Operationalized learning science.
MyGRIT Course® translates established cognitive and educational research into structured, repeatable student behaviors. The science is not new. The behavioral infrastructure is.
The three scholars who made this possible.
Grit — perseverance and passion for long-term goals — predicts success more reliably than talent or IQ. Duckworth's landmark 2007 research established that the disposition to persist matters more than the capacity to perform. The name MyGRIT Course® is a direct homage to her work. What she named, the Effort Learning Model™ built a system to practice.
Metacognition and explicit learning strategy instruction transforms academic performance, sometimes within a single semester. Dr. McGuire's framework established that students who learn how to learn perform dramatically better than those who rely on content exposure alone. The DGRP™ framework operationalizes her findings into a structural, repeatable daily practice.
Self-generated questions deepen learning more than passive review. The Right Question Institute's methodology for teaching students to formulate their own questions is embedded into every stage of the Effort Learning Model™. Every ELA stage prompts students to generate questions, not just receive answers.
Together these three bodies of scholarship establish that students need the disposition (grit), the method (metacognition), and the system (ELM) for sustainable academic success. MyGRIT Course® uniquely integrates all three dimensions into a single structured learning platform.
The principles MyGRIT Course® makes practical.
Awareness and regulation of one's own thinking — knowing what you know, and what you don't.
Reasoning that distinguishes, organizes, and connects ideas with intent.
The cognitive infrastructure that turns intention into sustained action.
Strengthening memory and understanding by recalling, not re-reading.
Distributing encounters with material to support long-term retention.
Linking new information to existing mental structures.
Setting goals, monitoring progress, and adjusting strategy.
Examining thinking after the fact to improve it next time.
The three scholars MyGRIT Course® is built upon.
MyGRIT Course® doesn't invent learning science — it stands on the work of three scholarly anchors and turns their insights into something a student can actually do, every day.
Duckworth's work showed that long-term passion and perseverance — grit — are powerful predictors of achievement. MyGRIT Course® takes that conviction and gives it a structure: grit becomes a learnable behavior, not a personality trait.
Dr. McGuire's metacognitive teaching framework reframes learning as something students can be taught to manage. Her insistence that metacognition is teachable shapes how MyGRIT Course® makes thinking visible at every stage.
RQI's Question Formulation Technique puts the act of asking back in the student's hands. MyGRIT Course® builds on this — the AI Companion, the QI Tool™, and the DGRP™ framework all train students to generate the questions that drive their own learning.
The Effort Learning Model™ is an instructional sequence informed by decades of established learning science.
Each stage of the ELM is informed by a cluster of evidence-based learning principles drawn from peer-reviewed research on how people acquire, retain, and apply knowledge. The framework organizes what the research has consistently supported into a practical sequence a student can follow and an educator can reinforce. It does not claim a one-to-one mapping between each stage and a single confirmed cognitive mechanism. The full research foundation, including primary sources, study populations, and appropriate limitations, is documented in the MyGRIT Course® Research Foundation document available to institutional partners upon request.
Research foundations for each stage.
- Stage 1, Preparing.
Research on pretesting and prequestioning consistently shows that engaging with material before instruction improves later learning, even when initial attempts are incorrect. The Institute of Education Sciences, a division of the U.S. Department of Education, recommends prequestioning as an evidence-based instructional strategy.
Richland, Kornell, and Kao, 2015.
- Stage 2, Active Listening.
Research on attention and memory encoding supports the principle that deliberate engagement during instruction produces stronger initial learning than passive reception. Attention influences what enters memory. Distraction during instruction creates gaps that later study cannot always repair.
- Stage 3, Question Generation.
Student-generated questioning is supported by a body of peer-reviewed research as a strategy that promotes reading comprehension, self-monitoring, and deeper processing of material. It is a generative learning approach that requires learners to actively select and construct meaning rather than passively receive it.
Multiple peer-reviewed studies on student-generated questioning.
- Stage 4, Organizing.
Distributing review across time rather than concentrating it in a single session is one of the most replicated findings in cognitive psychology. Spaced practice is consistently associated with stronger long-term retention than massed study across a wide range of subjects, ages, and learning contexts.
Cepeda et al., 2006, Psychological Bulletin.
- Stage 5, Refining.
Using self-generated questions to identify what you know and what you do not know engages retrieval practice, which is among the most reliably supported study behaviors in the research literature. A meta-analytic review across 159 studies found that retrieval practice produced a mean effect size of approximately g equal to 0.50 relative to repeated study, with 81% of comparisons favoring retrieval over rereading.
Rowland, C.A., 2014, Psychological Bulletin, 140, 6.
- Stage 6, Answering.
Attempting to answer self-generated questions combines retrieval practice with self-explanation, two strategies with consistent support in the learning science literature. A meta-analysis examining self-regulated learning interventions across primary and secondary school studies reported an average effect size of 0.69 for academic performance outcomes. These figures apply to self-regulated learning interventions broadly and are not a direct measure of this specific stage.
Dignath, Büttner, and Langfeldt, 2008, Metacognition and Learning.
- Stage 7, Evaluating.
Students who assess their own understanding against explicit criteria before an assessment tend to perform better than those who do not. A meta-analysis across 175 studies and more than 19,000 participants found that self-assessment produced a mean effect size of g equal to 0.585 and peer-assessment produced g equal to 0.606 for academic performance across education levels and age groups.
Yan, Z., et al., 2022, Educational Research Review.
The Effort Learning Model™ organizes established learning strategies into a sequence with a clear next action at every stage. It does not claim to be the only framework informed by this research. It claims to be a practical system that makes these strategies accessible and structured.
The ELM framework has not yet been independently validated by external researchers. It was developed through direct practitioner work, informed by established learning science, and tested in formative tutoring research approximately between 2021 and 2022. Outcome studies are planned for Year 1 and Year 2 post-launch. Institutional partners may request the full Research Foundation document, which includes primary sources, effect sizes, study populations, and limitations for each stage.
The readiness gap is measurable before students reach the next transition.
The Texas 2036 and George W. Bush Institute State of Readiness Report found that 78% of Texas eighth-graders do not achieve college or career milestones within six years of high school graduation, and 86% of economically disadvantaged students do not complete a postsecondary credential within that window. MyGRIT Course® addresses the missing behavioral process behind those outcomes.
841 students across four countries described exactly what they want from AI in education.
A 2026 study published in Frontiers in Education asked 841 students in four countries to describe in their own words what they wanted AI to do in a classroom. Without being given any categories to choose from, students independently described three roles: a tutor for explanation and understanding, a coach for personalization and self-regulation, and a companion for emotional and motivational support. For each role they drew a firm limit. They want AI to help them think. They do not want it to think for them. The researchers observed that fears of inevitable learner passivity may be overstated.
The Twin AI™ was designed around exactly these principles before this research was published.
Students' conceptions about AI in science classrooms. Frontiers in Education, 2026. DOI: 10.3389/feduc.2026.1810140.
Built from established science. Validated deliberately.
MyGRIT Course® is grounded in established learning science and formative tutoring research. The platform has not yet been independently validated by external researchers. Outcome studies are planned for Year 1 and Year 2 post-launch, and institutional partners may request the full Research Foundation document, including primary sources, study populations, effect sizes, and limitations.
A 2026 peer-reviewed study involving 841 students across four countries independently documented student demand for exactly the kind of AI learning companion the Twin AI™ was designed to be — before MyGRIT Course® launched.
Learning science is mature. The execution layer wasn't.
Decades of research have established what works. MyGRIT Course® is the behavioral and technological layer that makes those findings usable inside a student's day.