Inter-rater reliability (Reliability across researchers) A value of 0.80 or higher is generally considered to indicate that the construct being measured has good internal reliability, though it should be noted that, as the number of items in a scale increases, it may be possible to obtain a relatively high Cronbach’s α even with relatively low levels of correlation between items. There are several ways to test for internal consistency.

A test for internal consistency, such as Cronbach’s α (the Greek letter alpha), would indicate that the three “Strongly Disagree” questions should be removed from the instrument. If you have a set of 6 Likert-scale items that are designed to measure self-efficacy of students who are studying programming for the very first time and all items were stated in the positive (“I am confident I can learn programming” instead of “I am not confident I can learn programming”), then students wouldn’t answer “Strongly Agree” on three items and “Strongly Disagree” on the other three. If they did not understand while loops, then all three answers would be answered incorrectly. If your test had 100% internal consistency reliability and if a student understands while loops, then all three answers would be answered correctly. For example, suppose you are creating a multiple-choice test, and three of the questions are designed to measure one construct – while loops. It helps ensure that the various items that measure different constructs deliver consistent scores across those items. Internal consistency reliability reflects the consistency of the results of an instrument or a test. Internal consistency reliability (Reliability across items) The results of one or more measures provide evidence of reliability for the instrument. We can measure instruments for reliability in several ways. You want to ensure that the test or quiz measures the same knowledge for every student who takes it. It answers the question “Does this instrument yield repeatable results?” If you are a teacher, you know that creating a test for assessing students’ knowledge of while loops or conditional statements can be time-consuming. In both cases, we want our instrument (or tool) to be reliable.įor evaluation instruments, reliability is a measure of the consistency and stability of the participants’ results. In computing, when we enter a URL in our browser, we want the browser to return the correct site for that particular URL. When a thermometer is designed and then produced, as a consumer, we want the thermometer to accurately measure the temperature each day. For example, let’s take another instrument we use quite frequently in deciding what to wear every day–the thermometer.

Reliability in evaluation instruments is no different than reliability in other instruments used in science-and even computer science.

Reliability of test in education