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Archive for the ‘Adaptive Learning’ Category

Video games and failure-based learning

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I used to teach afterschool in City of New York/Parks & Recreation’s Computer Resource Center program. Kids in the program spent a lot of time playing educational games like Logical Journey Of The Zoombinis and The Incredible Machine.

The kids would literally fight with each other to get to be the first to play these games, with an intensity that surprised me. I mean, the games are fun and everything, but they were nonviolent, with less-than state of the art graphics and no recognizable characters from TV or movies. The educational content was rarely disguised as “fun,” and yet, kids who snoozed through math class were riveted by the exact same content when it was presented in the context of Treasure Mathstorm. Read the rest of this entry »

Reverse Engineering and Knewton

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When evolutionary biologists encounter a trait in nature, they perform a process known as reverse engineering to understand why that trait existed in the past and continues to exist in the present.

Take, for example, the peacock’s tail.

Evolutionary theory is based on the idea that every adaptation must increase the organism’s reproductive fitness or it would long ago have been bred out of existence. On the face of it, the peacock’s tail poses a problem to the theory. It’s big, heavy and impractical to the point of being downright counterfunctional. The recent theory is that the tail’s very cumbersomeness advertises the peacock’s high level of overall reproductive fitness. The tail announces to peahens, “look at me, I can schlep around all this excess plumage, I must be a pretty impressive peacock.”

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Written by Knewton

September 30, 2009 at 5:27 PM

Customize your LSAT practice with “Create a Quiz”

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There are many ways to prep for the LSAT, but all the experts agree on one piece of advice: practice, practice, practice.

The LSAT tests a lot of skills. How can you make sure your practice program is right for you? Knewton has a new solution: “Create a Quiz.”

Create a Quiz is an interactive study tool that lets you tailor your practice tests to fit your needs. Looking for extra Logic Games work? Design a quiz that tests your Selection and Absolute Ordering skills. Logical Reasoning section giving you trouble? Run through a quiz of Assumption, Parallel Reasoning, and Strengthen/Weaken questions.

You can make as many quizzes as you want, in as many combinations as you can imagine. The quiz tool draws on nearly 2,000 real LSAT questions, and it shows all your results so you can track your progress. Additionally, every question features a detailed explanation written by our team of experts.

Knewton’s Create a Quiz makes LSAT prep personal and adaptive. We give you all the LSAT sections, all the question types, all the explanations—you just decide how you want to use them.

Written by Knewton

August 6, 2009 at 7:17 PM

Posted in Adaptive Learning

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A Plethora of CATs

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Knewton VP of Research David Kuntz uses the English language to explain the numbers behind his Science.

Computer-adaptive tests (CATs) come in all shapes and sizes, and you meet them everywhere: getting your driver’s license, achieving an IT certification like MCSE or CCNA, or applying for admission to business school.  Even the TV show “Are You Smarter Than A Fifth-Grader?” can be considered an adaptive assessment, albeit self-adaptive, not computer-based.  But they all have something in common: Instead of going through a set of questions in some predetermined order, the questions you face next are selected (by you or someone else) in some manner based on how you have already responded to the questions you’ve seen.

Underlying every CAT is an algorithm that selects the next item to display.  There are many such algorithms in use today. Some base selection on whether you answer a question correctly. Others adapt based on which specific incorrect response is selected.  Still others look at overall performance on groups of questions.  Some very advanced CATs don’t look like tests at all, and present tasks or activities based on what you actions you took in the preceding activities.

The GMAT has a blueprint—a set of specifications (difficulty, question type, content area, etc.) – that defines the structure and content of the test. Each question has statistical characteristics (e.g., that the question is hard or easy) and content characteristics (e.g., that the question is a Geometry item dealing with isosceles triangles). The algorithm looks at your performance on the questions you have already answered and the characteristics of each question remaining in the pool and then selects for you the question that simultaneously best satisfies the blueprint and provides the most statistical information it can, to generate the best estimate of your ability. Since people at all ability levels take the test, a large quantity of questions are needed in order to be able to provide accurate assessment for test-takers. All of these questions need to be carefully constructed, reviewed, and statistically aligned so that they contribute meaningfully to your ability estimate.

So what makes a good CAT?  In addition to a rich pool of questions of varying difficulty, it requires a robust algorithm to estimate your ability, a fast and reliable mechanism to identify the best question for you to see next, and a powerful scoring algorithm that translates the ability estimate into something meaningful. It also needs a whole series of mechanisms to ensure that you don’t see the same questions over again when you take the test more than once, and don’t see too much of one content category or another.

As you can imagine, CATs are tricky to build and maintain. One of the great things about the Knewton CAT is that it was developed by the people who actually made the GMAT (and GRE) CATs.  So all of the algorithms that select questions, estimate your ability, and score your test are as close to the real thing as you can get without actually sending your scores to a business school.

We’ll talk about how scoring works for GMAT in another post.  Until then, do your homework. 🙂

Written by Knewton

July 23, 2009 at 1:48 PM

Learning Adapted

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Branch_PB_04_stillThe word “adapt” has its roots in the Latin word aptare, meaning “to fit.” We think learning works best when it fits you specifically, the way shoes work best when they fit your feet. One on one, any competent teacher can customize the lesson to fit a student’s needs. But in groups, it can be difficult or impossible. Every classroom teacher faces the same challenge: Half the class is bored; the other half is struggling.

How do you pace a lesson so that everyone in the room is on the same page?

Technology can help. Computer programs can track your progress and serve up lesson plans or practice questions to suit your unique needs. Self-pacing helps to keep you in a state of fluid learning. When you’re working, you want to be challenged enough to stay engaged, without being so overwhelmed that you get frustrated. Software can fill the role of a personal tutor.

You’ve probably experienced adaptive learning without meaning to—in the context of video games. A well-designed game is first and foremost a self-paced learning tool. If you master the easier early levels, you move on to the harder ones. If not, you repeat the early ones. Not every game is well-balanced, but the best ones carefully balance challenges with rewards to maintain your personal flow.

At Knewton, we think adaptive learning is especially important because some of our students will face adaptive testing. The GMAT is administered as a Computer Adaptive Test. It starts with a question of medium difficulty. If you answer it correctly, you get a harder question next. If you answer incorrectly, you get an easier question. The computerized GMAT is unique to each test taker. We think the best way to practice for this kind of test is with computerized adaptive learning.

Written by Knewton

June 26, 2009 at 3:23 PM