Using Practical Programming Tasks to Enhance Combinatorial Understanding
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| Title: | Using Practical Programming Tasks to Enhance Combinatorial Understanding |
|---|---|
| Language: | English |
| Authors: | Sigal Levy (ORCID |
| Source: | Teaching Statistics: An International Journal for Teachers. 2024 46(2):113-120. |
| Availability: | Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us |
| Peer Reviewed: | Y |
| Page Count: | 8 |
| Publication Date: | 2024 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Programming, Probability, Mathematics Skills, Computer Science Education, Concept Formation, College Freshmen, Postsecondary Education, Problem Solving, Difficulty Level |
| DOI: | 10.1111/test.12369 |
| ISSN: | 0141-982X 1467-9639 |
| Abstract: | 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. |
| Abstractor: | As Provided |
| Entry Date: | 2024 |
| Accession Number: | EJ1420856 |
| Database: | ERIC |
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| Abstract: | 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. |
|---|---|
| ISSN: | 0141-982X 1467-9639 |
| DOI: | 10.1111/test.12369 |
