Promoting the Development of STEM Tech Employability Skills: A Review of Practices and Needs in the ATE Community

认识到高素质技术人员队伍的重要性，行业和教育领导者期待社区和技术学院的技术人员计划在培养关键的学术和职业技能(非技术技能)方面提供创新、经验教训、最佳实践和指导，有助于国家科学、技术、工程和数学(STEM)基础设施的健康和安全。高级技术教育(ATE)社区的从业者和政策制定者面临着重新设想学习、环境和工作场所的紧迫性，以更好地支持个人建立关键和复杂的非技术性就业能力技能。根据对研究和实践者文献的回顾，与解决问题相关的认知就业能力技能似乎享有相对强劲的投资和知名度，但与人际关系技能相关的就业能力技能以及应对和保持积极“心态”的个人内部技能(例如，积极的态度、坚持不懈和灵活性)可能非正式地发生在雷达之下。然而，与技术技能不同，就业能力技能的定义并不明确。定性研究的结果将为教育从业者、政策制定者和雇主提供基于研究的指导，以就如何促进就业能力技能的发展做出明智的决定，并倡导所需的资源。针对技术人员教育中关于学术和职业发展的文献中的空白，有针对性的研究项目将以定性研究为特色，审查和综合关于就业能力技能的文献和专家知识。探索性实证研究探讨了三个问题。什么是就业能力技能？研究中确定的学习原则，以及为什么它们在技术环境中很重要，例如信息技术(IT)和先进制造(AM)？在IT和AM中，有哪些实践用来发展和衡量就业能力技能，以及如何具体支持代表不足的群体的需求？在劳动力规划实践、研究和政策方面，未来发展和评估就业能力技能的最有前途的方向是什么？三种定性研究方法将被用来回答研究问题。这一总体方法重复了先前对支持长期失业和就业不足的个人以及在中学后教育和初级就业中代表不足的少数族裔成人学生的一般方案所采取的方法。叙事性研究综述是由Cooper(1998,2006)和Campbell and Associates(1992)提出的研究综述的概念化。与劳动力发展、技术员教育和行业选定行业的专家信息者的访谈将加深对就业能力技能的理解。对研究和专家知识的综合进行系统审查和反复完善将评估数据饱和程度(例如，知道需要多少次访谈才能为可复制的结论提供足够的代码和主题)，并确保支持制定稳定的数据类别。

Recognizing the importance of a highly qualified technician workforce, industry and education leaders look to community and technical colleges' technician programs for innovations, lessons learned, best practices, and guidance on cultivating critical academic and career skillsets (non-technical skills) that contribute to the health and security of the nation's Science, Technology, Engineering, and Mathematics (STEM) infrastructure. Practitioners in the Advanced Technological Education (ATE) community and policy makers face an urgency to re-envision learning and environments and workplaces to better support individuals in building critical and complex non-technical employability skillsets. Based on a review of the research and practitioner literature, the cognitive employability skills associated with problem solving appear to enjoy a relatively robust level of investment and visibility, but the employability skills associated with interpersonal skills and the intrapersonal skills of coping and maintaining a positive "mindset" (e.g., positive attitude, persistence, and flexibility) are likely to occur informally and under the radar. However, unlike technical skills, employability skills are ill defined. Findings from the qualitative research study will yield research-based guidance for practitioners in education, policy makers, and employers to make informed decisions on how to promoted the development of employability skills and to advocate for needed resources. Addressing a gap in the literature on academic and career development in technician education, the targeted research project addresses will feature a qualitative research study that examines and synthesizes the literature and expert knowledge on employability skills. Three questions are investigated in the exploratory empirical research study. What are the employability skills? learning principles identified in the research and why are they important in technical contexts, such and Information Technology (IT) and Advanced Manufacturing (AM)? What are the practices used to develop ad measure employability skills in IT and AM and how do the specifically support the needs of underrepresented groups? What are the most promising directions for future development and evaluation o employability skills in workforce programming practice, research, and policy? Three qualitative research methods will be used to answer the research questions. This overall approach replicates the approach one taken in a previous investigation into general programs for supporting chronically unemployed and underemployed individuals and underrepresented minority adult students in post-secondary education and entry-level employment. The narrative research synthesis is informed by the conceptualization of research syntheses proposed by Cooper (1998, 2006) and Campbell and associates (1992). The Interviews with expert informants in workforce development, technician education, and the industry selected industry sectors will deepen an understanding of employability skills. The systematic examination and iterative refinement of the synthesis of the research and expert knowledge will assess data saturation (e.g., knowing how many interviews are needed to provide sufficient codes and themes for replicable findings) and ensure support the development of stable data categories.