Item analysis of university-wide multiple choice objective examinations: the experience of a Nigerian private university

Quality & Quantity, Mar 2017

Teachers and Students worldwide often dance to the tune of tests and examinations. Assessments are powerful tools for catalyzing the achievement of educational goals, especially if done rightly. One of the tools for ‘doing it rightly’ is item analysis. The core objectives for this study, therefore, were: ascertaining the item difficulty and distractive indices of the university wide courses. A range of 112–1956 undergraduate students participated in this study. With the use of secondary data, the ex-post facto design was adopted for this project. In virtually all cases, majority of the items (ranging between 65% and 97% of the 70 items fielded in each course) did not meet psychometric standard in terms of difficulty and distractive indices and consequently needed to be moderated or deleted. Considering the importance of these courses, the need to apply item analyses when developing these tests was emphasized.

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Item analysis of university-wide multiple choice objective examinations: the experience of a Nigerian private university

Item analysis of university-wide multiple choice objective examinations: the experience of a Nigerian private university Jonathan A. Odukoya 0 1 Olajide Adekeye 0 1 Angie O. Igbinoba 0 1 A. Afolabi 0 1 0 Covenant University , Ota , Nigeria 1 & Jonathan A. Odukoya Teachers and Students worldwide often dance to the tune of tests and examinations. Assessments are powerful tools for catalyzing the achievement of educational goals, especially if done rightly. One of the tools for 'doing it rightly' is item analysis. The core objectives for this study, therefore, were: ascertaining the item difficulty and distractive indices of the university wide courses. A range of 112-1956 undergraduate students participated in this study. With the use of secondary data, the ex-post facto design was adopted for this project. In virtually all cases, majority of the items (ranging between 65% and 97% of the 70 items fielded in each course) did not meet psychometric standard in terms of difficulty and distractive indices and consequently needed to be moderated or deleted. Considering the importance of these courses, the need to apply item analyses when developing these tests was emphasized. Item analysis; Multiple choice questions; Examination; Dificulty Index 1 Introduction 1.1 Statement of problem 1.2 Statement of significance 1.3 Statement of objectives 1.4 Research questions 2 Method Distractive index ¼ Number of times an option was selected Total number of respondents Difficulty index ¼ Number of respondents who selected the right option Total number of respondents 3 Results 4 Discussion A (%) B (%) C (%) D (%) E (%) Comment Table 1 continued A (%) B (%) C (%) D (%) E (%) Comment NM Description 1. Items that are okay 2. Items that are fairly okay 3. Items that need moderation (NM) 4. Items that need serious moderation (NSM) Description 1. Items that are okay 2. Items that are fairly okay 3. Items that need moderation (NM) 4. Items that need serious moderation (NSM) Description of items 1. Items that are okay 2. Items that are fairly okay 3. Items that need moderation(NM) 4. Items that need serious moderation (NSM) Description of items 1. Items that are okay 2. Items that are fairly okay 3. Items that need moderation (NM) 4. Items that need serious moderation (NSM) 11.4 22.9 17.1 48.6 5 Recommendations and conclusion Appendix 1 See Table 6. Table 6 GXX 121 full table of results ITEMS A (%) B (%) C (%) D (%) E (%) Multiple Table 6 continued ITEMS A (%) B (%) C (%) D (%) E (%) Multiple Table 6 continued ITEMS A (%) B (%) C (%) D (%) E (%) Multiple Appendix 2 See Table 7. HXX 421 full table of results A (%) B (%) C (%) D (%) E (%) Table 7 continued A (%) B (%) C (%) D (%) E (%) Appendix 3 See Table 8. TXX 121 full table of results A (%) B (%) C (%) D (%) Multiple Table 8 continued A (%) B (%) C (%) D (%) Multiple Ary , D. , Jacobs , L.C. , Razavieh , A. : Introduction to Research in Education, 6th edn. Wadsworth, California ( 2002 ) Bichi , A. A. : Item analysis using a derived science achievement test data . Int. J. Sci. Res . 4 ( 5 ). www.ijsr.net ( 2015 ) Boopathiraj , C. , Chellamani , K. : Analysis of test items on difficulty level and discrimination index in the test for research in education . Int. J. Soc. Sci. Interdiscip. Res . 2 , 2 ( 2013 ) Cechova , I. , Neubauer , J. , Sedlacik , M. : Computer-adaptive testing: item analysis and statistics for effective testing . In: Proceedings of the 13th European Conference on E-Learning. http://apps.webofknowledge. com/. (2014) El-Uri , F.I. , Malas , N. : Analysis of use of a single best answer format in an undergraduate medical examination . Qatar Med. J . 1 , 3 - 6 ( 2013 ) Gochyyev , P. , Sabers , D. : Item analysis . J. Res. Methods . https://srmo.sagepub.com/view/encyc-of-researchdesign/n199.xml. ( 2010 ) Instructional Assessment Resources: Item analysis . Instructional Assessment Resources . http://www.utexas. edu/academic/ctl/assessment/iar/students/report/itemanalysis.php ( 2011 ) Kehoe , J. : Basic item analysis for multiple-choice tests . Pract. Assess. Res. Eval . 4 ( 10 ). http://PAREonline. net/getvn. asp?v=4&n= 10 ( 1995 ) Sabri , Shafizan: Item analysis of student comprehensive test for research in teaching beginner string ensemble using model based teaching among music students in public universities . Int. J. Educ. Res . 1 , 12 ( 2013 ) Suruchi , Rana , S.R. : Test item analysis and relationship between difficulty level and discrimination index of test items in an achievement test in biology . Indian J. Res . 3 ( 6 ), 56 - 58 ( 2015 ) Tavakol , M. , Dennick , R. : Post-examination analysis of objective tests . Med. Teach . 33 ( 6 ), 447 - 458 . http:// www.medicalteacher. org/medteach_wip/pages/home .htm ( 2011 )


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Jonathan A. Odukoya, Olajide Adekeye, Angie O. Igbinoba, A. Afolabi. Item analysis of university-wide multiple choice objective examinations: the experience of a Nigerian private university, Quality & Quantity, 2017, 1-15, DOI: 10.1007/s11135-017-0499-2