Difficulty Index, Discrimination Index and Distractor Efficiency in Multiple Choice Questions for final exam of human and growth course, College of nursing, King Saud University (Preprint)

Abstract

UNSTRUCTURED The item analysis of multiple-choice questions (MCQs) is an essential tool that can provide input on validity and reliability of items. It helps to identify items, which can be revised or discarded, thus building a quality MCQ bank. The aim of the study To evaluate the quality of MCQs by analyzing DIF, DI and DE and to find out the association of MCQs having good difficulty and discrimination indices with DE. The study conducted in the department of maternity and child health nursing at College of nursing during the academic year 2023, second semester. Students of level six who took the final exam of course ( NUR 328) human growth and development second semester academic year 2023, A total 0f 152 third year Bachelor of Nursing, human and growth course students. The item analysis explored the difficulty index (DIF I) and discrimination index (DI) with distractor effectiveness (DE). Data was kept confidential and the descriptive and inferential statistics will be computed using SPSS 22.0. Results: Of total 50 MCQs, the majority, that is, 74 (82%) MCQs had a good/acceptable level of difficulty with a mean DIF I of 94.94 ± 6.36 (mean ± SD), This indicates that, on average, the MCQs were relatively easy for the students, as the difficulty index is close to 100. The discrimination index, which assesses the ability of the MCQs to differentiate between high and low-performing students, had a mean of 0.11 and a standard deviation of 0.47. This relatively low mean value suggests that the MCQs had limited discriminatory power, meaning they did not effectively distinguish between students with different levels of performance. 150 (75%) were categorized as functional distractors (FDs). These FDs effectively served their purpose by distracting students from selecting the correct answer, challenging their knowledge and understanding. On the other hand, 50 distractors (25%) were classified as non-functional distractors (NFDs). Conclusion: The categorization of the MCQs based on distractor efficiency highlights the importance of having well-constructed and effective distractors. The presence of functional distractors challenges students' decision-making, while non-functional distractors need to be revised or replaced to improve the overall quality of the MCQs. This finding indicates a potential area for improvement in the construction and selection of MCQs to enhance their ability to differentiate student abilities.