In this research paper, we compare the alignment between advanced manufacturing (AM) competencies in Florida’s Career and Technical Education (CTE) AM Curriculum Framework and the U.S. Department of Labor’s Advanced Manufacturing Competency Model. AM educators are guided by state department of education documents that specify program content, while employers track the knowledge, skills, and dispositions that AM technicians require to successfully function in the workplace. The Curriculum Framework, created with input from educators and industry, shape AM curricula and course syllabi because they specify the learning outcomes that AM graduates upon completion of two-year AM degree programs. The Department of Labor’s Advanced Manufacturing Competency Model, crafted by federal policymakers and industry representatives, includes personal, academic, industry-specific, and managerial competencies needed by successful AM technicians; the Model is intended to influence technicians’ hiring, training, and evaluation. Although these documents were created by different sets of stakeholders, they “bookend” AM technicians’ school-to-career pathways. To determine the extent to which the 2019-2020 Florida AM Curriculum Framework aligns to the Department of Labor’s Advanced Manufacturing Competency Model, we used text mining to extract and compare the key competencies found in both documents. Through this approach, we compared these documents and identified: 1) frequently addressed topics; 2) verbs that guided the complexity (i.e., Bloom’s Revised Taxonomy of Learning Objectives cognitive level) of the course learning task versus workplace competency; and 3) overall match between the documents. Our results suggest that the documents overlap very little, with significant misalignments in higher-level Bloom’s verbs. We present implications for educational institutions, AM policy makers, and industry; suggest a revision cycle and process; and propose an ongoing assessment model to improve the congruence between what employers want and what is taught in two-year AM degree programs.
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Facilitating Advanced Manufacturing Technicians' Readiness in the Rural Economy: A Competency-based Deductive Approach
While rural manufacturing job availability is growing throughout the country, rural communities often lack skilled workers. Thus, it is imperative for employers to validate needed new professional competencies by understanding which skills can be taught on-the-job as well as the knowledge and abilities best gained through classroom learning and experiential learning opportunities. This enhanced understanding not only benefits employers’ hiring practices, but also it can help Career and Technical Education (CTE) programs improve curricula and expand learning opportunities to best meet students’ and employers’ needs. In this study, we triangulated industry competency model content with rural employer perspectives on new advanced manufacturing (AM) professionals’ desired competencies (i.e., the level of skill sophistication in a particular AM work area). To extract competencies for entry-level AM rural jobs, we used a deductive approach with multiple methods. First, we used Natural Language Processing (NLP) to extract, analyze, and compare the U.S. Department of Labor’s AM 2010 and 2020 Competency Models because they reflect the levels and topics AM industry professionals nationally reported as technician needs. Then, we interviewed 10 rural AM employers in North Florida to capture their perceptions of the most important competencies for new middle-skill technicians. Interview transcripts were also processed using NLP to extract competency levels and topics; we compared this output to the AM Competency Model analysis results. We deduced that the most critical competencies identified by rural AM employers required direct classroom instruction, but there was a subset of skills obtainable through on-the-job training or other experiential learning. This study, with the goal of addressing employee shortages and increasing the number of technicians ready for the workforce, has implications for rural community colleges’ AM programs curricula and the role of experiential learning.
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- Award ID(s):
- 1700581
- NSF-PAR ID:
- 10289593
- Date Published:
- Journal Name:
- 2021 ASEE Virtual Annual Conference
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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