Machine Learning and Data Analysis to Improve Vocational Rehabilitation Placement
Opportunities for Ohioans with Disabilities provides Vocational Rehabilitation (VR) services to individuals with disabilities, helping participants find meaningful and accessible employment. Although Ohio has the third-largest number of apprentices in the country, there are no documented VR participants in apprenticeship programs. By analyzing VR data and apprenticeship data, my research seeks to find overlapping trends in the datasets. I matched the VR and apprenticeship data by their common variable of occupation code. I explored the demographics of participants in both programs, identified top apprenticeship occupations and programs in each region, and did a preliminary machine learning cluster analysis. From the results of the cluster analysis, apprentices and VR participants each group together in different industry/geographic clusters. However, further research with additional variables could improve the richness of cluster analysis. My results also show there are VR participants who would be good candidates for apprenticeship programs based on their geographic location and job goals. Opportunities for Ohioans with Disabilities are now incorporating these findings into their process of identifying apprenticeships for VR participants.
Vocational Rehabilitation, Public policy, Machine learning, Apprenticeship, Disability policy