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Excellence in Mathematics in Secondary School and Choosing and Excelling in STEM Professions over Significant Periods in Life
International Journal of Science and Mathematics Education ( IF 2.051 ) Pub Date : 2021-01-12 , DOI: 10.1007/s10763-020-10138-x
Zehavit Kohen , Ortal Nitzan

Excellent Science, Technology, Engineering, and Mathematics (STEM) employees are in constant demand worldwide. The current study explores Israeli students’ choices to study and pursue careers in STEM fields, while students’ level of excellence in mathematics in secondary school is explored as a predictor for choosing a STEM track in future study and employment, as well as a predictor for the level of success in completing a STEM degree. The theoretical framework for the study is based on the task performance model of the social cognitive career theory which focuses on human behavior in the context of career choice. The study presents a big data analysis based on about 650,000 records retrieved from the Central Bureau of Statistics in Israel for several points in time over the last one and a half decades, to demonstrate choice patterns over the years. We analyzed a representative sample using systematic sampling over the last decade and a half, from secondary school, higher education, and postgraduate STEM-related populations who are employed in STEM professions. Our study presents a scale for mathematics excellence, which reflects a combination of study level and level of success. Our findings reveal that choosing a more advanced level of mathematics in secondary school, as opposed to the level of success in these studies, is the best predictor for choosing STEM as a major in secondary school, completing a STEM bachelor’s degree, succeeding in a STEM bachelor’s degree, and making a STEM career choice.



中文翻译:

生命中重要时期的中学数学卓越以及STEM专业的选择和卓越

全球范围内不断有优秀的科学,技术,工程和数学(STEM)员工。当前的研究探讨了以色列学生在STEM领域学习和从事职业的选择,而在中学阶段学生的数学卓越水平则被用作选择未来学习和就业的STEM路径的预测因素,以及完成STEM学位的成功水平。该研究的理论框架基于社会认知职业理论的任务绩效模型,该模型关注职业选择背景下的人类行为。这项研究基于过去65年中从以色列中央统计局检索到的大约650,000条记录,对这些数据进行了大数据分析,这些记录在过去的15年中有多个时间点,展示多年来的选择模式。在过去的十五年中,我们使用系统抽样来分析了代表性的样本,这些样本来自中学,高等教育和从事STEM专业的与STEM相关的研究生。我们的研究提出了一个卓越的数学量表,它反映了学习水平和成功水平的结合。我们的发现表明,与在这些研究中的成功水平相反,在中学阶段选择更高水平的数学,是选择STEM作为中学专业,完成STEM学士学位,成功获得STEM的最佳预测指标学士学位,并做出STEM职业选择。以及从事STEM专业的研究生STEM相关人群。我们的研究提出了一个卓越的数学量表,它反映了学习水平和成功水平的结合。我们的发现表明,与在这些研究中的成功水平相反,在中学阶段选择更高水平的数学,是选择STEM作为中学专业,完成STEM学士学位,成功获得STEM的最佳预测指标学士学位,并选择STEM职业。以及从事STEM专业的研究生STEM相关人群。我们的研究提出了一个卓越的数学量表,它反映了学习水平和成功水平的结合。我们的发现表明,与在这些研究中的成功水平相反,在中学阶段选择更高水平的数学,是选择STEM作为中学专业,完成STEM学士学位,成功获得STEM的最佳预测指标学士学位,并选择STEM职业。

更新日期:2021-01-12
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