The abrupt transition from face-to-face to online anatomy teaching amidst the COVID-19 pandemic has posed great challenges to anatomy lecturers in Malaysia, as they have had to adapt to new skills to prepare and deliver online classes. These online classes were delivered either synchronously via a web teleconferencing application or asynchronously through pre-recorded videos that were uploaded to the learning management system (LMS). The online delivery of anatomy practical classes has become a major concern among anatomy lecturers and students, especially in public institutions, as there is a lack of hands-on experience and social interaction. Nevertheless, some private medical schools have adapted well to both online lectures and practical classes, as they had been venturing towards online learning and virtual reality tools even before the pandemic commenced. The Malaysian Anatomical Association (MAA) webinar, “Transformation of Anatomy Education in Malaysia during COVID-19 Pandemic”, discussed the issues related to lecturers’ and students’ receptivity to online anatomy classes. This study discusses the issues related to online anatomy teaching and learning (T&L) and the actions taken by the university’s governance and anatomy faculty members to resolve the issues discussed in the academic discourse.

Background: The Anatomy Education Environment Measurement Inventory (AEEMI) evaluates the perception of medical students of educational climates with regard to teaching and learning anatomy. The study aimed to cross-validate the AEEMI, which was previously studied in a public medical school, and proposed a valid universal model of AEEMI across public and private medical schools in Malaysia.Methods: The initial 11-factor and 132-item AEEMI was distributed to 1,930 pre-clinical and clinical year medical students from 11 medical schools in Malaysia. The study examined the construct validity of the AEEMI using exploratory and confirmatory factor analyses. The best-fit model of AEEMI was achieved using five factors and 26 items (ꭓ2 = 3300.71 (df = 1680), P < 0.001, ꭓ2/df = 1.965, RMSEA = 0.018, GFI = 0.929, CFI = 0.962, NFI = 0.927, TLI = 0.956) with Cronbach’s alpha values ranging from 0.621 to 0.927.Results: Findings of the cross-validation across institutions and phases of medical training indicated that the AEEMI measures nearly the same constructs as the previously validated version with several modifications to the item placement within each factor.Conclusions: These results confirmed that variability exists within factors of the anatomy education environment among institutions. Hence, with modifications to the internal structure, the proposed model of the AEEMI can be considered universally applicable in the Malaysian context and thus can be used as one of the tools for auditing and benchmarking the anatomy curriculum.

Background The Anatomy Education Environment Measurement Inventory (AEEMI) evaluates the perception of medical students of educational climates with regard to teaching and learning anatomy. The study aimed to cross-validate the AEEMI, which was previously studied in a public medical school, and proposed a valid universal model of AEEMI across public and private medical schools in Malaysia. Methods The initial 11-factor and 132-item AEEMI was distributed to 1930 pre-clinical and clinical year medical students from 11 medical schools in Malaysia. The study examined the construct validity of the AEEMI using exploratory and confirmatory factor analyses. Results The best-fit model of AEEMI was achieved using 5 factors and 26 items (χ 2 = 3300.71 (df = 1680), P < 0.001, χ 2/df = 1.965, Root Mean Square of Error Approximation (RMSEA) = 0.018, Goodness-of-fit Index (GFI) = 0.929, Comparative Fit Index (CFI) = 0.962, Normed Fit Index (NFI) = 0.927, Tucker–Lewis Index (TLI) = 0.956) with Cronbach’s alpha values ranging from 0.621 to 0.927. Findings of the cross-validation across institutions and phases of medical training indicated that the AEEMI measures nearly the same constructs as the previously validated version with several modifications to the item placement within each factor. Conclusions These results confirmed that variability exists within factors of the anatomy education environment among institutions. Hence, with modifications to the internal structure, the proposed model of the AEEMI can be considered universally applicable in the Malaysian context and thus can be used as one of the tools for auditing and benchmarking the anatomy curriculum.

A well-designed assessment has beneficial impacts on students’ learning and competency attainment. Failure in obtaining psychomotor learning competency, lack of understanding of assessment principles among instructors, unoptimized information and technology facilities, and difficulties in ensuring the integrity of online examination are among the threats to validity of online anatomy assessment during the COVID-19 pandemic. To ensure the validity of anatomy assessment during the pandemic, it is important to adopt several educational principles into the assessment design. We solidify the input discussed in the Malaysian Anatomical Association webinar 2021, on the challenges of anatomy online assessment and proposed six solutions to the challenges, namely adopting the programmatic assessment design, conducting small group in-person high stake examination, modifying assessment policy, utilizing question bank software, upgrading ICT facilities, and offering the ICT training to the students and instructors. It is envisioned that anatomy assessment are future ready are adaptive to change.

Background: The Anatomy Education Environment Measurement Inventory (AEEMI) evaluates the perception of medical students of educational climates with regard to teaching and learning anatomy. The study aimed to cross-validate the AEEMI, which was previously studied in a public medical school, and proposed a valid universal model of AEEMI across public and private medical schools in Malaysia. Methods: The initial 11-factor and 132-item AEEMI was distributed to 1,930 pre-clinical and clinical year medical students from 11 medical schools in Malaysia. The study examined the construct validity of the AEEMI using exploratory and confirmatory factor analyses. Results: The best-fit model of AEEMI was achieved using 5 factors and 26 items (χ 2 = 3300.71 (df = 1680), P < 0.001, χ 2/df = 1.965, Root Mean Square of Error Approximation (RMSEA) = 0.018, Goodness-of-fit Index (GFI) = 0.929, Comparative Fit Index (CFI) = 0.962, Normed Fit Index (NFI) = 0.927, Tucker–Lewis Index (TLI) = 0.956) with Cronbach’s alpha values ranging from 0.621 to 0.927. Findings of the cross-validation across institutions and phases of medical training indicated that the AEEMI measures nearly the same constructs as the previously validated version with several modifications to the item placement within each factor. Conclusions: These results confirmed that variability exists within factors of the anatomy education environment among institutions. Hence, with modifications to the internal structure, the proposed model of the AEEMI can be considered universally applicable in the Malaysian context and thus can be used as one of the tools for auditing and benchmarking the anatomy curriculum.