Data_Sheet_1_Evaluation of students’ digital literacy through an immersive university-high school collaboration.docx

IntroductionRecent efforts including the U.S. Department of Education’s Raise the Bar: STEM Excellence for All Students, designed to strengthen Science, Technology, Engineering and Mathematics (STEM) education, typify the development of effective outreach programs implemented in high school settings to increase STEM achievement and literacy and to promote future careers in STEM. Specifically, artificial intelligence (AI) and machine learning (ML) are topics of great importance and interest but are often reserved for higher-level education. Introductions of complex subjects in high school promotes student efficacy, enthusiasm, and skill-development for STEM careers. Establishing strong partnerships between universities and high schools is mutually beneficial for the professional development of students, teachers, and professors. In this paper, we detail immersive outreach efforts and their effectiveness in a high school setting.
MethodsFrom Spring 2021 to Spring 2024, we conducted eight data-science and analysis-coding style workshops along with two data science units, with 302 students participating in the data science workshops and 82 students in the data science units. All students who participated in the data science lessons completed a comprehensive final project. Surveys measuring knowledge and appeal to data science and coding were conducted both retrospectively and prospectively, before and after each workshop and the data science units. A 1 year follow up survey was conducted for students in the 2023 data science lessons (n = 23).
ResultsOverall, average student interest significantly increased from 2.72 ± 1.08/5.0 (n = 205) to 3.15 ± 1.18/5.0 (n = 181, p = 0.001) during the data science workshops, while 70% of students expressed desire to continue with coding. Interest modestly increased in the data science lessons from 3.15 ± 0.65/4.0 to 3.17 ± 0.77/4.0 (n = 82, p = 0.8571), while knowledge significantly increased from 64.16% to 88.5% (% correct out of six questions) in the 2023 data science lessons and from 52.62% to 60.79% (% correct out of 29 questions) in the 2024 data science lessons.
DiscussionIncreasing STEM exposure through outreach programs and a modified curriculum can positively alter students’ career trajectory and prepare them for the evolving technologically advanced world and the careers within it.

引言
近期包括美国教育部《Raise the Bar: STEM Excellence for All Students》在内的多项举措，旨在强化科学（Science）、技术（Technology）、工程（Engineering）与数学（Mathematics，简称STEM）教育，这类举措典型代表了当前针对高中阶段开发的有效外展推广项目——此类项目旨在提升学生的STEM学业成就与科学素养，并推动其未来投身STEM领域职业。具体而言，人工智能（AI）与机器学习（ML）作为极具影响力与关注度的主题，却常被限定在高等教育阶段开展。在高中阶段引入复杂学科内容，有助于提升学生的STEM职业效能感、学习热情与相关技能储备。构建高校与高中的深度合作伙伴关系，对学生、教师与教授的职业发展均具有双向增益价值。本文详细阐述了高中阶段开展的沉浸式外展推广项目及其实施效果。

研究方法
2021年春季至2024年春季期间，本团队共开展8次数据科学与分析编码类工作坊，以及2个数据科学单元课程，累计有302名学生参与数据科学工作坊，82名学生参与数据科学单元课程。所有参与数据科学课程的学生均需完成一项综合性结项作业。针对数据科学与编码的知识掌握程度及学习兴趣的调研，分别在各工作坊与单元课程开展前后进行了回顾性与前瞻性问卷调研。针对2023年数据科学课程的学生（n=23），我们额外开展了为期1年的追踪调研。

研究结果
整体而言，参与数据科学工作坊的学生平均学习兴趣从2.72 ± 1.08/5.0（n=205）显著提升至3.15 ± 1.18/5.0（n=181，p=0.001），且70%的学生表示希望继续学习编码。在数据科学单元课程中，学生兴趣仅出现小幅提升，从3.15 ± 0.65/4.0升至3.17 ± 0.77/4.0（n=82，p=0.8571）；而知识掌握程度则显著提升：2023年数据科学课程中，学生在6道测试题中的正确率从64.16%升至88.5%；2024年数据科学课程中，学生在29道测试题中的正确率从52.62%升至60.79%。

讨论
通过外展推广项目与优化后的课程提升学生的STEM接触机会，能够正向引导学生的职业发展路径，帮助他们适应不断发展的科技化世界及其中的相关职业。