CPATH-1: An interdisciplinary, problem-based, collaborative course on computational thinking

该项目正在为贝勒大学的非计算机科学本科生开发和提供一门计算思维课程。在这门课程中，计算思维是从算法的角度来看的，因此它帮助学生培养有效解决算法问题所需的技能。它包括问题抽象和分解，基本编程概念，以及计算的实践和理论限制等主题。首先，它面向所有学生，而不仅仅是那些与科学相关的学科的学生。第二，它是协作的。学生们以小组形式工作，每周更换一次。第三，它是基于问题的。学生通过解决实际问题来学习计算思维。最后，本课程中给出的问题来自计算机科学以外的学科。来自全校的教职员工正在帮助开发一套在课堂上使用的问题。因为这门课程关注的是如何在其他学科中使用计算思维，所以它将比现有的计算机科学专业入门课程更好地培训非计算机专业的学生。该项目的第一年专注于课程开发，包括定义问题类型的规范列表，为课程收集问题，以及为学生选择合适的软件实施。该课程将在项目的第二年开设两次，每学期一次。考虑到传统的计算机科学入门课程的招生人数，对这门课程的需求很高。智力价值这门非专业的入门课程为非计算机科学家提供了广泛的计算思维入门知识。每个主要研究人员都有多年使用基于问题的协作学习向所有级别的计算机科学专业教授计算思维的经验。以问题为基础的课程，使用外部学科的问题，用来激发计算主题。这门课程还教育学生了解计算的广度？S的应用，并向他们介绍其他领域。这门课程有可能成为算法计算思维入门的典范，从而具有变革的潜力。它将来自多个学科的学生和问题聚集在一起，并将他们团结在一个共同的主题下。该课程在训练学生计算思维方面的效果将得到严格评估，并与传统的计算机科学入门课程进行比较。广泛影响如果技术要继续对社会产生积极影响，与技术互动的人必须了解如何有效地使用和创造技术。为此，拟议的课程通过为学科外的学生提供服务，扩大了对计算机的参与，并通过在课程发展中纳入外部教师，扩大了教员的参与。该课程通过提供课程、软件工具和一系列可公开使用的问题来增强教育基础设施。PI对这门课程有广泛的支持，无论是在计算机科学系内部，还是在贝勒的许多其他系的教职员工中。

This project is developing and offering a course in computational thinking for non-computer science undergraduate students at Baylor University. In this course, computational thinking is viewed algorithmically, thus it helps students to develop the skills needed to effectively solve problems with algorithms. It includes such topics as problem abstraction and decomposition, fundamental programming concepts, and the practical and theoretical limits of computation.There are several distinctive aspects to this course. First, it is intended for all students rather than only those in science-related disciplines. Second, it is collaborative. Students work in small groups that change weekly. Third, it is problem-based. Students learn computational thinking by solving real problems. Finally, problems given in the course come from disciplines outside of computer science. Faculty members from across the university are helping to develop the set of problems to be used in the class. Because the course focuses on how computational thinking may be used in other disciplines, it will better train non-computer science majors than the existing introductory course for computer science majors.The first year of the project is focused upon curriculum development, including defining a canonical list of problem types, gathering problems for the course, and selecting appropriate software for student implementation. The course will be offered twice in the second year of the project, once each semester. Given the enrollment in traditional introduction to computer science courses, demand for the course is high.Intellectual MeritThis introductory course for non-majors gives a broad introduction to computational thinking for non-computer scientists. The principal investigators each have years of experience using problem-based, collaborative learning to teach computational thinking to computer science majors at all levels. A problem-based curriculum, using problems from external disciplines, serves to motivate the computational topics. The course also educates students about the breadth of computation?s application, and introduces them to other fields.This course has the potential to be transformative by becoming a model for the introduction to algorithmic computational thinking. It brings together students and problems from multiple disciplines, and unites them under a common theme. The efficacy of the course in training students in computational thinking will be rigorously evaluated and compared with a traditional introductory computer science course.Broader ImpactsIf technology is to continue to have a positive impact on society, it is essential for the people who interact with technology to understand how to effectively use and create with it. To this end, the proposed course broadens participation in computing by serving students outside the discipline.It also broadens the participation of faculty members by including external faculty in course development. The course enhances education infrastructure by providing a curriculum, software tools, and a body of problems to be made publicly available. The PIs have broad support for this course, both from inside the computer science department and across the faculty in many other departments at Baylor.