Strides in Development of Medical Education

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Designing a Valid and Reliable Tool for Assessing Academic Educational Environment in Health Schools of Hormozgan University of Medical Sciences

Document Type : Original Article

Authors

1 Ph.D. in Medical Education, Associate Professor, Department of Medical Education, Medical Education Development Center, Virtual School AND School of Medicine, Tehran University of Medical Sciences, Tehran, Iran

2 M.Sc. Student in Medical Education, Virtual School, Tehran University of Medical Sciences, Tehran & Associate Professor, Department of Public Health, School of Health, Hormozgan University of Medical Sciences, Bandar Abbas, Iran

3 Ph.D. in Nursing Education, Assistant Professor, Medical Education Research Center, Medical Education Development Center, Guilan University of Medical Sciences, Rasht, Iran

4 Ph.D. in Biostatistics, Lecturer, Department of Public Health, School of Health, Hormozgan University of Medical Sciences, Bandar Abbas, Iran

Abstract

  Background & Objective: Educational environment is an important determinant in success of a curriculum The quality of educational environment is one of the elements of effective learning The aim of this study was designing a valid and reliable tool for assessing academic educational environment in schools of health   Methods: Using a theoretical sampling method eight students and three faculty members of School of Health Hormozgan University of Medical Sciences (Iran) were interviewed and 81 items related to educational environment were extracted These items were classified in six domains including school atmosphere teaching faculty members students educational equipments and facilities and physical environment Expert panels and assessing item impact were used to determine face validity and content validity ratio and index were used to determine content validity of the tool To determine its construct validity 250 students in completed the questionnaires and confirmatory factor analysis was applied Reliability of the tool was determined by Cronbachs Alpha and intracluster correlation coefficient   Results: Due to expert panel and calculating item impact and content validity ratio and index the tool items decreased from 81 to 56 The results of confirmatory factor analysis showed that all of factor loadings were significant in level of 005 Cronbachs Alpha for total items was 094 and for six domains ranged from 065 to 085 Moreover intracluster correlation coefficient for total items was 094 Conclusion: The designed tool has good validity and reliability and can be used as a suitable tool for assessing academic educational environment in schools of health

Keywords

References
  1. The Executive Council, The World Federation for Medical Education. International standards in medical education: assessment and accreditation of medical schools’ -educational programmers. A WFME position paper. Med Educ 1998; 32(5):549-58.
  2. Genn JM. AMEE Medical Education Guide No. 23 (Part 1): Curriculum, environment, climate, quality and change in medical education—a unifying perspective. Med Teach 2001; 23(4):337-44.
  3. McAleer SRS. What is educational climate? Med Teach 2001; 23(4):333-4.
  4. Harden RM: The learning environment and the curriculum. Med Teach 2001; 23(4):335-6.
  5. Ludtke O, Robitzsch A, Trautwein U, Kunter M. Assessing the impact of learning environments: How to use student ratings of classroom or school characteristics in multilevel modeling. Contemp Educ Psychol 2009; 34(2):120–31.
  6. Karabenick SA. Perceived achievement goal structure and college student help seeking. Journal of Educational Psychology 2004; 96(3):569–81.
  7. Roff S, McAleer S, Harden RM, Al-Qahtani M, Ahmed AU, Deza H, et al. Development and validation of the Dundee ready education environment measure (DREEM). Med Teach 1997; 19(4):295-99.
  8. Varma R, Tiyagi E, Gupta JK. Determining the quality of educational climate across multiple undergraduate teaching sites using the DREEM inventory. BMC Med Educ 2005; 5:8.
  9. Soltani Arabshahi K, Kouhpayezadeh J, Sobuti B. The Educational Environment of Main Clinical Wards in Educational Hospitals Affiliated to Iran University of Medical Sciences: Learners' Viewpoints Based on DREEM Model. Iran J Med Educ 2008, 8(1): 43-50. [In Persian]
  10. Mayya SS, Roff S. Students’ perceptions of the educational environment: a comparison of academic achievers and under-achievers at Kasturba Medical College, India. Educ Health 2004; 17(3): 280-91.
  11. Roff S, McAleer S, Ifere OS, Bhattacharya S. A global diagnostic tool for measuring educational environment: Comparing Nigeria and Nepal. Med Teach 2001; 23(4): 378-82.
  12. Pimparyon P, Roff S, Mcaleer S. Educational environment, student approaches to learning and academic achievement in a Thai nursing school. Med Teach 2000; 22(4): 359-64.
  13. Henderson A, Cooke M, Creedy DK, Walker R. Nursing students' perceptions of learning in practice environments: A review. Nurse Educ Today 2012; 32(3):299–302.
  14. Aghamolaei T, Fazel I. Medical students' perceptions of the educational environment at an Iranian Medical Sciences University. BMC Med Educ 2010; 29; 10:87.
  15. Hajizadeh E, Asghari M. Statistical methods and analyses in health and biosciences: a research methodological approach. Tehran: Jahade Daneshgahi; 2011. [In Persian].
  16. Lawsche CH. A quantitative approach to content validity. Pers Psychol 1975; 28(4), 563-75.
  17. Vakili MM, Hidarnia AR, Niknami S. Development and psychometric of an Interpersonal Communication skills scale among Zanjan Health Volunteers. Hayat 2012; 18(1): 5-18. [In Persian]
  18. Waltz CF, Bausell RB. Nursing research: Design, statistics, and computer analysis (2en ed). Philadelphia: F. A. Davis Company; 1983.
  19. Sarmad Z, Bazargan A, Hejazi E. Research Methods in Behavioral Sciences. Tehran: Agah; 2005. [In Persian]
  20. Kline P. Principles and practice of structural equation modeling. 2nd ed. New York :The Guilford Press; 2005.
  21. Mardia KV. Measures of multivariate skewness and kurtosis with applications. Biometrika Trust 1970; 57(3):519-30.
  22. Kimberlin CL, Winterstein AG. Validity and reliability of measurement instruments used in research. Am J Health Syst Pharm 2008; 65(23):2276-84.
  23. Lacasse Y, Godbout C, Series F. Health related quality of life in obstructive sleep apnea. Eur Respir J 2002; 19(3): 499-503.
  24. Juniper EF, Guyott GH, Streiner DL. Clinical impact versus factor analysis for quality of life questionnaire construction. J Clin Epidemiol 1997; 50(3):233-8.
  25. Polit DF, Tatano Beck C. Essentials of Nursing Research. Appraising Evidence for Nursing Practice. 7th ed. Philadelphia: LippincottWilliams &Wilkins; 2010.
  26. Bentler PM. Comparative fit indexes in structural models. 107(2):238−46. Psychol Bull 1990;
  27. Stevens J. Applied multivariate statistics for the social sciences. New Jersey: Lawrence Erblaum Associates, Inc; 1996.
  28. Bollen KA, Long JS. Testing structural equation models. Publications, Inc; 1993. California: Sage
  29. Marsh HW, Balla JR, McDonald RP. Goodness of fit indices in confirmatory factor analysis: the effect of sample size. Psycholol Bull 1988;103(3):391–410.
  30. Brown TA. Confirmatory Factor Analysis for Applied Research. New York: The Guilford Press; 2006.
  31. Kline RB. Principles and practice of structural equation modeling. New York: The Guilford Press; 2010.
  32. Fleiss JL. The Design and Analysis of Clinical Experiments. New York: Wiley and Sons, Inc; 1986.
Strides in Development of Medical Education
Volume 11, Issue 1
May 2014
Pages 45-54
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