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Dedicated to Scientific Research
Empower your organization to produce best-in-class learning experiences based on cognitive science, machine learning and
human-centered design.
Overview
Educational Data Science
Process Mining
Learning Analytics
AI in Education
Psychometrics
Design & Human-
Computer Interaction
Product Design
Game Design
Smart Systems
Interaction Design
Design Factors for Motivation: Difficulty, Novelty, and Suspense
We conduct online experiments testing how different factors affect player motivation. Engaging game design is thought to come from being “not too hard, not too easy.” Our evidence suggests the maxim should be “not too hard, not too boring.”
Experimentation for Optimizing Learning and Motivation
We show that product experiments involving thousands of experimental conditions and tens of thousands of online learners can be used to optimize learning outcomes and to contribute to learning scientific research.
Machine Learning for Product Adaptivity
We use machine learning algorithms to automate product design experiments, resulting in optimized student outcomes at scale. Product experiments are a key enabling technology for continuous improvement, efficacy measurement, and personalized, adaptive learning.
Psychometric Validation of Neurological Assessment Games
We develop a game to measure “Selective Sustained Attention” in small children. We then demonstrate appropriate methods for validating the psychometric properties of the game.
Building Effective Games for Number Sense
We design a game for the assessment and instruction of “number sense.” We base the design of the game on the neuroscience of the approximate number system. We demonstrate various aspects of the efficacy of the game for learning and assessment.
Simple Interactions for Social Learning
We explore how social interactions in low-income households in India help overcome the limits of low-cost digital technology.
Radically Affordable Learning Hardware
We provide ethnographic depictions of the incorporation of $10 educational computers into low-income households in India. We show how various design factors might support the longevity of contemporary technology systems.
Assessment Data Forensics
We help education organizations maintain high integrity in their exams. We use data analytics and computer vision-based methods to analyze assessment data from both digital and paper systems.
Process Analysis for Educational Data
We invent new methods to understand the processes of education technology interaction. We build process models from student and teacher data to find actionable places for product improvement.
Design Factors for Motivation: Difficulty, Novelty, and Suspense
We conduct online experiments testing how different factors affect player motivation. Engaging game design is thought to come from being “not too hard, not too easy.” Our evidence suggests the maxim should be “not too hard, not too boring.”
Experimentation for Optimizing Learning and Motivation
We show that product experiments involving thousands of experimental conditions and tens of thousands of online learners can be used to optimize learning outcomes and to contribute to learning scientific research.
Machine Learning for Product Adaptivity
We use machine learning algorithms to automate product design experiments, resulting in optimized student outcomes at scale. Product experiments are a key enabling technology for continuous improvement, efficacy measurement, and personalized, adaptive learning.
Psychometric Validation of Neurological Assessment Games
We develop a game to measure “Selective Sustained Attention” in small children. We then demonstrate appropriate methods for validating the psychometric properties of the game.
Building Effective Games for Number Sense
We design a game for the assessment and instruction of “number sense.” We base the design of the game on the neuroscience of the approximate number system. We demonstrate various aspects of the efficacy of the game for learning and assessment.
Simple Interactions for Social Learning
We explore how social interactions in low-income households in India help overcome the limits of low-cost digital technology.
Radically Affordable Learning Hardware
We provide ethnographic depictions of the incorporation of $10 educational computers into low-income households in India. We show how various design factors might support the longevity of contemporary technology systems.
Assessment Data Forensics
We help education organizations maintain high integrity in their exams. We use data analytics and computer vision-based methods to analyze assessment data from both digital and paper systems.
Process Analysis for Educational Data
We invent new methods to understand the processes of education technology interaction. We build process models from student and teacher data to find actionable places for product improvement.
Design Factors for Motivation: Difficulty, Novelty, and Suspense
We conduct online experiments testing how different factors affect player motivation. Engaging game design is thought to come from being “not too hard, not too easy.” Our evidence suggests the maxim should be “not too hard, not too boring.”
Experimentation for Optimizing Learning and Motivation
We show that product experiments involving thousands of experimental conditions and tens of thousands of online learners can be used to optimize learning outcomes and to contribute to learning scientific research.
Machine Learning for Product Adaptivity
We use machine learning algorithms to automate product design experiments, resulting in optimized student outcomes at scale. Product experiments are a key enabling technology for continuous improvement, efficacy measurement, and personalized, adaptive learning.
Psychometric Validation of Neurological Assessment Games
We develop a game to measure “Selective Sustained Attention” in small children. We then demonstrate appropriate methods for validating the psychometric properties of the game.
Building Effective Games for Number Sense
We design a game for the assessment and instruction of “number sense.” We base the design of the game on the neuroscience of the approximate number system. We demonstrate various aspects of the efficacy of the game for learning and assessment.
Simple Interactions for Social Learning
We explore how social interactions in low-income households in India help overcome the limits of low-cost digital technology.
Radically Affordable Learning Hardware
We provide ethnographic depictions of the incorporation of $10 educational computers into low-income households in India. We show how various design factors might support the longevity of contemporary technology systems.
Assessment Data Forensics
We help education organizations maintain high integrity in their exams. We use data analytics and computer vision-based methods to analyze assessment data from both digital and paper systems.
Process Analysis for Educational Data
We invent new methods to understand the processes of education technology interaction. We build process models from student and teacher data to find actionable places for product improvement.
Design Factors for Motivation: Difficulty, Novelty, and Suspense
We conduct online experiments testing how different factors affect player motivation. Engaging game design is thought to come from being “not too hard, not too easy.” Our evidence suggests the maxim should be “not too hard, not too boring.”
Experimentation for Optimizing Learning and Motivation
We show that product experiments involving thousands of experimental conditions and tens of thousands of online learners can be used to optimize learning outcomes and to contribute to learning scientific research.
Machine Learning for Product Adaptivity
We use machine learning algorithms to automate product design experiments, resulting in optimized student outcomes at scale. Product experiments are a key enabling technology for continuous improvement, efficacy measurement, and personalized, adaptive learning.
Psychometric Validation of Neurological Assessment Games
We develop a game to measure “Selective Sustained Attention” in small children. We then demonstrate appropriate methods for validating the psychometric properties of the game.
Building Effective Games for Number Sense
We design a game for the assessment and instruction of “number sense.” We base the design of the game on the neuroscience of the approximate number system. We demonstrate various aspects of the efficacy of the game for learning and assessment.
Simple Interactions for Social Learning
We explore how social interactions in low-income households in India help overcome the limits of low-cost digital technology.
Radically Affordable Learning Hardware
We provide ethnographic depictions of the incorporation of $10 educational computers into low-income households in India. We show how various design factors might support the longevity of contemporary technology systems.
Assessment Data Forensics
We help education organizations maintain high integrity in their exams. We use data analytics and computer vision-based methods to analyze assessment data from both digital and paper systems.
Process Analysis for Educational Data
We invent new methods to understand the processes of education technology interaction. We build process models from student and teacher data to find actionable places for product improvement.
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