Engaging Underrepresented High School students in Data Driven Storytelling: An Examination of Learning Experiences and Outcomes for a Cohort of Rising Seniors Enrolled in the Gaining Early Awareness and Readiness for Undergraduate Program (GEAR UP)
Engaging Underrepresented High School students in Data Driven Storytelling: An Examination of Learning Experiences and Outcomes for a Cohort of Rising Seniors Enrolled in the Gaining Early Awareness and Readiness for Undergraduate Program (GEAR UP)
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让代表性不足的高中生参与数据驱动的讲故事：对参加本科项目早期意识和准备 (GEAR UP) 的一群即将崛起的高年级学生的学习经历和成果进行检查
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
E. Donate
中科院分区：
文献类型：
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作者：
L. Dierker;Nadia L. Ward;Jalen Alexander;E. Donate
背景资料：以数据为导向的职业的上升趋势有可能进一步增加女性和少数民族群体在数据分析和应用统计项目中的代表性不足。为了开始为面向数据的职业发展必要的技能，基于项目的学习似乎是最有前途的，因为它专注于旨在吸引学生兴趣和热情的现实世界的活动。方法：使用前和后的调查数据，本研究探讨了学生的背景特征，学习经验和课程成果的一个队列的33个上升的高中高年级学生参与了为期两周的，加速版本的基于项目的数据分析和应用统计课程。结果如下：平均而言，学生们认为这次经历是有益的，绝大多数（78.1%）认为他们取得的成就超过了他们的预期。根据对课程前和课程后调查的回应，大约一半的学生报告对应用技能的信心有所增加（即开发研究问题，管理数据，选择正确的统计测试，有效地展示研究结果，以及对数据进行统计分析），而超过80%的学生报告对编写代码以运行统计分析的信心有所增加。84.4%的学生表示对一个或多个后续课程感兴趣，其中对计算机编程的兴趣最多（53.1%）。结论：这些研究结果支持以前的研究表明，现实世界中，基于项目的经验提供了实现有意义的参与研究，解决问题和专业发展所需的分析和统计素养的最佳希望。
Background : Upward trends in data-oriented careers threaten to further increase the underrepresentation of both females and individuals from racial minority groups in programs focused on data analysis and applied statistics. To begin to develop the necessary skills for a data-oriented career, project-based learning seems the most promising given its focus on real-world activities that are aimed at engaging student interest and enthusiasm. Method : Using pre and post survey data, the present study examines student background characteristics, learning experiences and course outcomes for a cohort of 33 rising high school seniors involved in a two-week, accelerated version of a project-based data analysis and applied statistics curriculum. Results : On average, students rated the experience as rewarding and the vast majority (78.1%) felt that they had accomplished more than they had expected. Based on responses to both the pre and post course surveys, roughly half of the students reported increases in confidence in applied skills (i.e. developing a research question, managing data, choosing the correct statistical test, effectively presenting research results, and conducting a statistical analysis of data), while more than 80% reported increased confidence in writing code to run statistical analyses. Fully 84.4% of students reported interest in one or more follow-up courses with interest in computer programming being endorsed by the largest number of students (53.1%). Conclusions : These findings support previous research showing that real-world, project-based experiences afford the best hope for achieving the kind of analytic and statistical literacy necessary for meaningful engagement in research, problem solving and professional development.