Learner Variability Project

Product or Programme · All products and programmes
Evidence · 15 claims (14 for, 1 mixed) · 5 studies (2 qualitative, 2 design, 1 associational), q1–q2 · 0 of 5 report an effect size · 15 claims rest on one study

Description

The Learner Variability Project, developed by Digital Promise, provides the Learner Variability Navigator web app and related research-based tools to help educators understand learner differences and select strategies.

Components

• Learner Variability Navigator (LVN) web app: The LVN is a free, open-source web app built by the Learner Variability Project to remove barriers of time, paywalls, and perceived applicability that keep teachers from reading research. The article states, "This app synthesizes peer-reviewed research and provides tools to scaffold educators' knowledge about the evidence-based factors that contribute to learning and practical strategies that support different learner needs." It presents Learner Models concretely framing whole-child learning for pre-K through grade 12, including the Learner Centered Design Tool, which suggests related factors based on empirical research connections and recommends prioritized research-based strategies. In Tas (Medha Tare et al. (2022))
• LPS website: a free, open-source digital resource translating Learner Factors research into design and curriculum strategies: The Learner Positioning Systems (LPS) website is a free, open-source digital resource presenting the research behind the Learner Factors that most impact learner variability, culminating two years of systematic literature review and framework development. It contains a description of each Factor and its influence on reading, shows which Factors interact with others, and links Factors to research-based instructional strategies that also provide guidance for product developers. The paper directs readers to explore Factors and strategies at lps.digitalpromiseglobal.org. (Sheppard (2015))
• Learner Variability Navigator (LVN) web app curating factors of learning and strategies: The Learner Variability Navigator is a free, open online tool that curates learning research: "The Learner Variability Navigator (LVN) is a free and open source web app that features Learner Models for grades Pre-K to 12 in math and literacy and an adult learning model." It provides factors of learning and strategies to help teachers customize learning experiences, and its whole child framework structures this guide's reflection template and strategy bank. (The IEP Project: A Strength-based, Whole Learner Teacher Guide)
• Learner Positioning Systems and Learner Models framework: Digital Promise Global's Learner Positioning Systems (LPS) initiative aims to build frameworks and products that provide "a fuller understanding of learners and how to support them no matter how they learn best." At its heart are Learner Models that identify factors research shows affect learning and vary among learners, combining content area factors with each learner's unique characteristics. The Models build on Todd Rose's concept of "jagged profiles," which recognizes that each learner has distinctly different strengths and areas of growth. LPS is also envisioned as a tool for evaluating and certifying personalized learning products. (Research et al. (2015))
• Digital Promise's learner variability framework: every learner has a jagged learning profile across four domains: The framework holds that learner variability is the rule, not the exception, and that every learner has a unique profile across what Digital Promise identifies as four domains: content, cognition, social and emotional, and biographical backgrounds. It implies teachers must act like doctors—diagnosing where learners stand on progressions and tailoring instruction—rather than like line workers, and must uncover their own biases to avoid inequitable practices. The publication uses the framework as the foundational rationale for personalized, competency-based, digitally informed constructs for teaching and learning. (Brizard (2023))
• Learner variability whole child framework: strengths and challenges across content, cognition, social-emotional learning, and student background: The guide's organizing framework treats learner variability as a design challenge rather than a student problem: "Learner variability is the recognition that every student has a unique set of strengths and challenges across a whole child framework that are interconnected and vary according to context." The framework spans four domains — content, cognition, social and emotional learning, and student background — so a student strong at building relationships but weak in decoding can be supported with recorded text and peer book clubs. It underpins the Learner Variability Navigator and the guide's reflection questions. (The IEP Project: A Strength-based, Whole Learner Teacher Guide)
• The LPS K-3 Reading Learner Model organizes learner variability into 34 Factors across four research areas: The Learner Positioning Systems K-3 Reading Learner Model is a framework synthesizing research from Language and Literacy, Cognition, Social Emotional Learning, and Student Biographical Background. Using a rigorous selection process, the team identified 34 Factors that affect how students learn to read, such as Decoding, Working Memory, Emotion, and Home Literacy Environment. Each Factor is described on the LPS website with its influence on reading, its interactions with other Factors, and links to research-based instructional strategies and design guidance for product developers. (Sheppard (2015))
• LPS Learner Factors model for Reading PK-3: The Learner Positioning Systems (LPS) initiative at Digital Promise Global distills existing research on cognitive, social and emotional, content area, and background Learner Factors that affect learning in domains such as reading and math. Its first Learner Model, Reading PK-3 (Sheppard, 2017), organizes factors including Inhibition, Working Memory, Decoding, Primary Language, Emotion and Motivation, Vision, and Attention, and is used to review edtech products and recommend evidence-based features that support learner variability. (Partnerships that Work: Tapping Research to Address Learner Variability in Young Readers)
• LVP model of impact of designing for learner variability in edtech: The report proposes a theory-of-change model linking implementation of a suite of research-based features on the ReadWorks platform to teacher awareness, student use of features, increased student engagement, and increased student performance. The model treats learner variability as the starting point: because students differ in factors like attention, working memory, vocabulary, and vision, a suite of optional supports lets each student select what they need in the moment rather than all students receiving the same support. The partnership investigated the validity of the model through a mix of qualitative and quantitative research methods at three levels: a national survey, district-level (Tare et al. (2019))
• Whole-child learner variability theory of change: The Learner Variability Project's theory of change holds that synthesizing learning sciences research into factors critical to learner outcomes, connected across the whole child, generates a mental model for educators. As the article states, "Our theory of change proposes that by synthesizing the learning sciences research into factors critical to learner outcomes (see Figure 1) and showing how they are connected across the whole child, we can help generate a mental model for educators." Figure 4 depicts three steps: providing accessible tools and professional learning, shifting educator mindsets to recognize and leverage each student's strengths, and creating safe, supportive, personalized (Medha Tare et al. (2022))
• The Learner Variability Project four-pillar framework: Content, Cognition, Social and Emotional Learning, and Student Background: The Learner Variability Project (LVP) at Digital Promise distills learning sciences research into Learner Factors organized under four pillars: Content, Cognition, Social and Emotional Learning, and Student Background. Each Factor includes an explanation of what it is and how it connects with other Factors, situated in the context of a learning goal, with a robust list of research-based strategies showing how research may be applied in practice and product development. (Pape (2018))

Claims

• A brief self-guided engagement with the LVN shifted most educators' perception of the importance of learner variability [+M]
• Educators reported increased confidence across all four pillars of the whole-child model after LVN use [+M]
• Educators reported that LVN-selected strategies supported student engagement, content knowledge, confidence, and collaboration [+W]
• Educators reported the LVN strategy bank improved their understanding, use, and identification of strategies [+W]
• Educator-led peer professional development reinforced educators' own understanding and connected LVN to existing practice [+W]
• Time to plan, more than tools or training, was the largest reported barrier to implementing LVN strategies [~W]
• Classroom teachers rarely consult research when making decisions about their classroom practices, citing time constraints, the vastness of research, paywalls, and perceived distance from practice [+W]
• In the Learner Variability Navigator case, feedback loops across multiple partners generated an output of need that the authors say simple surveys may not have produced [+W]
• In the district study, teachers assigned articles above students' STAR Lexile levels (about 375 points higher on average), and greater STAR growth related to completing more, harder, and more accurate ReadWorks assignments [+W]
• Changing the audio default from opt-in to opt-out raised audio availability from 72% to 99% of assignments and student audio use from 68% to 84% [+W]
• Feature use related to a slight increase in multiple choice accuracy, larger for lower-Lexile students and for easier articles [+W]
• Feature use was widespread across student groups (92% of students used at least one feature; 75% of assignments included feature use), with no differences by STAR score, special education status, or income, but substantial variation across teachers [+W]
• Using at least one feature raised students' multiple choice question attempt rate to 89 percent and eliminated the drop on hard assignments, with a significant feature-use × difficulty interaction [+W]
• Teachers who tried ReadWorks features reported high intent to assign more and higher-level articles (89% and 82%) [+W]
• Teachers reacted unanimously positively to new audio supports on the ReadWorks platform and offered them to all students, not only struggling readers [+W]

Related Products and Programmes

• Renzulli Learning
• OGAP Math

Key Sources

• Medha Tare, Alison R. Shell, Jessica Jackson. (2022). Shifting Mindsets: Designing Lessons for Learner Variability. Digital Promise. https://digitalpromise.dspacedirect.org/items/c1921acf-1964-4f4d-8232-1e8af6ad7367
• Sheppard, S. M. (2015). Supporting Research-Based Personalization for Reading Success. Digital Promise Global. https://global.digitalpromise.org
• Digital Promise. (2023, February). The IEP project: A strength-based, whole learner teacher guide. Digital Promise. https://doi.org/10.51388/20.500.12265/169
• Research and the Promise of Personalized Learning. (2015). Digital Promise Global, Making Learning Personal for All series. https://global.digitalpromise.org
• Brizard, J.-C. (2023). Breaking with the past: Embracing digital transformation in education. Digital Promise. https://doi.org/10.51388/20.500.12265/176
• Lb0
• Tare, M. & Shell, A. R. (2019). Designing for learner variability: Examining the impact of research-based edtech in the classroom. Washington, DC: Digital Promise Global. https://digitalpromise.dspacedirect.org/items/82839c44-adb1-400c-b422-9bfbbca65985. doi:10.51388/20.500.12265/81
• Pape, B. (2018). Learner Variability Is the Rule, Not the Exception. Digital Promise Global. https://lvp.digitalpromiseglobal.org/

Page metadata

Field	Value
type	product
id	learner-variability-project
aliases	learner-variability-project-lvp
title	Learner Variability Project
description	The Learner Variability Project, developed by Digital Promise, provides the Learner Variability Navigator web app and related research-based tools to help educators understand learner differences and select strategies.
status	review
moved_from	element/learner-variability-navigator-web-app, element/lps-website-open-source-learner-factor-resource, element/lvp-digitalpromiseglobal-navigator-tool, theory/learner-positioning-systems-framework, theory/learner-variability-four-domains-digital-promise, theory/learner-variability-whole-child-framework, theory/lps-k3-reading-learner-model-34-factors, theory/lps-learner-factors-reading-pk3-model, theory/lvp-learner-variability-impact-model, theory/lvp-whole-child-theory-of-change
product_kind	software
generated	by process:sweep-kinds on 2026-10-10
trust	unverified — no one has confirmed this page's content
sources	7 — medha-tare-2022, sheppard-2015, digital-promise-2023-february-the, research-and-the-promise-of-personalized-learning-2015, brizard-2023, lb0, tare-2019

Frontmatter is the page's machine-readable record — see the Schema & Guide.