Naeem Noor-I-Kiran, Hadie Siti Nurma Hanim, Ismail Irwan Mahazir, Yusoff Muhamad Saiful Bahri
Noor-i-Kiran Naeem, FCPS, MSc. MEd. Department of Medical Education, ABWA Medical College, Pakistan. Department of Medical Education, School of Medical Sciences, Universiti Sains Malaysia, Malaysia.
Siti Nurma Hanim Hadie, Ph.D. Department of Anatomy, School of Medical Sciences, Universiti Sains Malaysia, Malaysia.
Pak J Med Sci. 2023 Nov-Dec;39(6):1573-1583. doi: 10.12669/pjms.39.6.8430.
To develop and validate Digital Medical Education Environment (Digi-MEE) Instrument for measuring online learning environment in medical education.
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.
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.
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.
开发并验证用于衡量医学教育在线学习环境的数字医学教育环境（Digi-MEE）工具。
本系列研究在2022年5月至2022年12月期间纳入了696名参与者。在进行范围综述后，受邀的改良电子德尔菲法专家就衡量在线学习环境的组成部分和相关项目达成了共识。一组内容专家和一群医学生分别进行了内容和反应过程验证，以确定内容效度指数（CVI）和表面效度指数（FVI）。随后进行探索性和验证性因素分析以及可靠性分析，使用SPSS 26.0版和AMOS 26.0版确定Digi-MEE的因子结构和内部一致性。
德尔菲法专家就初始Digi-MEE版本的九个组成部分和73个项目达成了一致。Digi-MEE 2.0的CVI大于0.90，Digi-MEE 3.0的FVI为0.87。探索性因素分析得出46个项目，方差为57.18%。验证性因素分析得出最终的Digi-MEE版本，包含九个组成部分中的28个项目，拟合优度指数水平可接受。最终Digi-MEE的总体克朗巴赫α系数大于0.90，九个组成部分的系数在0.62至0.76之间。
Digi-MEE是一种有前景的有效且可靠的工具，可用于评估医学教育中的在线教育环境。内容、反应过程、因子结构和内部一致性证据支持Digi-MEE的有效性。医学院校可将Digi-MEE用作评估工具，以持续改进在线学习环境的质量。
