Assessment in education has always been an important issue, and each school has its own approach.
Schools can find it challenging to embed a whole-school or departmental approach to assessment that is clear, consistent and coherent: What is the purpose of the assessment? What will progression within each subject look like? What range of assessment strategies will be used? How will progress be measured? How will the evidence be shared?
Increasingly, schools are turning towards adaptive tests as part of their whole-school approach.
Adaptive tests can help schools establish a baseline measure of ability in a way that is inclusive and can accommodate the full range of student abilities.
Adaptive tests, sometimes referred to as ‘tailored tests’, are an ideal method of assessing each student as an individual and can avoid some of the shortcomings of traditional tests.
The idea of adaptive testing dates back to 1905 and the Stanford-Binet scales. These were designed to diagnose cognitive development in young children. Understanding that students who were unable to answer an easy question were unlikely to be able to answer a difficult one, Binet tailored the tests he gave by rank ordering the items in terms of difficulty. He used different stopping rules for ending the test session based on the pattern of a student's responses. With developments in technology, adaptive testing became feasible in large-scale assessment.
In a computer-adaptive test, an algorithm controls the difficulty level of the questions. Each student faces different questions according to how well they are doing during the assessment. If the student is doing well and answering questions correctly, the difficulty of the questions increases. However, if the student struggles to answer questions correctly, the algorithm presents slightly easier questions. The idea is to give questions that the student has a 50% chance of answering correctly.
CEM introduced its adaptive test for primary schools, InCAS, in 2003 and its computer-adaptive baseline test, MidYIS, for secondary schools two years later in 2005. Now around 350,000 students sit a CEM adaptive test each year.
But what benefits do adaptive tests give schools that traditional static tests do not?
Accuracy is at the heart of good assessment. Adaptive tests require a large collection of test items to ensure there are enough questions to match the varied abilities of all students taking the exam. The large collection of test items enables the computer program to select questions that are appropriate to a student’s ability.
Better targeting of student ability means that adaptive tests can give more accurate ability measurements, and fewer questions are required compared to traditional ‘flat’ tests.
Because adaptive tests require fewer questions, the test can be completed in a shorter time period. Adaptive tests do not need lengthy or multiple test sessions, therefore, more of time can be focused on teaching and learning.
Additionally, data-processing for computer-adaptive tests is quicker. For example, CEM assessments give raw scores immediately after an assessment has been completed. More detailed feedback, including standardised scores, is also available within 48 hours of returning the data to CEM.
The speed of the feedback means that teachers can start to use the information to adapt instruction and improve academic support for students straight away.
We know that students have a wide range of abilities and that they develop at different rates. Attempting a one-size-fits-all approach to assessment will disadvantage many students.
Adaptive tests tailor each question to the knowledge and abilities of the individual. Therefore, students do not need to struggle with questions that are too difficult or spend time on questions that are too easy.
Test security is also improved because no two students sit the same test.
Better assessment experience
Adaptive tests make sure that more of the test questions are in each student’s ‘learning zone’. They are given a test which is challenging but not overwhelming.
Therefore, matching the student’s ability level promotes a more student-friendly test-taking experience.
In adaptive tests, a question’s difficulty matters, and a student's score depends on the difficulty of the questions they have been given and how many of those questions they answered correctly.
Two students may have encountered the same number of questions and have answered the same number correctly, but the student who had the harder set of questions would be given a higher ability score.
We know that good assessment means good responsive teaching.
Using a computer-adaptive assessment alongside professional observations helps to inform and validate your judgements. The feedback helps to support you in making the best decisions, so that you can transform the academic outcomes of the students you teach.
Find out more
Watch the video: How does assessment data impact on student learning?
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