About the Learner Variability Project

Overview

“When we understand learner variability, we see a design challenge, not a student problem.” (Pape 2018)

Learner variability is the recognition that each student has a unique set of strengths and challenges across a whole child framework that are interconnected and vary according to context. It embraces both students’ struggles and strengths. In concept and practice, learner variability opens up the doors to cultural responsive and strengths-based, inclusive teaching and learning for each student.

LVP’s web app, the Learner Variability Navigator (LVN), is a free and open source tool with professional learning resources that can be customized for educators and edtech developers. The goal of LVN is to provide easy access to evidence-based strategies that they can readily weave into their practice and products in order to meet the needs of the full diversity of learners. LVN is composed of learner models from grades pre-K through 12 in literacy and math, as well as an adult learner model—all based on a whole learner framework. Each learner model was developed by a team of researchers and practitioners (see below).

Most unique about LVN is the tool’s ability to show connections among factors (for example, how sleep can have an impact on working memory) and provide strategies that can address the connected factors. Understanding the different factor connections displayed in LVN helps educators and edtech developers understand the “why” of each student, customize learning, and, thus, put students and their unique strengths and struggles at the center of the learning experience.

FAQ on the Learner Variability Navigator

Why and how did LVP emerge?

Learner variability is based on Todd Rose’s book, The End of Average. One continuing goal of LVP is to disrupt the myth of the average learner and provide educators and edtech developers with evidence-based factors and strategies that can easily be incorporated into their practice and product. The Oak Foundation is the primary funder of the project. Other funders include: CZI, The Bill and Melinda Gates Foundation, and Overdeck Family Foundation.

Is learner variability the same thing as learning styles?

Learner variability is not learning styles (e.g., identifying as an auditory, visual, or kinesthetic learner). The notion of learning styles, while widespread, is not grounded in research and further promotes the idea that students have a fixed way of learning. Importantly, the modality a learner uses or prefers can vary greatly depending on the task and context. For instance, you might remember a phone number by repeating it multiple times (auditory), but you might remember someone’s name with a visual reminder, such as a nameplate on a desk. Additionally, research shows that engaging students with multi-modal instruction (audio, visual, and kinesthetic) helps solidify information into Long-term Memory.

What is a learner model?

  • A learner model is the curation of research that matters for learning across a whole learner, within a framework of developmental stage and content area.
  • Each learner model begins with the question, “According to research, what are the major factors that affect learning in this domain (e.g., “math,” “literacy,” “adult learning”) for the full diversity of learners?”
  • We define the grade range according to classroom curriculum/standards and developmental stages based in the science of learning (e.g., developmental, sociological, neuroscience) to narrow the focus and best represent learners at a given stage.

What does a learner model consist of?

  • Each learner model is divided into four main pillars (see Figure 1 below) to represent factors of learning across the whole child: student background, social emotional learning, cognition, and academic content skills.
  • Learner factors (e.g., Safety, Motivation, Working Memory, Algebraic Thinking, etc.) are defined and categorized within the pillars through the research review process noted below.
  • We find research-based connections (causal and correlational relationships) between the factors to showcase how these factors are closely connected and can impact each other across the whole model.
  • Teacher-facing strategies (e.g., project-based learning, word walls, untimed tests, etc.) and supports for the learner factors are developed through the research process as noted below.
Learner model factor map for Literacy 7-12 with four factor categories and group of factors within each. See figure 1 caption for more info.
Figure 1: Literacy 7-12 Learner Model: Factors are contained within 4 pillars as represented by colored columns

Who is the audience for the LVN/this research?

  • Educators
  • Instructional designers
  • EdTech product companies
  • Coaches/administrators
  • Professors
  • Student teachers
  • Parents/caregivers
  • Learners

What is your research review process?

  1. Each learner model is developed through an iterative and collaborative process (see Figure 2).
  2. First, we narrow focus by choosing a content area (e.g. math, literacy) and age range.
  3. Next, we outline the major factors for learner success using seminal papers and reviews, along with consulting curriculum standards
  4. Then, to collaboratively shape and define the factors, we recruit a board of expert research advisors with diverse backgrounds and knowledge across the whole learner.
  5. Finally, we synthesize the key components of the factor and why they matter for learner outcomes, along with connections between the factors.
  6. We continue to modify the content alongside our research and practitioner advisory board to ensure it is robust and accurate.
Process outlining the cycles of work to create a learner model, going from literature review with experts to creating a factor map to identifying context-specific strategies with practitioners.
Figure 2: Depiction of the learner model creation process starting on the left and continuing in a clockwise direction

What type of research do you consider and why?

  • For factor content: We prioritize meta-analyses and reviews along with recently published (<20 years old) empirical research. We aim to include research from high impact journals while also looking to include diversity of researchers and participants. Most of our research is based in the U.S. but we do include international research where relevant. Each factor summary is shaped and reviewed by experts from our learner model advisory board.
  • For factor connections (see Figure 3): We prioritize recent meta-analyses and empirical research. We will include a connection if there is at least one recent empirical paper with strong evidence that there is a correlation between the two factors for the given age range, however typically there are many studies that support the connection.
Example of a factor connections wheel for the Literacy 4-6 learner model "Emotion" factor, showing connections to 22 factors across each factor category.
Figure 3: Factor connection wheel for Emotion factor: Each slice shows research-based connections to the other factors across the whole learner
  • For strategies: We also prioritize empirical research that shows benefits of the strategy in the classroom. However, we also value input from educators and case studies that showcase the nuances of applying a strategy in different contexts for a minimum of 3-5 references for strategies.

How do you consider or address inequities in the research you review?

  • Whenever possible, we look for research from diverse researchers and institutions. It is not always possible to determine the background of the research team and there are cases where we may not be able to find the diverse representation of research backgrounds that we desire. If you notice a gap in our research diversity and have suggestions for other resources, we encourage your feedback.
  • We also are aware that research populations can be homogenous. We work to include diverse representation in the participant groups when possible, prioritizing research with students who have been historically and systematically excluded, as we acknowledge that designing for these learners benefits all students.

How do you keep your research up to date?

  • We try to ensure that the majority of our references are recently published (~before 2010) and we continue to add new and relevant research as we find it. However in some cases we do cite older seminal studies and reviews that have shaped the field of study and are major references for understanding a factor or strategy.
  • We consider the Learner Variability Navigator (LVN) to be a “living resource”—it is constantly being updated. We engage in learner model refreshes as a way of keeping up with current research and education findings/needs. These refreshes help us examine the LVN from different lenses to make sure it reflects current practices in the field.

Why can’t I access the research link?

  • We do our best to synthesize the research so you don’t have to read the original articles, however we support anyone interested in learning more to dig deeper. Whenever possible we try to use freely available research or post links to Google Scholar where that paper may be accessible. However, it is not always possible that key research is free to everyone. Please reach out to us if you have any questions about any of these references.

What are some gaps you’ve found in your research?

  • While there is increasing research across the pillars of learning (the columns: Student Background, SEL, Cognition, Content), there is still a need for more cross-disciplinary research to connect across these pillars. For instance, we often find gaps when looking for connections between factors in the SEL column, and academic outcomes—for instance, math motivation, an aspect of the SEL column, and math content factors.
  • We strive to use research that includes students from diverse backgrounds, yet still much of the research is conducted with homogenous samples.
  • Our strategies are research-based, and we aim to connect them to each of the factors they can support. However, there is often a lack of research that shows evidence that they do in fact support many of our factors, including for example, Motivation, Metacognition, or Emotion.

How do I cite the Learner Variability Navigator?

  • We are a free and open-source tool and encourage you to use it, share it, and iterate upon it with fidelity, at your will. However, we understand and respect the importance of citing sources. To cite us, please use the following:
    • Learner Variability Navigator (2023). Digital Promise. Washington, DC. Retrieved from: https://lvp.digitalpromiseglobal.org/

Citation

Pape, B. (2018). Learner Variability is the Rule, Not the Exception

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