Backed by Learning Science Research and Powered by Data-Driven Intelligence.

edapt platform was built from the ground up based on proven research-backed strategies and learning techniques coupled with data-driven intelligence to deliver an unparalleled personalized mastery-learning experience as effective as one-to-one tutoring.

Learning Science RESEARCH

Mastery Learning.

a.k.a. “Learning for mastery”, students are required to master each concept before moving to dependent concepts. Mastery learning focuses on the role of feedback in learning and encourages students to learn at their own pace as they master skills and progress toward learning goals.

Through painstaking implementation and refinement, edapt platform incorporated the most impactful mastery learning techniques into its core pedagogy including 1:1 instruction, reinforcement, feedback-corrective mastery learning, cues and explanations, initial cognitive prerequisites and independent intervention.

"The 2 Sigma Problem: The Search for Methods of Group Instruction as Effective as One-to-One Tutoring." - Bloom, B. S. (1984).
Learning science RESEARCH


Identifying knowledge gaps and delivering instructional scaffolds is critical and educationally consequential. Scaffolding is a seamless and timely process that provides students with support until they can apply new skills and strategies independently. As they begin to demonstrate mastery, the assistance or support is gradually decreased to shift the responsibility for learning to the students.

edapt platform's pedagogy uses our proprietary "Recursive Bi-Directional Scaffolding" mechanism to deliver highly effective ways of identifying and closing knowledge gaps through seamless scaffolding and just-in-time remediation.

"Using Scaffolded Instruction To Optimize Learning." - Larkin, Martha (2002).

Our Research Advisors.

The pedagogy powering our platform was developed in close collaboration with our research advisors from Stanford University.

Dr. Emma Brunskill

Dr. Brunskill is a computer science professor at Stanford where she is part of the AI lab and Statistical Machine Learning group. Her research focuses on reinforcement learning in high stakes scenarios.

Dr. Karin Forssell

Dr. Forssell is the program director for the Learning, Design and Technology program at Stanford. Her research focuses on the choices people make in learning about and using new digital tools.

Dr. Rob Tibshirani

Dr. Tibshirani is a professor of statistics at Stanford where he leads research in data science and statistics. His research focuses on dealing with large amounts of data and separating out consistent patterns from the noise.

cognitive science RESEARCH

Dual Coding.

Instruction designed to leverage both visual and auditory channels of the human brain’s processing capacity will lead to deeper learning. Instructional design should be sensitive to how humans learn and leverage the three cognitive science principles of learning namely:
1) dual channels - humans possess separate channels for processing visual and verbal materials
2) limited capacity - each channel can only process a small amount of material at any one time
3) active processing - deep learning depends on the learner's cognitive processing during learning (e.g. selecting, organizing and interacting).

edapt platform's pedagogy has incorporated dual coding techniques to deliver
1) Instruction using high-quality video lessons
2) Bite-sized lessons designed to maximize limited capacity
3) Each video lesson is followed by problem-solving to enable active processing and recollection

"Cognitive Theory of Multimedia Learning." - Mayer, Richard E. (2001).

Knowledge Segmentation.

Bite-sized knowledge segments and processing time between successive segments reduces the cognitive load. Knowledge segmentation is a mechanism that breaks down and offers information to students in bite-sized segments. Learners can digest each knowledge segment before moving on to the next.

With this approach incorporated into edapt platform's pedagogy, the learner has time and capacity to organize and integrate the information resulting in robust encoding and efficient long-term recollection.

"Nine ways to reduce Cognitive Load in Multimedia Learning." - Mayer, Richard E. & Moreno, Roxana (2003).
cognitive science RESEARCH

Constructed Response.

Interactive and rigorous items enable deeper engagement, a higher level of thinking, and improved measures of student knowledge. Traditional assessments use “selected” response (multiple choice) questions which are a lot less reliable in measuring student knowledge than “constructed” response (completing an interactive task) questions. Such Constructed Response items a.k.a. Technology Enhanced Items (TEI) improve measures of student knowledge, create more engaging learning experiences and reduce the effects of guessing.

edapt platform supports an extensive and ever-expanding list of 60+ prebuilt TEI item types and interactives to encourage designers to incorporate more constructed responses than selected responses in their course content.

"Construction versus Choice in Cognitive Measurement." - Bennett, R. E. (1993).

Ready to transform your courses?