Maximize Learning Outcomes at Scale
To achieve this vision, we've built an intelligent learning platform by painstakingly interweaving the most effective evidence-based strategies drawn from decades of research involving cognition, instruction, data and technology.
Cognitive Intelligence
Cognitive strategies that enable the intelligence to improve how students process and retain knowledge over the long term.
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Learning Intelligence
Instructional strategies that enable the intelligence to improve how to teach students and assess their knowledge accurately.
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Data Intelligence
Data-driven strategies that enable the intelligence to deliver an unparalleled adaptive learning experience for each student.
Learn MoreResearch Advisors
Distinguished professors and renowned researchers from Stanford University.
Dr. Emma Brunskill
Department of Computer ScienceStanford University
Dr. Brunskill is a computer science professor at Stanford where she is part of the Stanford Artificial Intelligence Lab and the Statistical Machine Learning Group. Her research focuses on reinforcement learning in high stakes scenarios - how can an agent learn from experience to make good decisions when experience is costly or risky, such as in educational software. Her recent publications include: "The Misidentified Identifiability Problem in Bayesian Knowledge Tracing".
Dr. Karin Forsell
Department of EducationStanford University
Dr. Forssell is the Program Director for the Learning, Design, and Technology Master's Program at the Stanford Graduate School of Education. Her research focuses on the choices people make in learning about and using new digital tools, with a special interest in teachers as learners and the design process. Her recent publications include "Making Meaningful Advances: TPACK for Designers of Learning Tools".
Dr. Rob Tibshirani
Department of StatisticsStanford University
Dr. Tibshirani is a professor of statistics at Stanford where he leads research in data science and statistics and how they can bring scalable social change. He is passionate about combining math and computer science to solve real-world problems. His research focuses on the challenges with sorting through large amounts of data and separating out the consistent patterns from the noise. His recent publications include: "The Elements of Statistical Learning: Data Mining, Inference and Prediction".
Independently Recognized
ScootPad has been recognized as the world's leading adaptive learning platform by the non-profit education research firm EdSurge and reputed global market research firm HTF.
Sponsored by The Gates Foundation, EdSurge developed a framework to decode "adaptive learning technology" and offers a three-pronged approach to evaluate how tools adapt to learners in real-time.
ScootPad has been recognized as the leading adaptive learning platform that offers adaptive content, adaptive assessment and adaptive sequence. Of the 24 tools evaluated, ScootPad is the ONLY tool that offers adaptive learning across content domains (Math and ELA) for grades K-8 and accessible 24x7 over the cloud on any device.
ScootPad has been recognized as a leader in the rapidly growing Global Adaptive Learning market by HTF market research. Key players recognized in this research report include: D2L, Knewton, McGraw-Hill Education, ScootPad and Smart Sparrow.
HTF's research report Global Adaptive Learning Software Market 2017-2021, has been prepared based on an in-depth market analysis with inputs from industry experts. HTF's research also forecasts the global adaptive learning software market to grow at a CAGR of 31.07% during the period 2017-2021.
Cognitive Intelligence
Cognitive strategies drawn from decades of evidence-based research in cognitive science enable the intelligence to help improve how students process and retain knowledge over the long term.
Learning Intelligence
Instructional strategies drawn from decades of evidence-based research in learning science enable the intelligence to help improve how to teach students and assess their knowledge accurately.
Data Intelligence
Data-driven strategies drawn from emerging research in data science and machine learning enable the intelligence to help deliver an unparalleled adaptive learning experience for students.
