Developing an Achievement Test for Selected Defensive and Offensive Basketball Skills Based on the Rasch Model

Abstract

Objectives of the Study:
• Develop an achievement test to measure selected defensive and offensive basketball skills using the Rasch model.
• Examine the scientific properties (validity and reliability) of the achievement test designed based on the Rasch model.
Methodology:
The study employed a descriptive comparative approach due to its suitability for the research objectives. Data collection methods included content analysis, interviews, and questionnaires designed according to the Rasch model. The test development process involved the following steps:
• Designing test items based on the Rasch model.
• Analyzing data using statistical software (Microsoft Excel, WINSTEPS, Bilog-MG3).
Population and Sample:
• Research Population: Second-year students from the College of Physical Education at the University of Duhok and the Department of Physical Education and Sports Sciences at the University of Zakho, totaling 213 students.
• Research Sample:
o Construction Sample: A total of 149 students (69.95% of the population) were purposively selected, distributed between the University of Duhok (109 students) and the University of Zakho (40 students).
o Application Sample: A total of 64 students (30.05% of the population) were purposively selected to test the final version of the achievement test.
Key Findings:
• The Rasch model demonstrated high accuracy and objectivity in constructing cognitive tests, excluding inappropriate items to achieve reliable results.
• The model relies on sample-independent measurements, ensuring precise and unbiased estimates.
• The Rasch model provided accurate estimates of validity and reliability coefficients, enhancing measurement quality and result accuracy.
• The model showed strong capabilities in distinguishing individual differences, reflecting high sensitivity to performance variations.
• Excluding a larger number of items in the Rasch model indicates its strict adherence to rigorous standards, leading to greater precision in skill measurement.
• Statistical analyses revealed significant differences in estimates derived from the Rasch model, underscoring its superiority in delivering precise and objective measurements.
Conclusion and Recommendations:
The study concluded that the Rasch model is an effective tool for data analysis and cognitive test design in the sports field. It is recommended to adopt the Rasch model more widely in test design, train researchers and practitioners on its application, and develop user-friendly software to expand its use in other domains.