The purpose of this research is to address the need for a robust system to accurately determine a cutoff score by using the Angoff method and leveraging the Rasch infit and outfit statistics of item response theory by detecting and removing misfitting items in a test.
Researchers in educational evaluation support the use of grades as a complete measure to evaluate students’ overall academic performance. In higher education, determining cutoff scores is crucial for assessing academic progress and achievement. Higher education institutions worldwide set predefined minimal standards of success, sometimes referred to as cutoff thresholds. These thresholds serve as benchmarks for assessing performance quality and determining eligibility for academic credit or advancement.
The proposed approach combines the Angoff method with Rasch item fit statistics to precisely determine the cutoff score by excluding items that do not fit well (misfitting items) in a test. This methodology holds the potential to enhance the fairness and accuracy of grading practices, ensuring that assessments align with educational objectives and provide meaningful feedback to students.
The value of this research extends to various fields where cutoff scores are used for decision-making purposes. By using Rasch item fit statistics and the Angoff method, practitioners and researchers can enhance the quality and validity of their assessments.
