利用实际编程任务加深对组合的理解

IF 1.2 Q2 EDUCATION & EDUCATIONAL RESEARCH Teaching Statistics Pub Date : 2024-04-12 DOI:10.1111/test.12369
Sigal Levy, Yelena Stukalin, Nili Guttmann-Beck
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引用次数: 0

摘要

概率论在统计、计算机科学和金融等各个领域都有广泛的应用。在概率论教育中,学生将学习基本原理,其中可能包括组合学和对称样本空间等数学主题。攻读计算机科学学位的学生在编程、软件工程和算法思维方面拥有坚实的基础。尽管这些学生带着独特的视角和学习潜力进入概率课程,但在掌握组合概念方面却遇到了挑战。在本实验中,我们让计算机科学专业的一年级学生对一个实际的组合问题进行模拟编程。学生们就这一任务是否以及如何帮助他们内化组合学的基本概念发表了意见。我们旨在展示如何利用编程任务让学生更深入地掌握组合学。
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Using practical programming tasks to enhance combinatorial understanding
Probability theory has extensive applications across various domains, such as statistics, computer science, and finance. In probability education, students are introduced to fundamental principles which may include mathematical topics such as combinatorics and symmetric sample spaces. Students pursuing degrees in computer science possess a robust foundation in programming, software engineering, and algorithmic thinking. Despite entering probability courses with a unique perspective and learning potential, these students encounter challenges in grasping combinatorial concepts. In this experiment, we challenged first-year postsecondary computer science students to program a simulation of a practical combinatorics problem. Students commented on whether and how this task helped them internalize the basic concepts of combinatorics. We aim to show how utilizing programming tasks may empower students with a deeper grasp of combinatorics.
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来源期刊
Teaching Statistics
Teaching Statistics EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
2.10
自引率
25.00%
发文量
31
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