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

CER：影响大学信息技术成功的因素 (FICSIT)

基本信息

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

项目摘要

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来分析大学生？当学生在大学学习计算机科学时，教育背景和以前与IT相关的经验，同时控制人口差异。这项研究将揭示有关高中教师在科学和数学教学中的使用以及越来越多的高中计算机科学课程与全国12,000名大学计算机科学专业学生的表现有关的决策，他们将从随机选择的2年和4年学院招募。这项研究具有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课程，竞赛，比赛和俱乐部，并评估与介绍性学院计算机科学课程不断发展的景观期间经验之间的匹配影响。这种知识只能帮助改善过早地追求潜在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而言，他们历来比其他同学更早地选择了这一领域。大学和高中计算机科学讲师都可以从了解为学生有效准备的因素中受益吗？第一学院计算机科学课程。