Knewton Adaptive Learning by Chaitu Ekanadham

Posted on Mar 30, 2015
The skills we demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.

Knewton Adaptive Learning by Chaitu Ekanadham

On March 18 we were lucky to host Chaitu Ekanadham, a data scientist from Knewton. Knewton is an education technology company that uses adaptive learning techniques. It uses data about past learning to aid students in future learning experiences.

For example, in traditional “text book” learning, students move through the content in a linear fashion, one chapter and then the next. While this is a tried and true method of teaching, it isn’t the best solution for every student in every situation. Some students may need only a review of some particular content, while others may need to spend a great deal of time on the same content. For that reason, it makes sense to direct students to content dynamically--show them only the content that would be most helpful for them at that time.

When Knewton begins working with a publisher, they start by organizing the material in the textbook into a Knewton knowledge graph. This is used to represent the ways that content is related to each other conceptually. In this way students’ progression can be evaluated automatically. This gets the right content to the right student at the right time.

So how does one even begin to apply models to this sort of information? Knewton primarily utilizes the data to create models describing the learners, and models describing the educational content.

Modeling Learners

The model of the learner is individualized to each student. After a student has completed some amount of graded content, the system has some idea of their capability. Knewton can then model the likelihood that a student will correctly answer some future question. Quiz questions can then be presented that are neither too hard nor too easy.

Modeling Content

When recommending new content for a student, the system avoids any content that is predicted to have a likelihood of either close to 0 (indicating the student will most likely not learn or retain this information) or 1 (which indicates that the student is familiar with the concepts and does not need any further instruction).

All material is given a score for how difficult it is based on the number of students who historically found it difficult. This value is used in the above model of likelihood a student will get it correct.

In addition, the content is judged for how it engages the students. If students generally move through the content with few breaks it is considered engaging – while content that is consistently associated with long breaks, is considered not engaging. Response time is summed up for all students to give a value for a typical response time for some given content.

How These Models are Used

Knewton uses this data in several different business purposes
1. Generate recommendations for students--what is the best content for that student to consume right now?
2. Analytics--are students on track? What do they need to do in order to pass the next assessment of their skills?
3. Content insights for the creators--what content is most effective? Are there any gaps in content?
4. Classroom dashboards for teachers--how is the class doing? Who is falling behind?

About Author

Leave a Comment

No comments found.

View Posts by Categories


Our Recent Popular Posts


View Posts by Tags

#python #trainwithnycdsa 2019 2020 Revenue 3-points agriculture air quality airbnb airline alcohol Alex Baransky algorithm alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus ames dataset ames housing dataset apartment rent API Application artist aws bank loans beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep boston safety Bundles cake recipe California Cancer Research capstone car price Career Career Day citibike classic cars classpass clustering Coding Course Demo Course Report covid 19 credit credit card crime frequency crops D3.js data data analysis Data Analyst data analytics data for tripadvisor reviews data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization database Deep Learning Demo Day Discount disney dplyr drug data e-commerce economy employee employee burnout employer networking environment feature engineering Finance Financial Data Science fitness studio Flask flight delay gbm Get Hired ggplot2 googleVis H20 Hadoop hallmark holiday movie happiness healthcare frauds higgs boson Hiring hiring partner events Hiring Partners hotels housing housing data housing predictions housing price hy-vee Income Industry Experts Injuries Instructor Blog Instructor Interview insurance italki Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter las vegas airport lasso regression Lead Data Scienctist Lead Data Scientist leaflet league linear regression Logistic Regression machine learning Maps market matplotlib Medical Research Meet the team meetup methal health miami beach movie music Napoli NBA netflix Networking neural network Neural networks New Courses NHL nlp NYC NYC Data Science nyc data science academy NYC Open Data nyc property NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time performance phoenix pollutants Portfolio Development precision measurement prediction Prework Programming public safety PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R Data Analysis R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn seafood type Selenium sentiment analysis sentiment classification Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau teachers team team performance TensorFlow Testimonial tf-idf Top Data Science Bootcamp Top manufacturing companies Transfers tweets twitter videos visualization wallstreet wallstreetbets web scraping Weekend Course What to expect whiskey whiskeyadvocate wildfire word cloud word2vec XGBoost yelp youtube trending ZORI