Development and validation of Digi-MEE Instrument measuring online learning environments in medical education

Abstract

Objectives: To develop and validate Digital Medical Education Environment (Digi-MEE) Instrument for measuring online learning environment in medical education.
 Methods: This series of studies involved 696 participants from May 2022 to December 2022. Following scoping review, invited modified e-Delphi experts developed consensus on the components and related items for measuring online learning environments. A panel of content experts and a group of medical students carried out content and response-process validation to determine Content Validity Index (CVI) and Face Validity Index (FVI) respectively. This was followed by exploratory and confirmatory factor analysis and reliability analysis to determine Digi-MEE’s factorial structure and internal consistency using SPSS version 26.0 and AMOS 26.0.
 Results: Delphi experts agreed upon nine components with 73 items of initial Digi-MEE version. CVI of Digi-MEE 2.0 was more than 0.90. with FVI of Digi-MEE 3.0 of 0.87. Exploratory factor analysis yielded 46 items with 57.18% variance. Confirmatory factor analysis led to the final Digi-MEE version containing 28 items within nine components with acceptable levels of goodness of fit indices. Overall Cronbach alpha of the final Digi-MEE was more than 0.90, and for the nine components ranged between 0.62 and 0.76.
 Conclusion: Digi-MEE is a promising valid and reliable instrument to evaluate online education environment in medical education. Content, response-process, factorial structure, and internal consistency evidence support the validity of Digi-MEE. Medical schools can use Digi-MEE as an evaluation tool for the continuous quality improvement of online learning environments.
 doi: https://doi.org/10.12669/pjms.39.6.8430
 How to cite this: Naeem NK, Hadie SNH, Ismail IM, Yusoff MSB. Development and validation of Digi-MEE Instrument measuring online learning environments in medical education. Pak J Med Sci. 2023;39(6):---------. doi: https://doi.org/10.12669/pjms.39.6.8430
 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.