Using practical programming tasks to enhance combinatorial understanding

Author:

Levy Sigal1ORCID,Stukalin Yelena1ORCID,Guttmann‐Beck Nili12ORCID

Affiliation:

1. Statistics education unit Academic College of Tel Aviv Yaffo Tel Aviv Israel

2. School of Computer science & Statistics education unit Academic College of Tel‐Aviv Yaffo Tel Aviv Israel

Abstract

AbstractProbability 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.

Publisher

Wiley

Reference11 articles.

1. Research and Developments in Probability Education

2. TEACHING PROBABILITY WITH THE SUPPORT OF THE R STATISTICAL SOFTWARE

3. Guidelines for Assessment and Instruction in Statistics Education (GAISE) Reports.2016https://www.amstat.org/education/guidelines‐for‐assessment‐and‐instruction‐in‐statistics‐education‐(gaise)‐reports

4. Using Online Game-Based Simulations to Strengthen Students’ Understanding of Practical Statistical Issues in Real-World Data Analysis

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