CER: Factors Influencing College Success in Information Technology (FICSIT)

CER：影响大学信息技术成功的因素 (FICSIT)

• 批准号: 1339200
• 负责人: Philip Sadler
• 金额: $ 60万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1339200&HistoricalAwards=false
• 关键词: CER; Factors; Influencing; College; Success

Harvard University will undertake a retrospective cohort study to analyze college students? education background and previous IT-related experiences for predictors of performance when students study Computer Science in college, while controlling for demographic differences. The study will reveal how decisions concerning the use of technology made by high school teachers in the teaching of science and mathematics and the growing number of high school computer science courses relate to the performance of 12,000 college computer science students nationwide, who will be recruited from randomly selected 2-year and 4-year colleges and universities. This study has the capacity to both reveal and evaluate the use of the most promising educational practices and interventions, including both in-school computing instruction and after-school programs, competitions, and clubs, and to assess the effects of a match between experiences during the high school years with the evolving landscape of introductory college computer science courses. Such knowledge can only help to ameliorate the high failure rates that prematurely end the pursuit of a potential computer science degree, especially for females and under-represented minorities who historically opt out of this field earlier and in greater numbers than other classmates. Both college and high school computer science instructors can also benefit from understanding the factors contributing to effective preparation for students? first college computer science course.

哈佛大学将进行一项回顾性队列研究，分析大学生？教育背景和以前的IT相关经验的预测性能时，学生在大学学习计算机科学，同时控制人口统计学差异。 该研究将揭示高中教师在科学和数学教学中使用技术的决定以及越来越多的高中计算机科学课程与全国12，000名大学计算机科学学生的表现之间的关系，这些学生将从随机选择的2年制和4年制学院和大学中招募。 这项研究有能力揭示和评估最有前途的教育实践和干预措施的使用，包括校内计算教学和课后计划，比赛和俱乐部，并评估高中期间经验之间的匹配的影响随着大学计算机科学入门课程的不断发展。 这些知识只会有助于改善过早结束追求潜在的计算机科学学位的高失败率，特别是对于女性和代表性不足的少数民族来说，他们历史上选择退出这个领域的时间比其他同学更早，人数更多。大学和高中的计算机科学教师也可以从了解有助于学生有效准备的因素中受益。大学计算机科学第一课