Collaborative Research: CSEdPad: Investigating and Scaffolding Students' Mental Models during Computer Programming Tasks to Improve Learning, Engagement, and Retention

计算技能，如计算机编程，是许多学科的组成部分，包括科学、技术、工程和数学(STEM)领域。尽管这类技能的需求量很大，有抱负的计算机科学(CS)学生的数量也令人鼓舞，但CS毕业生的供应和需求之间的巨大差距仍然存在，例如，大学CS课程在入门CS课程中存在较高的流失率。计算机科学入门课程流失率高的一个原因是计算机科学概念和任务的内在复杂性。为了帮助学生更好地应对高水平的复杂性，该项目研究了一种名为CSEdPad(CS Education Pad)的新型教育技术，旨在帮助学生在早期接触CS概念和任务时简化编程入门。此外，该项目通过一个研究项目在CS教育中开拓了新的领域，促进了我们对学生源代码理解、学习和动机过程的理解。CSEdPad项目有可能改变学生对计算机科学的看法，提高他们的编程技能和自我效能，并导致更高的保留率。CSEdPad系统设计将运用成熟的教育技术和技巧，在CS教育中改善学生的心理模型构建、学习、参与和保持。特别是，该系统的目标是理解源代码，这对学习者和专业人士来说都是一项关键技能。当学生参与各种代码理解任务时，它监控和搭建源代码理解过程。正在探索的主要方法包括动画教学代理、自我解释和开放式社会学习者模式。结果变量包括理解测量、学习收获、参与度、保持和自我效能。由于其跨学科性质，该项目将影响多个领域，包括计算机科学教育、认知心理学、智能辅导系统和人工智能。参与实验的学生将从不同的学生群体中挑选出来，涉及性别、种族和社会经济地位。增加招收和留住这些群体的学生将产生深远的影响。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Computing skills, such as computer programming, are an integral part of many disciplines, including the fields of science, technology, engineering, and math (STEM). Although such skills are in high-demand, and the number of aspiring Computer Science (CS) students is encouraging, a large gap between the supply of CS graduates and the demand persists because, for instance, college CS programs suffer from high attrition rates in introductory CS courses. One reason for the high attrition rates in introductory CS courses is the inherent complexity of CS concepts and tasks. To help students better cope with the high level of complexity, this project investigates a novel education technology, called CSEdPad (CS Education Pad), meant to ease students' introduction to programming during their early encounters with CS concepts and tasks. Moreover, the project forges new frontiers in CS education through a research program that advances our understanding of students' source code comprehension, learning, and motivational processes. The CSEdPad project has the potential to transform how students perceive computer science, increase their programming skills and self-efficacy, and lead to increased retention rates. The result will be a win-win-win situation for aspiring students, CS programs and their organizations, and the overall economy.The CSEdPad system design brings to bear proven educational technologies and techniques to improve students' mental model construction, learning, engagement, and retention in CS education. In particular, the system targets source code comprehension, a critical skill for both learners and professionals. It monitors and scaffolds source code comprehension processes while students engage in a variety of code comprehension tasks. Key approaches being explored include Animated Pedagogical Agents, self-explanation, and the Open Social Learner Model. Outcome variables include comprehension measures, learning gains, engagement level, retention, and self-efficacy. Due to its interdisciplinary nature, the project will impact several fields including Computer Science education, cognitive psychology, intelligent tutoring systems, and artificial intelligence. Students participating in the experiments will be selected from a diverse student body with respect to gender, ethnicity, and socioeconomic status. An increase in recruitment and retention of students from these populations will have far-reaching implications.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.