Psychometric quality of multiple-choice questions in the residency entrance examination at the Faculty of Medicine in Batna: A tool for improving assessment practices

##plugins.themes.academic_pro.article.sidebar##

Published May 24, 2026
https://doi.org/10.62438/tunismed.v104i05.6612
Download
PDF
Vol. 104 No. 05 (2026): Tunis Med May 2026

##plugins.themes.academic_pro.article.main##

Mohamed Ridha Guedjati
Faculty of Medicine. University of Batna 2, Ezzoouhour street, Batna 05000, Algeria
Hanane Benaldjia
Faculty of Medicine. University of Batna 2, Ezzoouhour street, Batna 05000, Algeria.
Jalaleddinne Omar Bouhidel
Faculty of Medicine. University of Batna 2, Ezzoouhour street, Batna 05000, Algeria.
Adeila Dallel Taibi
Faculty of Medicine. University of Batna 2, Ezzoouhour street, Batna 05000, Algeria.
Abdesselam Hamizi
Faculty of Medicine. Constantine 3 University. Ali Mendjeli (New Town). Constantine 25000. Algeria.

Abstract

Introduction: A psychometric analysis of multiple-choice questions (MCQs) is an important step in the assessment process. It makes sure that MCQ items are valid and reliable. The residency competition is an important part of medical training. It is how we choose future doctors who
can meet the clinical and scientific requirements. Our aim is to find out what the medical residency competition's MCQs are like.
Methods: 150 multiple-choice questions (MCQs) were analysed from the October 2025 medical residency exam. There were 410 candidates in the exams. This analysis looked at the difficulty index (DIF I), the discrimination index (DI), and Cronbach's alpha coefficient.
Results: 78 (52%) of the multiple-choice questions were at a recommended/acceptable level of difficulty, with an average DIF I of 43± 2,03. 45 (30%) were too difficult. 97 items (64%) had a DI between excellent and acceptable, and 40 (26%) were rejected, with an overall average DI of 0,325± 0,017. There was a relationship between DIF I and DI (r=0.36, p<0.01). The reliability of the items was satisfactory at 0.84, as measured
by Cronbach's alpha coefficient.
Conclusion: Our study allowed us to find good MCQs to add to the question bank for future tests, as well as MCQs that needed to be changed. This thorough analysis makes sure that the assessments are valid and reliable. It makes sure that the selection process is tough and that it meets the necessary academic and practical standards.

Keywords:

QCM, concours de résidanat, Psychométrie indice de difficulté, indice de discrimination

##plugins.themes.academic_pro.article.details##

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

References

  1. Epstein RM. Assessment in medical education. New England journal of medicine. 2007;356(4):387-96.
  2. Adams NE. Bloom’s taxonomy of cognitive learning objectives. Journal of the Medical Library Association: JMLA. 2015;103(3):152.
  3. Witheridge A, Ferns G, Scott-Smith W. Revisiting Miller’s pyramid in medical education: the gap between traditional assessment and
  4. diagnostic reasoning. International Journal of Medical Education. 2019;10:191.
  5. Abey Abraham Joy, Neethu Soman, HymaV, Jiyo Chacko, Sujatha M.B., Sreelakshmi Venugopal. Item Analysis of Multiple-
  6. Choice Questions Using Difficulty and Discrimination Indices International Journal of Life Sciences, Biotechnology and Pharma
  7. Research;2025;14(9).
  8. Mohammed OEAH, Srinivasamurthy SK, Bhat R, Alhassan Eltahir YAM, Hamdy Elshamly HA, Mohammed F, Hamad B. Postgraduate
  9. Clinical Residency: The Impact of Multiple-Choice Question Quality on Exam Success Rates. Advances in Medical Education and
  10. Practice. 2025:1381-97.
  11. Vaske JJ, Beaman J, Sponarski CC. Rethinking internal consistency in Cronbach's alpha. Leisure sciences. 2017;39(2):163-73.
  12. Eleragi A, Miskeen E, Hussein K, Rezigalla AA, Adam MI, Al-Faifi JA, et al. Evaluating the multiple-choice questions quality at the
  13. College of Medicine, University of Bisha, Saudi Arabia: a three-year experience. BMC Medical Education. 2025;25(1):233.
  14. Mirbahai L, Adie J. Applying the utility index to review single best answer questions in medical education assessment. Archives of
  15. Epidemiology and Public Health. 2020;1:1-5.
  16. Yahia AIO. Post-validation item analysis to assess the validity and reliability of multiple-choice questions at a medical college with an
  17. innovative curriculum. Natl Med J India. 2021;34(6):359-62.
  18. Newton, P.E. (2013), Two Kinds of Argument? Journal of Educational Measurement, 50: 105-109.
  19. 11. Date AP, Borkar AS, Badwaik RT, Siddiqui RA, Shende TR, Dashputra AV. Item analysis as tool to validate multiple choice
  20. question bank in pharmacology. Int J Basic Clin Pharmacol. 2019;8(9):1999-2003.
  21. Pande SS, Pande SR, Parate VR, Nikam AP, Agrekar SH. Correlation between difficulty & discrimination indices of MCQs in formative
  22. exam in Physiology. South-East Asian Journal of Medical Education. 2013;7(1).
  23. Guedjati MR, Bouhidel OJ, Benaldjia H, Derdous C. The Medical Residency Examination in the Era of the Overhaul of Medical Study
  24. Programs, a Call for Reform. Reflections for New Docimological Orientations. Acta Scientific Medical Sciences. 2024 May 1;63–8.
  25. Van Der Vleuten CP, Schuwirth LW. Assessing professional competence: from methods to programmes. Medical education.
  26. ;39(3):309-17.
  27. Patil VC, Patil HV. Item analysis of medicine multiple choice questions (MCQs) for under graduate (3rd year MBBS) students.
  28. Research Journal of Pharmaceutical Biological and Chemical Sciences. 2015;6(3):1242-51.
  29. National Board of Medical Examiners. NBME Item-Writing Guide: Constructing Written Test Questions for the Health Sciences.
  30. National Board of Medical Examiners; 2024.
  31. Mitra NK, Chitra E, Wong PS, Sow CF, Binti Abd Razak SS, Er HM, Nadarajah VD. Artificial Intelligence: Opportunities and Challenges
  32. in Health Professions Education. International E-Journal of Science, Medicine & Education. 2023;17(3).
  33. Kelley TL. The selection of upper and lower groups for the validation of test items. Journal of educational psychology. 1939;30(1):17.
  34. Christian DS, Prajapati AC, Rana BM, Dave VR. Evaluation of multiple choice questions using item analysis tool: a study from
  35. a medical institute of Ahmedabad, Gujarat. Int J Community Med Public Health. 2017;4(6):1876-81.
  36. Zubairi NA, AlAhmadi TS, Ibrahim MH, Hegazi MA, Gadi FU. Effective use of Item Analysis to improve the Reliability and Validity
  37. of Undergraduate Medical Examinations: Evaluating the same exam over many years: A different approach. Pakistan Journal of
  38. Medical Sciences. 2025;41(3):810.
  39. Gebremichael MW, Baraki B, Mehari M-A, Assalfew B. Item analysis of multiple choice questions from assessment of health sciences
  40. students, Tigray, Ethiopia. BMC Medical Education. 2025;25(1):441.
  41. Wrzesińska MA, Rakoczy J, Binder-Olibrowska KW, Kostyła M, Allott VE, Harris SR, et al. Comparing structured note-taking and multiple-
  42. choice question writing as learning strategies among physiotherapy students. BMC Medical Education. 2025;25(1):1665.
  43. Srisomsak V, Sitticharoon C, Keadkraichaiwat I, Meethes S, Inpaen I. Detection of flawed multiple-choice questions in preclinical
  44. medical education using item difficulty and discrimination indices: a six-year analysis. BMC Medical Education. 2025.
  45. Hwang R, Paley M, Bull D, Omrani O, Vergara-Jalandoni D, Egbury G. A Systematic Review and Meta-Analysis on the Impact of Peer-
  46. Made MCQ Question-Bank Usage on Summative Assessments in Medical Education. Journal of Advances in Medical Education &
  47. Professionalism. 2025;13(4):259.
  48. Rahim AFA, Simok AA, Wahab SFA. A Guide for Writing Single Best Answer Questions to Assess Higher-Order Thinking Skills Based on
  49. Learning Outcomes. Education in Medicine Journal. 2022;14(2).
  50. Oc Y, Hassen H. Comparing the effectiveness of multiple-answer and single-answer multiple-choice questions in assessing student
  51. learning. Marketing Education Review. 2025;35(1):44-57.
  52. Kwa SK, Tan CW, Ng AC, Mobarak SMAS, Selamat HA. Recommendations and tips for passing the key feature problem
  53. examination. Malaysian Family Physician: the Official Journal of the Academy of Family Physicians of Malaysia. 2022;17(2):2.
  54. Guedjati MR. Le concours de résidanat de médecine, peut-il servir à autre chose qu’au classement des candidats ? Oral Communication
  55. Pédagogie Médicale 10 S25-S67 (2009)
  56. Uyanah DA, Nsikhe U. The theoretical and empirical equivalence of Cronbach alpha and Kuder-Richardson formular-20 reliability
  57. coefficients. International Research Journal of Innovations in Engineering and Technology. 2023;7(5):17.
  58. Cronbach LJ. Coefficient alpha and the internal structure of tests. psychometrika. 1951;16(3):297-334.
  59. Edelsbrunner PA, Simonsmeier BA, Schneider M. The Cronbach’s alpha of domain-specific knowledge tests before and after learning:
  60. A meta-analysis of published studies. Educational Psychology Review. 2025;37(1):4.
  61. Kumar D, Jaipurkar R, Shekhar A, Sikri G, Srinivas V. Item analysis of multiple choice questions: A quality assurance test
  62. for an assessment tool. Medical Journal Armed Forces India. 2021;77:S85-S9.
  63. Desy J, Harvey A, Weeks S, Busche KD, Martin K, Paget M, et al. The impact of systematically repairing multiple choice questions with
  64. low discrimination on assessment reliability: an interrupted time series analysis. Canadian Medical Education Journal. 2024;15(3):52-6.
  65. Lertsakulbunlue S, Kantiwong A. Development and validation of immediate self-feedback very short answer questions for medicalstudents: practical implementation of generalizability theory to estimate reliability in formative examination designs. BMC Medical
  66. Education. 2024;24(1):572.
  67. Mustafa, S., Hamid, O.E. Psychometric item/question analysis of multiple-choice questions in fixed prosthodontics exam. BMC Med
  68. Educ (2025).