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

“让STEM本科生参与智能辅导系统”项目将展示个性化实时智能辅导环境(Prime)系统的设计、开发和评估，该系统将提供适应性问题解决支持和适应性动机支持，以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中提供实时反馈、多级别提示和定制的问题解决建议。该项目将使用块编程语言“Snap！”入门计算是许多STEM本科课程的必修课，而且由于计算对于所有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，可以塑造学生培养计算流利性的方式，这将在他们的职业生涯中服务于他们。北卡罗来纳州立大学将在每年为2000多名学生提供服务的大型计算机入门课程中对Prime智能教学系统进行评估。优质环境也将在佛罗里达大学和佛罗里达农工大学进行评估，佛罗里达农工大学是一所历史悠久的黑人大学。与Prime的实验研究将有双重重点：调查其在帮助学生学习计算(分析问题、创建模型和抽象以及构建和改进程序)和改善学生对计算的态度(计算自我效能感和计算兴趣)方面的影响。

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).