Collaborative Research: PRIME: Engaging STEM Undergraduate Students in Computer Science with Intelligent Tutoring Systems

“用智能辅导系统吸引STEM本科生学习计算机科学”项目将设计、开发和评估个性化实时智能辅导环境（PRIME）系统，该系统将提供自适应解决问题的支持和自适应激励支持，帮助学生学习解决计算问题。PRIME将跟踪每个学生的进度，同时在学生的学习互动过程中提供实时反馈、多级提示和定制的解决问题的建议。该项目将使用块编程语言“Snap!”，因为它消除了大多数语法错误，使学生能够专注于概念和逻辑。入门计算是许多STEM本科课程的必修部分，由于计算对所有STEM学科的基本重要性，向STEM本科生介绍计算的课程具有巨大的潜力，可以塑造学生发展计算流畅性的方式，这将在他们的整个职业生涯中为他们服务。PRIME智能辅导系统将在北卡罗莱纳州立大学的大型计算机入门课程中进行评估，该课程每年为2000多名学生提供服务。佛罗里达大学和佛罗里达农工大学（Florida a&m University）也将对PRIME环境进行评估，这是一所历史悠久的黑人大学。PRIME的实验研究将有双重重点：调查它对帮助学生学习计算（分析问题，创建模型和抽象，构建和完善程序）的影响，以及改善学生对计算的态度（计算的自我效能感和对计算的兴趣）。

The "Engaging STEM Undergraduate Students in Computer Science with Intelligent Tutoring Systems" project will see the design, development, and evaluation of the Personalized Real-time Intelligent Mentoring Environment (PRIME) system, which will provide adaptive problem-solving support and adaptive motivational support to help students learn to solve computing problems. PRIME will track each student's progress while providing real-time feedback, multiple levels of hints, and customized problem-solving advice throughout students' learning interactions. The project will use the block programming language "Snap!" as it eliminates most syntax errors, freeing students to focus on concepts and logic.Introductory computing is a required component of many STEM undergraduate curricula, and because of the fundamental importance of computing for all STEM disciplines, courses that introduce computing to STEM undergraduates hold enormous potential for shaping the way students develop computational fluency that will serve them throughout their careers. The PRIME intelligent tutoring system will be evaluated in a large introductory computing course at North Carolina State University, which serves more than 2,000 students each year. The PRIME environment will also be evaluated at the University of Florida and at Florida A&M University, a Historically Black University. Experimental studies with PRIME will have a dual focus: investigating its impacts on helping students learn about computing (analyzing problems, creating models and abstractions, and building and refining programs) and improving students' attitudes towards computing (self-efficacy for computing and interest in computing).