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The Adaptive SAT; what does that mean?

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The College Board announced in January 2022 that it was planning to finally migrate the Scholastic Aptitude Test (SAT) from paper-and-pencil to computerized delivery.  Moreover, it would make the tests “adaptive.”  But what does it mean to have an adaptive SAT?

What is the SAT?

The SAT is the most commonly used exam for university admissions in the United States, though the ACT ranks a close second.  Decades of research has shown that it accurately predicts important outcomes, such as 4-year graduation rates or GPA.  Moreover, it provides incremental validity over other predictors, such as High School GPA.  The adaptive SAT exam will use algorithms to make the test shorter, smarter, and more accurate.

Digital Assessment

Digital assessment, also known as electronic assessment or computer-based testing, refers to the delivery of exams via computers.  It’s sometimes called online assessment or internet-based assessment as well, but not all software platforms are online, some stay secure on LANs.

What is “adaptive”?

When a test is adaptive, it means that it is being delivered with a computer algorithm that will adjust the difficulty of questions based on an individual’s performance.  If you do well, you get tougher items.  If you do not do well, you get easier items.

But while this seems straightforward and logical on the surface, there is a host of technical challenges to this.  And, as researchers have delved into those challenges over the past 50 years, they have developed several approaches to how the adaptive algorithm can work.

  1. Adapt the difficulty after every single itemMultistage-testing-flow
  2. Adapt the difficulty in blocks of items (sections), aka MultiStage Testing
  3. Adapt the test in entirely different ways (e.g., decision trees based on machine learning models, or cognitive diagnostic models)

There are plenty of famous exams which use the first approach, including the NWEA MAP test and the Graduate Management Admissions Test (GMAT).  But the SAT plans to use the second approach.  There are several reasons to do so, an important one of which is that it allows you to use “testlets” which are items that are grouped together.  For example, you probably remember test questions that have a reading passage with 3-5 attached questions; well, you can’t do that if you are picking a new standalone item after every item, as with Approach #1.

So how does it work?  Each Adaptive SAT subtest will have two sections.  An examinee will finish Section 1, and then based on their performance, get a Section 2 that is tailored to them.  It’s not like it is just easy vs hard, either; there might be 30 possible Section 2s (10 each of Easy, Medium, Hard), or variations in between.  A depiction of a 3-stage test is to the right.

How do we fairly score the results if students receive different questions?  That issue has long been addressed by item response theory.

If you want to delve deeper into learning about adaptive algorithms, start over here.

Why an adaptive SAT?

The decades of research have shown adaptive testing to have well-known benefits.  It requires fewer items to achieve the same level of accuracy in scores, which means shorter exams for everyone.  It is also more secure, because not everyone sees the same items in the same order.  It can produce a more engaging assessment as well, keeping the top performers challenged and avoid the lower performers checking out after getting too frustrated by difficult items.  And, of course, using digital assessment has many advantages itself, such as faster score turnaround and enabling the use of tech-enhanced items.  So, the migration to an adaptive SAT on top of being digital will be beneficial for the students.

 

 

 

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Nathan Thompson, PhD

CEO at Assessment Systems
Nathan Thompson, PhD, is CEO and Co-Founder of Assessment Systems Corporation (ASC). He is a psychometrician, software developer, author, and researcher, and evangelist for AI and automation. His mission is to elevate the profession of psychometrics by using software to automate psychometric work like item review, job analysis, and Angoff studies, so we can focus on more innovative work. His core goal is to improve assessment throughout the world. Nate was originally trained as a psychometrician, with an honors degree at Luther College with a triple major of Math/Psych/Latin, and then a PhD in Psychometrics at the University of Minnesota. He then worked multiple roles in the testing industry, including item writer, test development manager, essay test marker, consulting psychometrician, software developer, project manager, and business leader. He is also cofounder and Membership Director at the International Association for Computerized Adaptive Testing (iacat.org). He's published 100+ papers and presentations, but his favorite remains https://scholarworks.umass.edu/pare/vol16/iss1/1/.

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