Question

A test is considered reliable if it:

• A. A. Measures what it is supposed to measure.
• B. B. Is easy to administer and score.
• C. C. Yields consistent results across different administrations.
• D. D. Predicts future language learning success.

Answer 1

Answer:

C. C. Yields consistent results across different administrations.

Understanding Test Reliability

• Test reliability refers to the consistency of a measure. A reliable test produces similar results under consistent conditions across different administrations or raters.
• It addresses the question: "How much measurement error is present in the scores?" A highly reliable test has minimal measurement error.
• Reliability is a necessary but not sufficient condition for validity. A test can be reliable without being valid, but it cannot be valid unless it is reliable.

Types of Reliability

• Test-Retest Reliability

  • Measures the consistency of results over time. The same test is administered to the same group of people on two different occasions.
  • A high correlation between the two sets of scores indicates good test-retest reliability.
  • Example: Administering an IQ test to the same group of students a month apart; if scores are similar, it shows good test-retest reliability.

• Parallel Forms Reliability (or Alternate Forms Reliability)

  • Measures the consistency between two different versions of the same test. Two different but equivalent forms of the test are administered to the same group of individuals.
  • This type reduces the impact of memory or practice effects from repeated testing.
  • Example: Having two different versions (Form A and Form B) of a multiple-choice exam covering the same content, and checking if students score similarly on both.

• Internal Consistency Reliability

  • Assesses the consistency of results across items within a test. It measures whether different items on a test that are supposed to measure the same construct produce similar results.
  • Methods include:
    • Split-Half Reliability: Dividing the test into two halves (e.g., odd vs. even items) and correlating the scores from the two halves.
    • Cronbach's Alpha (α): A widely used statistic that calculates the average of all possible split-half reliabilities. A higher Cronbach's Alpha (typically > 0.70 for research, > 0.90 for high-stakes tests) indicates higher internal consistency.
    • Kuder-Richardson Formula 20 (KR-20): Used for tests with dichotomous (right/wrong) items.

• Inter-Rater Reliability (or Inter-Observer Reliability)

  • Measures the consistency of judgments made by two or more independent observers or raters regarding the same behavior or performance.
  • Often used for subjective assessments, such as essay grading or behavioral observations.
  • Example: Two different teachers grading the same set of essays and their scores being highly correlated.

Reliability vs. Validity

• While reliability concerns the consistency of measurement, validity concerns the accuracy of measurement – whether a test measures what it claims to measure.
• A test can be reliable but not valid (e.g., a scale consistently shows you are 5 kg heavier, it's reliable but not valid). However, a test cannot be valid unless it is reliable.

Factors Affecting Reliability

• Test Length: Longer tests generally tend to be more reliable.
• Homogeneity of Test Items: Items measuring the same construct contribute to higher internal consistency.
• Test Difficulty: Tests that are too easy or too difficult may have lower reliability.
• Testing Conditions: Consistent and standardized administration procedures enhance reliability.
• Range of Scores: A wider range of individual differences in scores generally leads to higher reliability estimates.