首页> 外文会议>Human Factors and Ergonomics Society annual meeting >ARCHIVAL HUMAN FACTORS JOBS DATABASE AS A TOOL FOR TRACKING TRENDS IN SKILLS AND KNOWLEDGE EXPECTATIONS IN THE LABOR MARKET
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ARCHIVAL HUMAN FACTORS JOBS DATABASE AS A TOOL FOR TRACKING TRENDS IN SKILLS AND KNOWLEDGE EXPECTATIONS IN THE LABOR MARKET

机译:人为因素将作业数据库作为跟踪劳动力市场中技能和知识预期趋势的工具

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To educate the future human factors/ergonomics workforce and meet the demand for new professionals inthe field, academic institutions must pay close attention to the ever-changing skills and knowledge expectationsin the labor market. These trends are not easy to track, however. Surveys of new professionals abouttheir experiences in their first jobs or surveys of employers about their experiences with new hires sufferfrom low response rates, nonresponse bias, and the one-time nature of survey research. A better way totrack labor market trends is to continually analyze human factors job postings for education and experiencerequirements specified in them. This paper describes development of a database for that purpose. We alsodiscuss ways of analyzing unstructured text data in the database. The results of analyses of these data includesummary statistics of frequencies and their correlations, clusters of similar jobs, and a continuallyupdated mathematical model to classify jobs in the database. These results will be subjected to longitudinalanalyses when the database contains sufficient data.
机译:教育未来的人为因素/人机工程学劳动力,并满足对新专业人员的需求 在该领域,学术机构必须密切注意不断变化的技能和知识期望 在劳动力市场上。但是,这些趋势并不容易跟踪。关于新专业人员的调查 他们在第一份工作中的经历或对雇主关于新员工的经历的调查 低响应率,无响应偏见以及调查研究的一次性性质。更好的方法 跟踪劳动力市场趋势是要不断分析人为因素的工作岗位,以获取教育和经验 其中指定的要求。本文介绍了为此目的而开发的数据库。我们也 讨论分析数据库中非结构化文本数据的方法。这些数据的分析结果包括 频率及其相关性,类似工作的集群以及连续不断的统计摘要 更新了数学模型以对数据库中的作业进行分类。这些结果将受到纵向 分析何时数据库包含足够的数据。

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