IRT stands for Item Response Theory, a family of mathematical models used to explain the relationship between a person's underlying ability (or latent trait) and their responses to individual items on a test or assessment. It's also known as Latent Response Theory.
Here's a breakdown:
- Item: A question, task, or statement on a test or assessment.
- Response: The answer, action, or reaction a person gives to an item.
- Latent Trait: An unobservable characteristic or attribute, like mathematical ability, reading comprehension, anxiety, or depression, that IRT aims to measure.
How IRT Works:
IRT models predict the probability of a person giving a particular response to an item, based on their level of the latent trait being measured. Unlike classical test theory, IRT focuses on item characteristics and individual performance simultaneously, allowing for a more nuanced understanding of both.
For example, consider a math test designed to measure mathematical ability. IRT would model the probability that a student with a certain level of mathematical ability will answer a particular math problem correctly. This probability is influenced by characteristics of the student (their ability level) and characteristics of the item (its difficulty and how well it discriminates between students of different ability levels).
Key Concepts in IRT:
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Item Characteristic Curve (ICC): A graphical representation of the relationship between a person's latent trait level and the probability of them responding correctly to an item.
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Item Difficulty: Indicates how challenging an item is. A more difficult item will require a higher level of the latent trait to answer correctly.
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Item Discrimination: Measures how well an item differentiates between individuals with different levels of the latent trait. A good discriminating item will be answered correctly by those with high levels of the trait and incorrectly by those with low levels.
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Guessing Parameter: Accounts for the possibility that a person might guess the correct answer, even if they don't possess the underlying trait being measured. This is particularly relevant for multiple-choice items.
Advantages of IRT:
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Item Banking: IRT allows for the creation of item banks, where items are calibrated and can be used to create tests of varying difficulty levels that are still comparable.
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Adaptive Testing: IRT is the foundation for adaptive testing, where the difficulty of the items presented to a test-taker adjusts based on their performance. This allows for more efficient and precise measurement.
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Test Equating: IRT can be used to equate scores across different forms of a test, ensuring fairness and comparability.
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Item Analysis: IRT provides valuable information about the quality and characteristics of individual items, allowing for improvement of test development.
Applications of IRT:
IRT is widely used in various fields, including:
- Educational Testing: Standardized tests, classroom assessments.
- Psychological Measurement: Personality assessments, diagnostic tools.
- Health Outcomes Measurement: Patient-reported outcomes, quality of life scales.
- Market Research: Customer satisfaction surveys, brand perception studies.
In summary, Item Response Theory (IRT) offers a powerful framework for developing, analyzing, and scoring tests and assessments by linking a person's ability or trait to their probability of answering a specific item correctly. This approach provides a more detailed and sophisticated understanding of measurement than traditional methods.
