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空军工作兴趣导航器(AF-WIN)以改善人与工作的匹配度:开发、验证与初步实施。

Air Force Work Interest Navigator (AF-WIN) to improve person-job match: Development, validation, and initial implementation.

作者信息

Johnson James F, Romay Sophie, Barron Laura G

机构信息

Air Force Personnel Center, Randolph AFB, Texas.

Air Education and Training Command, Randolph AFB, Texas.

出版信息

Mil Psychol. 2020 Feb 4;32(1):111-126. doi: 10.1080/08995605.2019.1652483. eCollection 2020.

Abstract

This article describes development and validation of a web-based vocational interest tool designed to help recruits and re-trainees identify enlisted career fields that match their preferences for work contexts, activities, and functional roles in support of the Air Force mission. The tool has recently been implemented for use by members considering re-training, and is undergoing pilot testing for potential use in the recruiting process. We first describe how the AF-WIN was developed, based on adaptation of the taxonomy from a Navy vocational interest tool (Navy's Job Opportunities in the Navy [JOIN]), followed by surveys of subject matter experts (SMEs) in 132 Air Force career fields on relevant job markers. We then describe a validation study in which job incumbents completed the AF-WIN and reported their level of job satisfaction within their current career field; results show that incumbents the AF-WIN algorithm identified as a good match for their career field reported substantially higher levels of job satisfaction than incumbents identified as a relatively poor match based on the tool. Finally, we provide results from initial beta-testing of the tool in a sample of recent enlisted trainees on perceived accuracy, utility, and functionality of the tool for use in the initial job assignment process.

摘要

本文介绍了一种基于网络的职业兴趣工具的开发与验证情况。该工具旨在帮助新兵和再培训人员确定与他们对工作环境、活动及职能角色的偏好相匹配的现役职业领域,以支持空军任务。该工具最近已供考虑再培训的人员使用,并正在进行试点测试,以确定其在征兵过程中潜在的适用性。我们首先描述了空军职业兴趣网络(AF-WIN)是如何基于对海军职业兴趣工具(海军工作机会[JOIN])的分类法进行改编而开发的,随后对132个空军职业领域的主题专家(SME)进行了有关相关工作标识的调查。然后,我们描述了一项验证研究,在职人员完成了AF-WIN并报告了他们在当前职业领域内的工作满意度水平;结果表明,根据AF-WIN算法被确定为与他们的职业领域匹配度高的在职人员,其报告的工作满意度水平明显高于基于该工具被确定为匹配度相对较低的在职人员。最后,我们给出了该工具在最近入伍的新兵样本中进行初步测试的结果,内容涉及该工具在初始工作分配过程中的感知准确性、实用性和功能。

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