Priming Computer Science Students for Success

随着对计算机科学毕业生的需求飙升，“为计算机科学学生的成功做好准备”通过应用掌握学习和指导来解决计算机科学的大流失率，以解决课程中两个公认的绊脚石：入门计算机科学课程（CS 1）和四门必修数学课程。该项目将提供为期四年的奖学金，以两批八名学生在Ramapo学院学习计算机科学超过五年。参与的学者将有机会参加本科生研究，编程比赛，同行辅导，技术相关的校园俱乐部和校友指导。Ramapo将从当地城市学区招收学生，为低收入家庭学生提供服务，并提供长期的数学科学项目。招聘团队中有两名女教师，她们是培养女学生对计算机科学兴趣的典范。CS 1学者的掌握学习建立在“problets”和“epplets”的成功基础上，这两个软件辅导套件可通过网络使用，便于随时随地学习。事实证明，这些套房提高了妇女的自我效能，使其达到了男子的水平。导师会自动对学生的解决方案进行评分，并提供帮助学生学习的逐步反馈。设计用于课后在线使用，个别学生花尽可能多的时间与练习，直到他们掌握了指定的概念。参加CS 1的学者受益于认知学徒式教学。当使用这种方法时，教师首先模拟与概念相关的问题解决过程，然后使用苏格拉底式提问引导学生在监督下走向正确的解决方案，并逐渐淡化支持，同时要求学生越来越多地依赖自己的知识和经验。在数学课程中遇到学术困扰的S-STEM学者将与数学教师导师配对，后者每周将花一个小时使用认知学徒模式与学生一起解决问题。该项目将产生掌握学习的有效性和认知学徒式的方法在减少计算机科学专业的减员知识。研究结果将在ACM SIGCSE、ITiCSE、CCSCNE和IEEE FIE等国家和地区会议上公布。

As the demand for computer science graduates skyrockets, "Priming Computer Science Students for Success" tackles the large attrition rate in computer science by applying mastery learning and mentoring to target two universally acknowledged stumbling blocks in the curriculum: the introductory computer science course (CS1) and four required mathematics courses. The project will provide four-year scholarships to two cohorts of eight students studying computer science at Ramapo College over five years. Participating scholars will have the opportunity to participate in undergraduate research, programming contests, peer-tutoring, technology-related campus clubs, and alumni mentoring. Ramapo will recruit students from local urban school districts serving low-income students as well as a long-running Upward Bound Math Science program. The recruitment team includes two female faculty, valuable role models for cultivating interest in computer science among female students.Mastery learning for the CS1 scholars builds upon the prior success of "problets" and "epplets," two software tutoring suites available for use over the web that facilitate learning anytime anywhere. These suites have been shown to raise the level of self-efficacy of women to that of men. The tutors automatically grade student solutions and provide step-by-step feedback that helps students learn. Designed to be used online after class, individual students spend as much time as needed with the exercises until they have mastered the assigned concepts. Scholars enrolled in CS1 benefit from cognitive-apprenticeship-style teaching. When using this approach, the instructor first models the problem-solving process related to a concept, then uses Socratic questioning to steer students toward the correct solution under supervision, and gradually fades support while requiring students to rely increasingly on their own knowledge and experience. S-STEM scholars experiencing academic distress in mathematics courses will be paired with a mathematics faculty mentor who will spend an hour each week solving problems with the student using a cognitive-apprenticeship model. The project will generate knowledge on the effectiveness of mastery learning and the cognitive-apprenticeship-style approach in reducing attrition in the computer science major. Results will be presented at national and regional conferences such as ACM SIGCSE, ITiCSE, and CCSCNE, and IEEE FIE.