Placement opportunities for human factors engineering and ergonomics professionals in industry and government/military positions

Loomer, Sara; Kish, Michelle; Moroney, William F.

doi:10.1037/e577712012-053

Cited by 1 publication

(1 citation statement)

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“…We assume that the stated educational and experience requirements as well as job descriptions accurately reflect the demands of HF/E jobs, and that these data should therefore be taken into account in development and revision of HF/E curricula and programs in the academia. on placement opportunities for HF/E professionals annually for over 10 years (1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007) in the proceedings of the HFES annual meetings (Moroney, & Adams, 1996;Moroney, Sottile, & Blinn, 1996;Moroney, Anderson, & Soest, 1997;Moroney, Proulx, & Parker, 1997;Cummings, Barshay, Lesaigle, & Moroney 1998;Cummings-Hill, Means, Harrison, & Moroney, 1999;Schoeling, Goliber, & Moroney, 2001;Anderson, Bakowski, & Moroney, 2005;Loomer, Kish, & Moroney, 2006;Moroney, 2007). These data describe the hiring expectations during the aforementioned time period.…”

Section: Introductionmentioning

confidence: 94%

Archival Human Factors Jobs Database as a Tool for Tracking Trends in Skills and Knowledge Expectations in the Labor Market

Rantanen¹,

Claeys²,

Roder

et al. 2013

Proceedings of the Human Factors and Ergonomics Society Annual

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To educate the future human factors/ergonomics workforce and meet the demand for new professionals in the field, academic institutions must pay close attention to the ever-changing skills and knowledge expectations in the labor market. These trends are not easy to track, however. Surveys of new professionals about their experiences in their first jobs or surveys of employers about their experiences with new hires suffer from low response rates, nonresponse bias, and the one-time nature of survey research. A better way to track labor market trends is to continually analyze human factors job postings for education and experience requirements specified in them. This paper describes development of a database for that purpose. We also discuss ways of analyzing unstructured text data in the database. The results of analyses of these data include summary statistics of frequencies and their correlations, clusters of similar jobs, and a continually updated mathematical model to classify jobs in the database. These results will be subjected to longitudinal analyses when the database contains sufficient data.

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