Pin-Hsiang Huang^1,2,3
Chen-Huan Chen^2,1, Tyzh-Chang Hwang^2,4 and Boaz Shulruf^3,5
1 Taipei Veterans General Hospital
2 National Yang Ming Chiao Tung University
3 University of New South Wales
4 University of Missouri
5 University of Auckland

Academic promotion in college of medicine is critical, and many domains and subdomains of the academic performance of the applicants are reviewed during the process. However, thresholds of subdomains for successful promotion are often obscure. This study aims to propose an evidence-based approach to provide the thresholds. 

Full-time academic faculty members holding ranks of assistant professor, associate professor and full professor from College of Medicine, National Yang Ming Chiao Tung University were invited to participate. Participants responded to academic promotion scales, which included 3 domains, 21 subdomains (11 in research, 6 in service, and 4 in teaching) and 514 quantitative variables. Means and standard errors of each sub-domain for the three ranks were calculated, and the novel equal-Z model was applied to determine the thresholds for each subdomain between adjacent ranks. Z score for each subdomain was calculated, and each threshold was set by lower rank mean plus its standard error multiplied with Z score. Accuracy of classification was calculated as the percentage (0-100%) of correct classifications of upper and lower ranks based on the threshold for the subdomain. 

A total of 41 participants were enrolled with 11 assistant professors, 11 associate professors, and 19 professors. For the thresholds between assistant professor and associate professor, accuracy values were between 36.0% and 77.0%, and 17 subdomains presented accuracy more than 55%. Regarding the thresholds between associate professor and full professor, accuracy values were between 34.5% and 70.0% with 10 subdomains holding accuracy more than 55%. 

Subdomains with an accuracy equal to or larger than 55% were considered useful to discriminate teachers’ performance. The model will be fine-tuned with the growth of dataset, and it is self-adjustable forward to new trends. This study demonstrated that Equal-Z model is a feasible algorithm to define thresholds of subdomains to support academic promotion decisions. 

References (maximum three) 

1. Shulruf, B., Coombes, L., Damodaran, A., ... & Harris, P. (2018). Cut-scores revisited: feasibility of a new method for group standard setting. BMC medical education, 18(1), 1-8. 

2. Yeh, J. T., Shulruf, B., Lee, H. C., Huang, P. H., Kuo, W. H., ... & Chen, C. H. (2022). Faculty appointment and promotion in Taiwan’s medical schools, a systematic analysis. BMC Medical Education, 22, 356. https://doi.org/10.1186/s12909-022-03435-2 

3. Shulruf, B., Yang, Y. Y., Huang, P. H., Yang, L. Y., Huang, C. C., Huang, C. C., ... & Kao, S. Y. (2020). Standard setting made easy: validating the Equal Z-score (EZ) method for setting cut-score for clinical examinations. BMC Medical Education, 20(1), 1-9.