A Computer Adaptive Test (CAT) is a method of administering tests that dynamically adjusts the difficulty of successive questions based on the examinee’s performance on previous ones. The primary objective is to measure the test taker’s ability level more accurately and efficiently.
Definition
A Computer Adaptive Test (CAT) represents a testing methodology in which the difficulty level of questions is adapted in real-time to the test taker’s ability. This adaptive mechanism is a stark contrast to traditional fixed-form tests, where all test-takers receive the same set of questions with predetermined difficulty levels.
Key Features of CAT
- Dynamic Adjustability: Each question’s difficulty is tailored based on the test taker’s preceding answers.
- Efficiency: Fewer questions are needed to determine the examinee’s ability level accurately.
- Immediate Feedback: Some CATs can provide instant scoring and analysis.
- Personalization: Each individual’s test experience is unique and closely aligned with their ability.
How Does CAT Work?
Initial Item Selection
The test begins with a question of medium difficulty. Based on the test taker’s response, the computer assesses the performance and selects the next question appropriately.
Subsequent Adjustments
After each response, the algorithm calculates a provisional score and matches it against a pre-determined item pool to select the next question that is neither too difficult nor too easy relative to the test taker’s estimated ability.
Termination Criteria
The test concludes when one of the following criteria is met:
- Maximum Number of Questions: A preset limit on the number of questions is reached.
- Measurement Precision: The adaptive algorithm determines that it has measured the examinee’s ability with sufficient precision.
- Time Limit: The specified time for the test expires.
Examples of CAT in Standardized Testing
Graduate Management Admission Test (GMAT)
The GMAT utilizes CAT to assess examinees in quantitative, verbal, and integrated reasoning sections. The adaptive mechanism ensures that the test is efficient and can pinpoint the test taker’s proficiency level effectively.
Graduate Record Examination (GRE)
Similar to GMAT, the GRE employs CAT for its quantitative and verbal sections. It adjusts question difficulty based on the test taker’s performance, making the assessment highly individualized.
Historical Context
The development of CAT stems from the principles of Item Response Theory (IRT), which originated in the mid-20th century. IRT provided the foundational models for understanding how different item characteristics relate to latent traits like ability. CAT emerged as a practical application of these theoretical models, advancing significantly with the advent of computer technology in the late 20th century.
Applicability of CAT
Advantages
- Accuracy: Provides precise measurement of ability.
- Efficiency: Reduces the number of questions needed.
- Adaptability: Can cater to a wide range of ability levels.
- Security: Reduces risks of cheating as each test is unique.
Special Considerations
- Technical Requirements: Requires robust computing infrastructure.
- Item Pool Quality: Needs a well-calibrated and extensive bank of test items.
- Algorithms: Complex algorithms are needed to maintain fairness and accuracy.
Related Terms
- Item Response Theory (IRT): A framework for modeling the relationship between a person’s latent traits and their item responses.
- P adaptive testing: A simplified form of adaptive testing where the content and question types are pre-determined, but their order can change based on the examinee’s performance.
FAQs
How is the initial question in a CAT chosen?
Can a test-taker review or change answers in a CAT?
Are CATs fair to all test-takers?
References
- Weiss, David J. “Computerized Adaptive Testing: A Primer.” Lawrence Erlbaum Associates, 2000.
- Wainer, Howard. “Computerized Adaptive Testing: A Primer.” Second Edition. Routledge, 2010.
Summary
Computer Adaptive Tests (CAT) revolutionize the assessment process by tailoring test difficulty to individual examinee performance. This approach enhances accuracy, efficiency, and fairness in measuring ability levels across a broad range of subjects and test-takers. By utilizing sophisticated algorithms and leveraging the principles of Item Response Theory, CATs present a modern, dynamic solution to traditional fixed-form testing methods.
