Role of item analysis in post validation of multiple choice questions in formative assessment of medical students.

Autor: K., Sajitha, Permi, Harish S., Rao, Chandrika, H.L., Kishan Prasad
Předmět:
Zdroj: Nitte University Journal of Health Science; Dec2015, Vol. 5 Issue 4, p58-61, 4p
Abstrakt: Background: Multiple choice questions (MCQ) are used in the assessment of students in various fields. By this method of assessment it is possible to cover a wide range of topics in less amount of time. However the reliability of the test depends on the quality of the MCQ. The MCQ can be evaluated based on the Difficulty Index (DIF I), Discriminatory Index (Dl) and Distracter Efficiency (DE). Objectives: To evaluate the MCQs based on the Difficulty Index (DIF I), Discriminatory Index (Dl) & Distracter Efficiency (DE) and develop a valid pool of questions. Also to assess learner performance and discriminate between students of higher and lower abilities. Materials and Methods: A total of 120 students were assessed based on multiple choice questions in pathology. The number of items were 20 and the number of distracters were 60. Data was entered and analyzed in MS Excel 2007 and simple proportions, mean and standard deviations were calculated. Results: Mean and standard deviations for DIF I, Dl and DE were 57.8 ± 17.4%, 0.27 ± 0.17 and 84.98 ± 20.2% respectively. Out of the 20 items, 11 items had good level of DIF I (31 - 60%), eight (8) items were considered easy (DIF I > 61%) and one (1) item was considered difficult (DIF I < 30). Mean Dl in present study was 0.27 ±0.17. Analysis of the Dl showed good discrimination power in eighteen (18) of the items. Out of the 60 distracters, nine (9) were non - functional distracters (NFD) and were seen in eight items. Out of these, seven items had one NFD each and one item had two NFD. Conclusions: The study emphasizes on the importance of use of item analysis in construction of good quality MCQs and also in the evaluation of learner performance. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index