Outcome | % Agree |
|----------------|--------|
| Develop stronger phonics and decoding skills | 100% |
| Improve performance on UFLI-based weekly assessments | 94% |
| Stay engaged with reading practice | 90% |
| Build confidence and agency as readers | 90% |
| Improve reading fluency and accuracy | 85% |
| Increase reading comprehension | 80% |

Teachers are seeing LitLab’s impact show up directly on the assessments they already trust. With 94% agreeing that students improved on UFLI-based weekly assessments, the gains are visible in the same formative measures Ringwood uses to track phonics progress.

That assessment signal is reinforced by a broader instructional shift. 100% of teachers agreed that LitLab developed stronger phonics and decoding skills, which supports LitLab’s role in helping students move beyond isolated skill work into real reading.

---

## Student Data That Is Actually Actionable
Teachers were also asked how well LitLab delivers on its core promises to educators. The results confirm strong alignment with instructional priorities:

| Value Proposition | % Agree |
|------------------|--------|
| Content aligns well with our core phonics curriculum | 95% |
| Saves me time finding high-quality instructional material | 95% |
| Supports differentiation in foundational literacy | 95% |
| Improves the quality of student independent practice | 94% |
| Student data helps me monitor and respond to student needs | 92% |

The strongest signal here is how consistently teachers point to data as actionable, not just informative. With 92% agreeing that student data helps them monitor and respond to needs, LitLab isn’t just surfacing progress, it’s tightening the feedback loop between practice and instruction. Teachers can see skill-level performance tied directly to phonics patterns and immediately adjust grouping, pacing, or intervention without needing to triangulate across multiple tools. That shifts data from something retrospective to something operational, embedded in daily instructional decisions rather than reviewed after the fact.

## In Their Own Words: Teacher Perspectives
Teachers were also asked how well LitLab delivers on its core promises to educators. The results confirm strong alignment with instructional priorities:

> “LitLab is a great resource for independent practice with UFLI skills. They are also great books to print and send home.”  
> — 1st Grade Teacher  

> “My students love the decodables. They practice them often at home.”  
> — 1st Grade Teacher  

> “The students seem to really enjoy the books… My ML students are always asking for more.”  
> — ML Teacher  

> “Students are engaged… they like having control over their reading choices.”  
> — SPED Resource Teacher  

> “It’s a great program to practice phonics skills independently.”  
> — 2nd Grade Teacher  

---

## Looking Ahead

Ringwood Primary’s experience demonstrates what happens when practice is tightly aligned to a school’s phonics scope and sequence: students transfer skills from instruction to reading, teachers save time and trust the materials, and the gap between “learning phonics” and “reading fluently” begins to close. Every teacher surveyed agreed that LitLab strengthens students’ decoding skills. Teachers across every role — gen ed, SPED, Title I, MTSS, and multilingual learner — found ways to integrate the platform into their instruction. And students are not just building decoding and fluency skills; they’re building confidence, independence, and a genuine love for reading.

## Methodology

Data collected via online survey administered January 2026 after one semester of LitLab implementation. Twenty (20) respondents across grades K–2, including classroom teachers, SPED resource teachers, a Title I reading teacher, MTSS specialists, a multilingual learner teacher, and a student teacher. Student outcomes and value propositions measured on a Likert agreement scale. Behavioral observations were multi-select. Ease of use measured on a four-point scale. Open- ended responses from site lead collected via structured interview.

See how Ringwood Primary used curriculum-aligned decodables to improve fluency, engagement, and decoding skills in just one semester.

Case Study: Ringwood Primary School

There's a lot of AI in EdTech right now. Some of it is genuinely exciting. Some of it is a chatbot with a reading skin on top — content that isn't actually tied to a curriculum, a scope and sequence, or what a teacher taught that morning.  As a provider of educational materials that are intended to be used by early learners, it's critically important to be transparent about how AI is used and incorporated into educational materials. 

So, how does LitLab use AI? What's our philosophy?

The short version: We build tools that leverage emerging AI to handle the tedious parts: materials creation, curriculum alignment, and data analysis. Teachers get their time back and students get better-aligned practice. Teachers stay in control of the materials and instructional goals. Students never interact with a general-purpose AI. Every AI decision we make runs through one filter: does this actually serve the student's reading development?

That perspective comes directly from what the Science of Reading tells us about how young children learn to read.


## Coherence Is the Standard

The Science of Reading is a growing body of evidence about how children learn to read. That research points consistently to reading growth being supported by a systematic process — one where phoneme awareness, phonics, fluency, vocabulary, and comprehension build on each other in a predictable sequence. Effective instruction follows that sequence explicitly, and practice needs to reinforce exactly what instruction has taught.

That alignment is what makes practice work. Research shows a 19% greater efficacy delta for aligned practice in Tier 1 instruction, and 27% in Tier 2 intervention. More practice isn't inherently better. More *aligned* practice is.

This is what makes AI tricky in early literacy. A tool that generates reading content without enforcing scope and sequence doesn't just fall short, it actively works against the coherence that structured literacy depends on. Every minute a student spends on content that doesn't match what they've been taught is a minute that isn't reinforcing the lesson.

Word recognition and phoneme sensitivity are among the strongest predictors of early reading development \[3\]. Decoding and oral language skills independently predict reading comprehension as early as second grade \[2\]. The stakes are real: students who don't read proficiently by third grade are four times more likely to leave school without a diploma \[1\].

Getting early literacy right matters. And that means getting the tools right, too.



## The Problem with Most AI Decodable Generators

General-purpose AI, including tools that market themselves as decodable generators, can produce beginner-friendly text. What they can't do is enforce a phonics progression. They don't track which sound-spelling correspondences a student has been taught. They don't control for irregular words or patterns beyond a student's instructional level. They don't know what lesson happened this morning.

Decodability measures the percentage of words in a text that a student can decode using only the phonics patterns they've been explicitly taught — according to their specific scope and sequence. A word that's decodable in UFLI Foundations at lesson 40 might not be decodable in Fundations at the same point. True decodability isn't a fixed property of a text. It depends entirely on what a student has been taught, and when.

That's what makes most AI-generated content fall short. General-purpose AI has no concept of a scope and sequence. It can't know which sound-spelling correspondences your students have learned, which patterns are still ahead, or which words need to be pre-taught. The result looks like a decodable but isn't.

LitLab stories average 85%+ decodability, scored against the specific program a school has adopted. Nearly every word a student encounters has already been taught, in the right sequence, by their teacher. ChatGPT-generated texts, by comparison, score around 10%.

That gap matters. It isn't a leveled reader either. It's just words — with no verified skill alignment, no reliable Lexile, no A-Z level. It looks like instructional material and isn't. This is exactly the kind of incoherence that the Science of Reading asks us to move away from.



## How We Use AI at LitLab

LitLab uses AI across four areas: generating decodable content, extending aligned practice to students, enabling accessibility (e.g. text to speech), and analyzing oral reading fluency. In every case, the AI works within strict curriculum constraints. Teachers stay in control. Students never interact with a general-purpose AI.

### Custom Decodable Generators

LitLab's [decodable generators](https://www.litlab.ai/create) are built on a proprietary Scope & Sequence Alignment system. Teachers can generate three types of content: fiction stories, nonfiction passages, and reader's theater scripts designed for partner or group reading. Every format is phonics-aligned to the same scope and sequence — so the skill focus stays consistent whether students are reading independently or performing with a partner.

Every generated decodable is bound by a specific phonics skill focus, controlled vocabulary lists drawn from the teacher's chosen program, and age-appropriate content parameters.

When a teacher generates a decodable, the AI produces a draft. The teacher reviews it, edits if needed, and decides whether to assign it. Finding the right decodable text used to mean endless searching for something that came close enough to the lesson — LitLab handles that heavy lifting, so teachers can create and assign curriculum-aligned stories directly, confident that every text reinforces exactly what they taught. 

Teachers can assign decodables digitally or print them for hands-on reading. Five print formats are available (single image, read and draw, fully illustrated, compact story sheet, and booklet) so teachers can use them in the way that best fits their classroom.

LitLab also maintains a library of 1,500+ pre-made grab-and-go decodables, each built by literacy specialists and reviewed before publication. AI-generated and human-reviewed content work together within the same alignment system.

### Student-Initiated Practice: Aligned Reading, On Demand

One of the hardest problems in early literacy isn't the whole-group lesson — it's what happens after it. Students who finish early, students who want to reread, students who need more repetitions with a specific skill before it clicks. Teachers can't generate new decodable material on demand for every student who needs it. Until recently, that meant reaching for whatever was on the shelf, which often meant reaching for something misaligned.

LitLab lets students generate their own decodable stories, but only within the exact same curriculum constraints their teacher already set.

When a student requests a new story, the system doesn't open a general-purpose AI and let them ask for anything. It reads the skill focus and scope and sequence from their active assignment and generates a new, original story within those same bounds. The phonics patterns are the same. The controlled vocabulary list is the same. The instructional level is the same. The only thing that changes is the story itself.

![Student interface for skill and Scope-and-sequence alignment in the decodable generator](https://storage.googleapis.com/litlab-assets/blog/2026_03_06_ai_science_of_reading/image1.png)

To make the student-initiated generation safe and improve accessibility, we significantly constrain the student interface. There is no text input, no open field, no prompt. Students can make three visual choices: a character, a name, and a setting — from curated, age-appropriate options presented as picture cards. That's the full extent of their input. The rest of the prompt is fixed by the system, and the curriculum constraint is always present. There is no way for a student to ask the AI anything.

This matters because in structured literacy, encountering the same phonics patterns across different texts builds the automaticity that fluency depends on. The Science of Reading is clear that massed, varied practice with high-decodability text accelerates pattern recognition in ways that a single exposure can't. The student decodable generator enables additional reading practice at the skill level the teacher has assigned for reading practice. In the 25-26 school year, students on LitLab have read over 240,000 additional stories created by themselves! Teachers regularly report it as one of their students' favorite moments in the platform.

Teachers retain full visibility. Student-generated stories appear in the same assignment view, and fluency recordings from those sessions feed back into the same skill-level data teachers already use. Nothing about the data model changes — the fluency practice simply has more surface area.

This is what curriculum-aligned AI practice should look like: not a chatbot, not a leveled reader dispenser, but a system that extends a teacher's instructional intent into the moments between lessons.

### AI Fluency Analysis

When students read aloud in LitLab, their recordings are analyzed at the word and phoneme level. The platform surfaces accuracy data, comprehension scores, and reading rate — all mapped back to the specific skills in the teacher's scope and sequence through LitLab's Skill Maps.

Teachers can listen to every recording. They can validate or overwrite any automated analysis. Student recordings are processed for reading analysis only. They are not used by LitLab or by any of our AI vendors to train, fine-tune, or improve machine learning models. Our vendor agreements explicitly prohibit this.

AI surfaces the information. The teacher decides what to do with it.

### What AI Doesn't Do at LitLab

- **Students never interact with a general-purpose AI.** LitLab is not a chatbot, and student-facing story creation involves no text input of any kind. Students make three visual choices — a character, a name, and a setting — from curated, age-appropriate options. That's it. The rest of the prompt is fixed by the system, and the curriculum constraint is always present. There is no way for a student to ask the AI anything.
- **Student data is never used to train AI models.** Our vendor agreements explicitly prohibit this.
- **All AI-generated content is constrained by curriculum.** Always.

---

\[1\] Hernandez, D.J. (2011). *Double Jeopardy: How Third-Grade Reading Skills and Poverty Influence High School Graduation.* The Annie E. Casey Foundation. [https://files.eric.ed.gov/fulltext/ED518818.pdf](https://files.eric.ed.gov/fulltext/ED518818.pdf)

\[2\] Kendeou, P., van den Broek, P., White, M.J., & Lynch, J.S. (2009). Predicting reading comprehension in early elementary school: The independent contributions of oral language and decoding skills. *Journal of Educational Psychology, 101*(4), 765–778.

\[3\] Muter, V., Hulme, C., Snowling, M.J., & Stevenson, J. (2004). Phonemes, Rimes, Vocabulary, and Grammatical Skills as Foundations of Early Reading Development: Evidence From a Longitudinal Study. *Developmental Psychology, 40*(5), 665–681.

AI is everywhere in edtech — but not all of it belongs in an early literacy classroom. Here's how LitLab uses emerging AI to support the Science of Reading, and the principles that keep teachers in control.

AI and the Science of Reading

A pattern is emerging across schools transitioning to the Science of Reading: students pass phonics assessments but stall when reading connected text.

> "Our kids are doing well on skills in isolation — but they freeze up when you put them in front of connected text. They've learned the parts of a bike but never actually practiced riding one."  
> — Literacy Director, mid-sized district in Illinois

> "We had plenty of decodables, but when I actually looked at what kids were reading during centers, it had nothing to do with what their teacher had taught that week."    
> — Curriculum Coordinator, K–8 school in New York

The gap tends to surface during a classroom walkthrough, a coaching visit, or a data meeting where the numbers don't quite tell the story you expected. Students have been assessed, and the phonics data looks solid. They're moving through the scope and sequence. Teachers have been trained on the program. And then an adult sits down with a first or second grader and asks them to read a passage aloud — and what comes back is slow, effortful, word-by-word reading that doesn't resemble fluency at all.

The phonics instruction is doing what it's supposed to do, but something still isn't quite working for your students.


## The Difference Between Decoding a Word and Reading Fluently

Decoding and reading fluency are related but not the same skill. Decoding is what happens when a student applies a phonics rule to work out an unfamiliar word. They see a word, say the sounds, blend them, and arrive at the word. Decoding requires conscious effort and attentional resources. Fluency is what happens once a word has been encountered enough times that recognition becomes automatic — the student sees a word and can retrieve it instantly. When word recognition is automatic, cognitive resources are freed up for what reading is actually for: making meaning from text.

The path from decoding to automaticity runs through practice: repeated exposure to words and patterns in connected text, at the right level of difficulty, often enough that recognition stops requiring effort. Research puts the number of exposures needed to consolidate a new phonics pattern at 4–6. Most classrooms provide 1–2 during instruction. The rest has to come from somewhere, and in most schools, that gap simply doesn't get filled.

What tends to happen instead is this. A teacher delivers an explicit, well-structured phonics lesson. Students practice the skill in isolation — sorting pictures, reading word cards, writing words. Then they move to independent reading, centers, or small-group work, and the texts they practice with aren't tied to the lesson that just happened. They might be leveled readers left over from before the SoR transition, decodables from a bin that hasn't been sorted by skill, or passages from a supplemental program that follows a different scope and sequence. Practice is happening, but it's not reinforcing what the instruction taught. The connection between the lesson and the reading is loose, and sometimes it isn't there at all.

This is what literacy researchers and curriculum designers sometimes call the coherence problem. Instruction, practice, and assessment are operating in parallel rather than as a connected system — and the students who feel that disconnection most acutely are typically the ones who most need coherence to stick.


## Why Aligned Practice Is Harder to Provide Than It Sounds

Most teachers understand this problem instinctively. They know their students need more connected-text reading that's tied to what they've been teaching. The obstacle isn't awareness. It's materials — specifically, the absence of an unlimited, always-ready supply of connected texts matched to each lesson in the scope and sequence, at varying difficulty levels, appropriate for students at different levels in the same classroom.

Phonics programs are instruction systems. They provide the what and the when of phonics teaching. But oftentimes they don't include a scalable practice layer — enough curriculum-aligned decodable texts for every student to get meaningful reading time at their current skill level, with data showing whether that practice is working.

So teachers do what they need to do: they search, print, and improvise. Some schools have built good decodable libraries. But even well-resourced programs run thin when you account for the range of skill levels within a single classroom, the pace at which students move through a scope and sequence, and the sheer volume of reading repetitions needed to build automaticity.

The research on what alignment actually buys is now cleaner than it's ever been. A randomized controlled trial in Knox County, Tennessee (Tennessee SCORE + Accelerate, 2024–25) tested the question: Does it matter whether tutoring materials align with the student's Tier 1 classroom program? Both groups received high-quality, high-dosage tutoring. The only variable was alignment. Students with aligned materials outperformed the control group by 0.12 standard deviations, equivalent to 1.3 additional months of learning. The effects were even stronger for students in the bottom 10% of performers.

More reading practice isn't inherently better. More *aligned* reading practice is better. That distinction matters enormously when you're making decisions about how students spend instructional time.

The core phonics program a district has invested in is probably working. What it doesn't include is a scalable practice & evaluation layer — and that's exactly what LitLab provides.

## What Coherent Fluency Practice Actually Requires

When districts examine the fluency gap closely, three things tend to be missing at once.

The first is texts that are genuinely decodable at the student's current instructional level. Decodability isn't a fixed property of a piece of text — it's a relationship between the text and what a specific student has been taught. A story that's 90% decodable for a student in UFLI Lesson 45 might be far less decodable for a student in Lesson 28, even if the text looks "easy." Many libraries are organized by reading level or Lexile, not by specific lessons in the scope and sequence, which means the teacher has to do the alignment work manually or assign texts that don't match what students know.

LitLab's library of 1,500+ decodable stories and its AI-powered story generator are built around a scope and sequence alignment engine that spans UFLI, CKLA, Fundations, Reading Horizons, Benchmark, Superkids, and other major programs. Every story carries a decodability score calculated against the specific program a school uses: the percentage of words that a student at a given lesson can decode using only the patterns they've been taught. LitLab stories average 85%+ decodability against the assigned program. For comparison, texts generated by general-purpose AI tools typically score around 10% — they look like decodables but are functionally leveled readers, which ask students to guess, memorize, or skip unfamiliar words rather than decode them.

[👉 Learn more about AI and the Science of Reading here](https://www.litlab.ai/blog/ai-and-the-science-of-reading-how-litlab-integrates-emerging-tech-with-rigorous-reading-practice)

The second thing missing in many classrooms is simply enough repetition. Automaticity requires encountering the same patterns across many different texts, in varied contexts, enough times that recognition no longer requires conscious effort. This is difficult when only a handful of decodables are available at a given skill level. When the bins run out, aligned practice stops. LitLab's generator means the supply of appropriately aligned texts is effectively unlimited — teachers can generate new stories tied to a specific skill, with custom keywords, in fiction or nonfiction formats, and assign or print them immediately. Students can also generate their own stories at their assigned skill level, choosing characters and settings, which tends to produce more reading motivation than a fixed library alone can sustain.

<Callout icon="📚">

**In the 2025–26 school year, students created and read over 240,000 extra stories on LitLab for additional reading practice.** Each additional moment of self-directed reading practice was aligned to the skill their teacher assigned. 

</Callout>

The third missing piece is skill-level data generated from actual reading — not quarterly benchmarks, but evidence from daily practice. When a student reads aloud in LitLab, their recording is analyzed at the word and phoneme level. The platform surfaces accuracy, reading rate, and comprehension scores, all mapped back to the skills in the teacher's scope and sequence. Teachers can listen to any recording, review the analysis, and see at a glance which students are consolidating a skill, which are ready to move forward, and which are still making consistent errors on specific patterns. That information feeds directly back into instructional decisions, and it's available the next day, not six weeks later.

For English learners and multilingual students, who often carry a heavier cognitive load during reading practice, LitLab offers Spanish-language directions and comprehension questions to reduce interference and keep the focus on the reading itself.


## Coherence as a Design Principle

The fluency gap that district leaders are seeing — students who decode but don't read smoothly — is not primarily a teaching problem. It's a systems problem. Instruction is happening. Practice is happening. But because the practice isn't tightly coupled to the instruction, the repetitions students are getting aren't building toward automaticity as efficiently as they should be.

Closing that gap requires the different parts of the literacy program to function as a coherent system: practice tied to what was taught, data generated from practice in a format that's instructionally useful, and instructional response informed by that data on a short enough cycle to matter. That's the design principle behind LitLab — not to add another layer to what teachers are already managing, but to close the loop between phonics instruction and fluent reading.

Students who are working hard in phonics lessons and still reading haltingly from connected text aren't failing to learn. They're waiting for enough of the right kind of practice. The question for school and district leaders is whether the infrastructure is in place to give them that practice at the right level, in enough volume, starting tomorrow.

--

*LitLab serves 5000+ school sites and 400,000+ students across K–5. It is ESSA Tier IV certified and aligns to UFLI Foundations, CKLA, Fundations, Reading Horizons, Superkids, Benchmark, and other major phonics programs. [👉 Learn More](https://www.litlab.ai/schools) to see how it fits with your current program.*

Learn how LitLab bridges the gap between phonics instruction and fluency practice through coherent, curriculum-aligned reading practice grounded in the Science of Reading.

Why Students Can Decode But Struggle to Read Fluently

When it comes to early reading instruction, not all decodables are created equal.

A great decodable text is intentionally crafted so that the _vast majority of words_ align with what students have been explicitly taught, allowing them to successfully sound out and apply new phonics knowledge in context.

Below, we'll unpack the key features of a high-quality decodable using a LitLab story aligned to **UFLI Lesson 13 (/d/):** [Dot and Dad](https://www.litlab.ai/library/cm6fbp55n000hqobkwoxvznqv?sequence=ufli&ref=gallery_item_staff_pick)**.**

### Aligned to a Phonics Sequence

Every strong decodable text is anchored to a systematic phonics scope and sequence, such as **UFLI Foundations** or **CKLA**, ensuring that the words students encounter can be sounded out using previously taught patterns.

For example, if students have learned short vowel sounds and the letters _d_ and _t_, a sentence like _"Dad did it!"_ allows them to apply those skills successfully. This alignment gives students the structure they need to read independently and confidently, without guessing.

Research shows that the **degree of decodability** in a text strongly predicts both _reading accuracy and fluency_. In a large-scale study, **Saha et al. (2021)** found that text decodability uniquely predicted students' oral reading performance, even after accounting for decoding ability.

Across thousands of LitLab stories:

-   **Median decodability:** 96%
-   **All decodables** are aligned to a specific lesson in a phonics scope and sequence (from early CVC to vowel teams)

This tight alignment helps students apply new sound–spelling patterns without encountering untaught ones. Every LitLab story is fully aligned to a phonics sequence, ensuring that most words can be successfully sounded out.

![Example of aligned decodable text 1](https://storage.googleapis.com/litlab-assets/blog/2025_10_15_great_decodable/body_fig1.png)

![Example of aligned decodable text 2](https://storage.googleapis.com/litlab-assets/blog/2025_10_15_great_decodable/body_fig2.png)

### Focuses on a Target Skill — with Natural Repetition

A hallmark of great decodables is the **intentional density of skill words**.

Decodables should provide natural, frequent exposure to the target phonics pattern being practiced.

For example, if the lesson focuses on **\-ck**, the story might include several words like _duck_, _chuck_, and _tuck_. This repetition gives students multiple chances to apply the same phonics feature in varied contexts, building automaticity without sacrificing story flow.

The best decodables weave these repetitions seamlessly into engaging sentences, so practice feels like _real reading_, not drill.

### Non-Decodable Words Are Pre-Taught

Even the most controlled stories include a few words that can't yet be sounded out — such as _is_ or _the_ (often called **Heart Words**).

Most of the time, these are high-frequency words that have already been explicitly taught within the scope and sequence.

These words should be practiced _before reading_ so they don't interrupt decoding flow.

Pre-teaching them ensures that students can focus on applying the target phonics skill while still experiencing authentic, meaningful text.

![Pre-teaching example](https://storage.googleapis.com/litlab-assets/blog/2025_10_15_great_decodable/body_fig3.png)

![Picture supports comprehension](https://storage.googleapis.com/litlab-assets/blog/2025_10_15_great_decodable/body_fig4.png)

### Pictures Enhance the Narrative

In well-crafted decodable texts, illustrations **enhance comprehension without replacing decoding**.

Pictures help students connect meaning to the words they're reading and stay engaged, especially when a story includes new or conceptually rich details.

In the LitLab example above, students can decode the word _"it"_ and use the illustration to infer that _"it"_ refers to the jar. The word "_jar_" may not yet be decodable at early levels, so it is not included in the text. The image provides helpful context without serving as a guessing cue.

### Balanced, Engaging, and Teacher-Friendly

A high-quality decodable doesn't just support students. It supports _teachers_, too.

Beyond maintaining strong phonics control (typically **85–95% decodable**) and telling stories that make sense, great decodables make their structure transparent to the teacher.

Teachers should be able to easily see:

-   **Target skill words** — words that include the phonics pattern being practiced (e.g., _duck, pack, back_ for the **\-ck** skill)
-   **Non-decodable "story words"** — words not yet fully decodable but necessary for meaning
-   **High-frequency words** — previously taught sight words that reappear for fluency and familiarity

Clear categorization helps teachers preview texts, plan instruction, and pre-teach strategically, ensuring every story aligns with what's been taught.

**In LitLab,** each story clearly labels its target skill and categorizes all words by skill words, review words, high-frequency words, and non-decodable ("story") words. Teachers know exactly what students will encounter before reading.

This transparency keeps instruction consistent and empowers teachers to use decodables as both a reading and teaching tool, not just a text to hand out.

## Ready to Explore High-Quality Decodables?

A great decodable is more than controlled text. It's _purposeful practice_ that builds confident readers.

At **LitLab**, that balance is built in. Every story is:

-   Aligned to a phonics scope and sequence
-   Verified for decodability
-   Tagged with skill words, high-frequency words, and story words
-   Designed to make phonics practice both _accurate_ and _joyful_

By combining phonics precision, clear teacher supports, and engaging stories, LitLab makes it easy to choose texts that truly match instruction.

👉 **Explore high-quality decodable stories at [LitLab.ai](https://litlab.ai)**

_Written by: Drew McCann, K-3 Literacy Specialist and Head of Learning at LitLab.ai, and Jacqueline Ontell, Elementary Teacher, Special Education & Curriculum Development_

* * *

\[1\] Saha, N. M., Cutting, L. E., Del Tufo, S. N., & Bailey, S. (2021). Initial validation of a measure of decoding difficulty as a unique predictor of miscues and passage reading fluency. _Scientific Studies of Reading_, _25_(5), 404–418. [https://doi.org/10.1080/10888438.2020.1817093](https://doi.org/10.1080/10888438.2020.1817093)

Learn the key features of high-quality decodable texts that support student reading success and teacher effectiveness.

What makes a great decodable text?

LitLab was built to make high-quality decodable reading practice effortless for teachers, and that begins with aligning to the phonics instruction schools already trust. For many classrooms, that foundation is **UFLI Foundations**, a research-based phonics program grounded in the **Science of Reading** and widely used across K-3.

This post explains how **LitLab ensures precise, data-verified alignment with UFLI Foundations** through every word students encounter. Using decodability analysis across thousands of stories, you’ll see how **LitLab maintains over 95% decodability throughout the complete UFLI sequence**. The result is simple: teachers get rigorously aligned materials that fit their existing instruction, and students gain quality and engaging reading practice that builds confidence, fluency, and mastery one skill at a time.

## Why UFLI Alignment Matters

[UFLI (University of Florida Literacy Institute) Foundations](https://ufli.education.ufl.edu/foundations/) offers a structured scope and sequence that teaches phonics systematically from simple to complex patterns. Teachers using UFLI need materials that match that progression precisely.

According to research, the level of decoding difficulty in a text is a unique and significant predictor of both miscues and passage reading fluency (_Saha et al., 2021_). In other words, when students encounter phonics patterns they haven’t yet been taught, they’re more likely to struggle with accuracy and fluency during oral reading.

This highlights the importance of tightly controlled, skill-aligned texts—like those in LitLab—where decodability is optimized.

Practicing newly learned grapheme-phoneme correspondences (GPCs) in context helps solidify decoding skills. Research shows that students who practice taught GPCs in decodable texts apply more letter-sound knowledge strategies when reading less controlled or authentic texts later on (_Mesmer, 2008_). In short, highly decodable reading builds transferable skills.

That’s where **LitLab’s alignment with UFLI** makes a difference.

Every UFLI story in LitLab is built around a specific UFLI lesson, carefully controlling for phonics patterns so that students encounter only those they’ve been explicitly taught.

## How LitLab Ensures UFLI Decodability

At LitLab we've developed a **phonics-aware AI assistant** that helps us create decodable stories that adheres very tightly to the target skill and prior skills from the UFLI Foundations scope and sequence. **Each story in LitLab’s Grab-and-Go Decodable Library is created and evaluated by an educator who is an expert in the Science of Reading.**

A cornerstone of this process is ensuring high decodability. What is decodability? Decodability is the percentage of words that can be decoded by a student using the patterns a student has been taught up to that point. This concept is a cornerstone of UFLI Foundations and followed strictly for all LitLab stories.

We measure this using the same phoneme-grapheme correspondence progression defined by UFLI. The result: highly controlled texts that maintain readability, coherence, and instructional alignment.

## The Data: How Decodable Are LitLab Stories?

To quantify how closely LitLab aligns with UFLI, we analyzed thousands of stories across the entire UFLI sequence. The results speak for themselves.

### 1\. Median Decodability by UFLI Skill

How tightly aligned are LitLab’s stories to UFLI’s skills and pedagogy?

![Median Decodability by UFLI Skill](https://storage.googleapis.com/litlab-assets/blog/2025_10_10_ufli_alignment/body_fig1.png)

Not only does LitLab offer numerous stories for each UFLI skill, the data above shows that **across all 128 UFLI Lessons, LitLab stories maintain a median decodability above 90%**, with most skills exceeding 95%. Each point on this chart represents the median decodability for stories tagged to that skill, meaning that nearly all words in those stories can be decoded using that skill and prior knowledge.

This demonstrates **consistency across the full scope and sequence**, ensuring teachers can trust that LitLab stories remain tightly aligned from early short vowels through advanced vowel teams and r-controlled syllables.

### 2\. Story Decodability Distribution

How decodable are LitLab’s stories?

![Distribution of Story Decodability](https://storage.googleapis.com/litlab-assets/blog/2025_10_10_ufli_alignment/body_fig2.png)

The above figure shows the distribution by decodability for all UFLI-aligned decodables that are available to educators in LitLab’s Grab-and-Go Decodable Library. The higher the count of stories in a decodability bucket, the more stories LitLab has to offer teachers at that decodability level. First, notice that there are no stories in LitLab’s staff-curated grab-and-go decodable library with a decodability lower than 75%. **LitLab’s UFLI-aligned stories maintain a median decodability above 97%**, with fewer than 5% of all LitLab UFLI-aligned stories having a decodability below 86%.

In other words, **nearly all stories are highly decodable**, and even the lowest 5% maintain strong alignment to UFLI’s principles and pedagogy. This provides teachers flexibility to differentiate (beyond skill-level), by using the most controlled texts for early practice or slightly more open texts for fluency and comprehension work.

### 3\. Story Length vs. Decodability

But are all LitLab stories created equal?

![Story Length vs Decodability](https://storage.googleapis.com/litlab-assets/blog/2025_10_10_ufli_alignment/body_fig3.png)

The above scatter plot shows the decodability (y-axis) as a function of the number of words in each story (x-axis) on LitLab. The graph shows that **LitLab stories remain consistently decodable regardless of length**. Even as word count increases from early 30-word CVC stories to more advanced 400-word passages, decodability stays above 90%. An analysis shows the correlation between Word Count and Decodability was 0.06, which indicates no significant correlation between these two variables. This means teachers can confidently assign longer stories for fluency and comprehension without compromising their instructional practice.

## What This Means for Classrooms

For teachers, the takeaway is simple: **LitLab fits directly into UFLI-based phonics instruction without adding extra steps or guesswork.** Every decodable story in LitLab has already been analyzed for decodability, tagged by UFLI lesson, and verified to stay within the phonics patterns students have been taught.

Teachers can:

-   **Search by UFLI lesson or skill** to instantly find stories that reinforce that day’s instruction.
-   **Assign or print stories with confidence**, knowing every text meets rigorous decodability thresholds.
-   **Use decodability metrics** to choose the right level of challenge for each group or individual reader.
-   **Create new stories** with LitLab’s story generator, which automatically aligns to the same UFLI skill progression used in the Grab-and-Go Library.

For administrators, this alignment ensures **instructional consistency and data-backed quality** across classrooms. Schools can be confident that all decodable materials, whether created by staff or selected from LitLab’s library, follow the same structured phonics framework. This reduces variation between teachers, supports fidelity to UFLI, and strengthens overall reading outcomes.

In short, LitLab makes it easy to bring **rigorous, Science of Reading aligned practice** to every student. Teachers spend less time searching for the right materials and more time teaching. Students spend more time reading stories that match what they have learned, building both **accuracy and fluency** in authentic, engaging contexts.

Together, UFLI and LitLab provide the **structure and scalability** schools need to turn systematic phonics instruction into confident, joyful reading.

## Ready to See UFLI Alignment in Action?

Explore the full [UFLI-aligned Grab-and-Go Decodable Library](https://www.litlab.ai/gallery/v2?author=staff&sequence=ufli) and see how LitLab supports your district’s literacy goals with precise, consistent phonics practice.

_Written by: Drew McCann, K-3 Literacy Specialist and Head of Learning at LitLab.ai_

* * *

\[1\] Saha, N. M., Cutting, L. E., Del Tufo, S. N., & Bailey, S. (2021). Initial validation of a measure of decoding difficulty as a unique predictor of miscues and passage reading fluency. _Scientific Studies of Reading_, _25_(5), 404–418. [https://doi.org/10.1080/10888438.2020.1817093](https://doi.org/10.1080/10888438.2020.1817093)

\[2\] Mesmer, H. A. E. (2008). _Tools for matching readers to texts: Research-based practices_. New York, NY: Guilford Press.

See how LitLab maintains 97%+ median decodability across all 128 UFLI Foundations lessons — with the data to prove it. 

How LitLab Aligns to UFLI Foundations — Backed by Data

When working with early readers, decodable texts are a powerful tool to support phonics-based reading instruction. But even the most carefully constructed decodable story often contains a few words students haven’t yet fully mastered. That’s where previewing (or pre-teaching) comes in. Thoughtfully selecting which words to introduce before reading can make the difference between a choppy decoding experience and a confident, successful read. It is also a way to introduce unfamiliar vocabulary, helping students build strong comprehension of the text.

An analysis has shown that LitLab stories are highly decodable, with an average decodability greater than 95%, leaving just a handful of words in each story that may require previewing or pre-teaching with students. In this post, we’ll share a clear framework for selecting words to pre-teach using LitLab Stories as an example — but the principles apply across any decodable instruction.

## Why Preview Words?

-   **Fluency and confidence:** Removing stumbling blocks allows students to apply their decoding skills smoothly and prevents word guessing.
-   **Comprehension:** Knowing a key word’s meaning helps students follow the story or text without confusion.

## A Framework for Previewing Words

Here are the criteria we suggest when selecting 3–5 words to preview:

**1\. Out-of-sequence words**  
These are words that may be phonetically irregular (said, does, was) or phonetically regular (play, house, take), but haven’t been introduced yet in your phonics sequence. While LitLab stories are highly controlled to include word patterns and sight words already taught, these words sometimes appear in LitLab Stories and other decodables to make sentences more natural.

**2\. Words Critical to Comprehension**  
Sometimes a word is essential for understanding the plot or characters, even if it’s rare or outside the students’ decoding range. Previewing it can have a huge impact on your student’s comprehension of the story.

## How to Preview Effectively

**For vocabulary words:**

1.  Say it aloud and have students repeat.
2.  Show it in context in the story.
3.  Give a short, student-friendly definition.
4.  Ask a question to connect it to their experience.
5.  Optional: act it out or use a quick sketch.

**Out-of-sequence words:**

1.  **Say it** – Say the word and use it in a sentence.
2.  **Hear it** – Stretch out and say each sound you hear.
3.  **Map it** – Match sounds to letters as you write the word.
4.  **Mark it** – Put a heart over the tricky part you must “learn by heart.”
5.  **Show it** – Show students where they will see it in the story.

## Concrete example: Pre-teaching words for a decodable story (Shan Helps Pick Up Trash)

Below is an example from the LitLab Story, [Shan Helps Pick up Trash](https://www.litlab.ai/library/cm8ypen250051l003cqs1e5gz).

![Preview example](https://storage.googleapis.com/litlab-assets/blog/2025_10_10_pre-teach/body_fig1.png)

### Steps to Choose Words to Preview

1.  Find vocabulary words that are critical to understanding the story.
2.  Find words that are non-decodable.
3.  Check how many times each word repeats.
4.  Select the words that appear most frequently and are crucial to understanding the text.

#### Step 1: Find vocabulary words

-   compost
-   recycle

#### Step 2: Find non-decodable words

-   compost
-   day
-   earth
-   recycle

LitLab will do this step for you! You can find non-decodable words in the “Words to pre-teach” section of the vocabulary guide.

![Vocabulary guide](https://storage.googleapis.com/litlab-assets/blog/2025_10_10_pre-teach/body_fig2.png)

#### Step 3: Note the frequency of the words

-   compost (1x)
-   day (1x)
-   earth (1x)
-   recycle (1x)

#### Step 4: Select words to pre-teach

-   **compost** — Why? crucial to understanding the text
-   **recycle** — Why? out-of-sequence word with a prefix that is also crucial for understanding
-   **earth** — Why? out-of-sequence word

If a word only appears one time and you think it might be familiar to students, or it's not crucial to the meaning of the text, you may want to choose a word that appears more frequently to preview instead.

## Keep It Simple. Keep It Purposeful.

Previewing doesn’t mean front-loading every unfamiliar word. In this example, we didn’t preview the word “day” even though it is an out-of-sequence word because it is a familiar word often used in the classroom.

Use this time to support meaning and confidence — not to rob the story of its decodable power. With practice, you’ll quickly learn which words need to be pre-taught and which should be left for students to decode.

Want to try it out? Browse our LitLab Stories and try previewing three words before reading with your class. Tag us with your annotated story!

👉 Explore decodable stories at [LitLab.ai](https://www.litlab.ai/)

_Written by: Jacqueline Ontell, Elementary Teacher, Special Education & Curriculum Development_

A practical framework for selecting 3–5 words to preview so students read decodable texts with confidence and comprehension.

How to Choose Which Words to Pre-Teach for Decodable Texts

## Nashville Classical Charter School: Driving Growth and Engagement with Personalized, Curriculum-aligned Decodables

![Quote from Administrator: "Both classes had growth/performance rates higher than the other 1st and 2nd grade classes. Thank you all at LitLab for helping us create engaged, fluent readers - a skill no one can take away from them. I can't tell you how much it means to me to know our kids are choosing to read (and doing it well) every day."](https://storage.googleapis.com/litlab-assets/blog/2025_04_05_nashville_case_study/image1.png)

**[👉 Read the full case study here](https://storage.googleapis.com/litlab-assets/Shareables/LitLab_NCCS_case_study.pdf)**

## Background

Nashville Classical Charter School (NCCS) has always been rooted in the science of reading. As part of that commitment, they prioritized decodable texts in their early literacy instruction. 

But over time, gaps in their existing materials began to show—particularly in the lower grades.

"Our options were severely limited," said Emma Colonna, Director of K-8 Humanities. "Students, especially in K-1, would run through the decodables quickly and get bored. Engagement and personal motivation dropped. We needed texts that could both support skill development and spark interest."

Compounding the challenge was the nature of decodables themselves: what's decodable for one student might be inaccessible to another if they haven't yet learned a specific sound-spelling pattern. Without a way to personalize texts based on individual mastery, teachers struggled to offer targeted practice.

## Why LitLab

When Emma and her team encountered LitLab, the fit was immediate. The platform offered a rare combination of engagement, precision, and instructional alignment.

LitLab's Student Practice Platform allowed teachers to assign stories matched to each student's phonics needs. Stories were dynamic, customizable, and tied directly to phonics patterns being taught in Tier 1\. For students, the experience felt fresh and relevant. For teachers, it added a powerful tool for reinforcing instruction and differentiating support.

>"LitLab addressed multiple challenges at once. It increased student engagement, enabled data-driven practice, and aligned with our core phonics instruction. It was exactly what we needed."  
— Emma Colonna, Director of K-8 Humanities, Nashville Classical Charter School

## Implementation

NCCS launched a focused pilot in two classrooms—1st and 2nd grade—led by high-performing teachers Ms. Mullen and Ms. Ryan. The team was intentional about how the tool would be rolled out. Emma oversaw structural planning and served as the liaison with LitLab. Brigid, the Assistant Principal of K-2, supported implementation and coaching on the ground.

LitLab was used during the school's Tier 2 intervention block. While teachers worked with small groups, the rest of the class used LitLab independently. Teachers assigned decodable patterns weekly, based on data from AIMSWeb and CKLA. The weekly cadence allowed for rapid, responsive targeting of skills that students had not yet mastered.

"We didn't just drop a new tool in and hope it worked," Emma noted. "We had a clear plan, tight feedback loops with LitLab, and used our own data to make sure the implementation aligned with student needs."

## Results

By the end of the year, the results stood out.

Both classrooms that piloted LitLab outperformed their peers on end-of-year benchmarks—not just in proficiency, but in student growth. These two classrooms were in the top quartile for growth nationwide. The second grade class, in particular, showed outsized progress despite serving a large number of students with intellectual and behavioral needs. Every student in both groups made gains in oral reading fluency.

![Example of aligned decodable text 2](https://storage.googleapis.com/litlab-assets/blog/2025_04_05_nashville_case_study/image2.png)

Student engagement saw a marked shift. Teachers reported sustained focus—15 to 20 minutes of independent use—and growing excitement around reading.

> "LitLab supported the broader instructional ecosystem we had worked hard to build."

Students were running out of decodables—and losing motivation. This case study shows how Nashville Classical Charter School used LitLab's personalized, curriculum-aligned texts to drive measurable fluency growth and reignite student engagement. 

Case Study: Nashville Classical Charter School

There is a persistent gap in K-2 literacy instruction that better phonics curricula alone have not closed. Students learn to decode during instruction, then sit down with connected text and struggle. The skills do not transfer automatically. Practice has to bridge that gap, and for that to work, the practice has to be aligned, engaging, and frequent enough to actually build fluency.

LitLab was built on that premise. Our logic model, developed with LeanLab Education and Dr. Lynne Harden as part of a formal codesign research process, is our written account of why we believe it and the evidence that grounds each step.

[Download the full logic model →](https://drive.google.com/file/d/1k8K8s2Sud8HgHYG6YgeX6PNdWZMDHMfW/view)

---

## Why a Logic Model?

Logic models are standard practice in education research and program evaluation. They make an intervention's assumptions explicit: here's who uses it, here's what they do with it, here's what we expect to happen, and here's the evidence that those expectations are reasonable.

For LitLab, that documentation matters beyond the research community. Districts adopting new EdTech deserve to know not just what a product does, but why it should work. The logic model is our commitment, in writing, to that question.

---

## The Problem We're Solving

Decodables are often considered dry, repetitive, and disconnected from a school's actual scope and sequence. In many classrooms, phonics skill practice is isolated from real reading time and not necessarily matched to where each student actually is. In many cases, teachers don't have access to decodables aligned to their program at all.

The result is a transfer problem. Students learn phonics skills in one context and struggle to apply them when reading connected text. LitLab was built to close that gap by giving teachers aligned, engaging, plentiful decodable practice that connects what was taught today to what students practice next.

---

## How LitLab Works

LitLab's primary users are K-2 students, their teachers, and the interventionists and literacy specialists who support them.

The platform gives teachers a library of 1,000+ grab-and-go decodable stories with comprehension questions, compatible with most major phonics scope and sequences. An AI decodable generator lets teachers create custom fiction and nonfiction decodables aligned to their specific program and lesson. Students read, record themselves, create personalized stories, and practice phonics skills in connected text. A teacher dashboard surfaces student-level data including comprehension scores, words read per minute, reading time, and assignment completion, so teachers can identify gaps and respond.

Teachers search, assign, and track. Students read, practice, and create. The platform is designed to make it easy to connect what was taught today to what students practice that night.

---

## What We Expect to Happen

The logic model organizes expected outcomes across three time horizons.

In the short term, teachers benefit from easier access to aligned reading practice, time saved on searching for materials, and clearer visibility into where individual students need support. For students, the immediate effects are skill-level: stronger word recognition, growth in phoneme awareness measurable by assessments like DIBELS, and fluency gains through the cycle of reading aloud, listening back, and receiving feedback (Muter et al., 2004).

Over the medium term, as students practice consistently, the research predicts stronger reading comprehension as decoding becomes more automatic (Muter et al., 2004; Kendeou et al., 2009). Students who experience early reading success develop a belief in themselves as readers that predicts continued engagement well into later grades (Chapman & Tunmer, 2003). Personalization and choice in reading practice deepen engagement and build the kind of intrinsic motivation that keeps students coming back to books (Cordova & Lepper, 1996). Teachers, too, grow more confident in teaching phonics effectively when they have the right tools, aligned materials, and clear data.

The long-term stakes are well-documented. Students who don't read proficiently by third grade are four times more likely to leave school without a diploma, and for the most severely struggling readers, nearly six times more likely (Hernandez, 2011). Students who become intrinsically motivated to read report reading more frequently, which compounds into higher achievement over time (Baker & Wigfield, 1999). Word recognition accuracy in early grades continues to matter all the way through college readiness (Rasinski et al., 2016).

The long-term theory of change is straightforward: students who practice reading with engaging, aligned, personalized texts consistently, starting in kindergarten, develop the skills, the confidence, and the love of reading that carry them through school and beyond.

---

## What the Logic Model Assumes

No logic model is unconditional. Ours rests on three honest assumptions: that students are engaged by the stories they read, because engagement is a prerequisite for the consistent practice that produces growth; that students will show up repeatedly over time, since short sessions done regularly are what compound; and that teachers have already adopted a core phonics program.

That third assumption is the most important one for districts to understand. LitLab is designed as the practice and evidence layer under a Tier 1 program, not as a replacement for one. It works because it amplifies an investment districts have already made in structured literacy.

---

## Where We Are on the Evidence Trajectory

LitLab is currently ESSA Tier IV certified, with a Tier II randomized controlled study underway. Every product decision is grounded in the peer-reviewed research base on early literacy, and our logic model reflects that directly. Each outcome is tied to specific evidence, not assumption.

[Read the full logic model →](https://drive.google.com/file/d/1k8K8s2Sud8HgHYG6YgeX6PNdWZMDHMfW/view)

---

## References

Baker, L. & Wigfield, A. (1999). Dimensions of Children's Motivation for Reading and Their Relations to Reading Activity and Reading Achievement. *Reading Research Quarterly, 34*(4), 452-477.

Chapman, J.W. & Tunmer, W.E. (2003). Reading Difficulties, Reading-Related Self-Perceptions, and Strategies for Overcoming Negative Self-Beliefs. *Reading & Writing Quarterly, 19*, 5-24.

Cordova, D.I. & Lepper, M. (1996). Intrinsic Motivation and the Process of Learning: Beneficial Effects of Contextualization, Personalization, and Choice. *Journal of Educational Psychology, 88*(4), 715-730.

Hernandez, D.J. (2011). *Double Jeopardy: How Third-Grade Reading Skills and Poverty Influence High School Graduation.* The Annie E. Casey Foundation.

Kendeou, P., van den Broek, P., White, M.J., & Lynch, J.S. (2009). Predicting reading comprehension in early elementary school. *Journal of Educational Psychology, 101*(4), 765-778.

Muter, V., Hulme, C., Snowling, M.J., & Stevenson, J. (2004). Phonemes, Rimes, Vocabulary, and Grammatical Skills as Foundations of Early Reading Development. *Developmental Psychology, 40*(5), 665-681.

Rasinski, T. et al. (2016). Reading Fluency and College Readiness. *Journal of Adolescent & Adult Literacy, 60*(4), 1-8.


LitLab is ESSA Tier IV certified. Here's the research behind how we're built, and the logic model that grounds every product decision we make.



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