Table of Links Abstract and I. Introduction Abstract and I. Introduction I. Introduction II. Background and Related Work II. Background and Related Work A. Learning to Program: SCRATCH and Pair Programming A. Learning to Program: SCRATCH and Pair Programming B. Gender in Programming Education and Pair Programming B. Gender in Programming Education and Pair Programming III. Course Design III. Course Design A. Introducing Young Learners to Pair Programming A. Introducing Young Learners to Pair Programming B. Implementation of Pair Programming B. Implementation of Pair Programming C. Course Schedule C. Course Schedule IV. Method IV. Method A. Pre-Study and B. Data Collection A. Pre-Study and B. Data Collection C. Dataset and D. Data Analysis C. Dataset and D. Data Analysis E. Threats to Validity E. Threats to Validity V. Results V. Results A. RQ1: Attitude A. RQ1: Attitude B. RQ2: Behavior B. RQ2: Behavior C. RQ3: Code C. RQ3: Code VI. Conclusions and Future Work, Acknowledgments, and References VI. Conclusions and Future Work, Acknowledgments, and References VI. Conclusions and Future Work, Acknowledgments, and References IV. METHOD Using the PP-based SCRATCH course (Section III), we aim to empirically answer the following research questions: • RQ1: Does the pair constellation in PP relate to the students’ attitude towards programming? RQ1 Does the pair constellation in PP relate to the students’ attitude towards programming? • RQ2: Does the pair constellation in PP relate to the students’ behavior while programming? RQ2 Does the pair constellation in PP relate to the students’ behavior while programming? • RQ3: Does the pair constellation in PP relate to the students’ programs? RQ3 Does the pair constellation in PP relate to the students’ programs? A. Pre-Study To evaluate the course design, we conducted a pre-study with 15 students distributed in six pairs and one group of three. The main objective of the pre-study was to evaluate the difficulty of the tasks and the time allocation, so that the final course could be easily completed in a double period class. The responses and projects of the pre-study are not included in the analysis of RQ1–RQ3. We included eight tasks in the pre-study, which basically had the same content as in our main study. The first two tasks (basics and loops) and the last two tasks (free tasks) are the same in both. However, the other tasks were reduced in complexity and combined because of time restrictions: bouncing the ball off the wall was an extra task with conditions, which was then solved with the predefined block of SCRATCH and integrated into the second task (Section III-C2). The task to make the angle of incidence more exciting was an extra task before the free tasks, which also included a more complex formula of operators. The formula was reduced to a minimum of complexity and integrated into the fourth task (Section III-C4). B. Data Collection We conducted the final course nine times between April and July 2022, targeting children aged 8 to 14 without prior programming experience. An invitation for the course was sent to the schools in the local neighborhood of the University of Passau (Germany) by email. The course lasts about 1.5 hours, hus, it is feasible to conduct it within a typical double period class. The pairs grouped themselves either based on the seating in the class or their own preference [26]. Each pair was given a pair name by the researchers with which they used to login at a custom instance of SCRATCH hosted at the University of Passau, which tracks the interactions with the code editor as well as the final program. At the beginning of the course the students had to individually fill in a survey with their pair name, age, sex, previous knowledge in programming, if they know their pair partner, and if they think programming is cool. During the course, each student had to fill in the Fun Toolkit [49] after each task (Table I), asking if they would do the task again (AG), how they liked it (FU), what their role was, and how they liked their role (LR). At the end of the course, the students were given stickers of different colors to mark the tasks they liked best and worst, and the ones they found easiest and most difficult. At the end, they were asked to answer the question of whether they think programming is cool again. To ensure that the course ran smoothly, researchers filled different roles. One researcher was exclusively responsible for explaining the tasks and guiding through the course, while four to six supervisors observed the pairs and assisted with questions. One supervisor was usually responsible for two pairs. During the course, the supervisors observed the behavior of each pair assigned to them on the evaluation sheet after each task. In total, they kept track of six different categories: compliance with roles, collaboration, communication, harmony, dispute and need for help (Table I). In order to reduce gender biases in our setting, the role of the instructor and the supervisor were gender-balanced through all courses. Authors:
(1) Isabella Graßl, University of Passau, Passau, Germany (isabella.grassl@uni-passau.de);
(2) Gordon Fraser, University of Passau, Passau, Germany (gordon.fraser@uni-passau.de). Authors: Authors: (1) Isabella Graßl, University of Passau, Passau, Germany (isabella.grassl@uni-passau.de); (2) Gordon Fraser, University of Passau, Passau, Germany (gordon.fraser@uni-passau.de). This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. available on arxiv available on arxiv

Part of HackerNoon's growing list of open-source research papers, promoting free access to academic material.

Precision Data Collection: Probing Gender Dynamics in SCRATCH Pair Programming

About Author

Comments

TOPICS

THIS ARTICLE WAS FEATURED IN

Related Stories

11 Proven Solutions to Common GitHub Copilot Problems

Transforming Programming Education: Gender-Sensitive Pair Programming Insights

Igniting Young Minds: SCRATCH & Pair Programming for Early CS Success

Sparking Coding Enthusiasm: Introducing Pair Programming to Young Learners in SCRATCH

Cultivating Coding Success: A Supervised Approach to Pair Programming for Youth

Mastering Play: Our SCRATCH Course Blueprint for Learning Pong & Coding Concepts

11 Proven Solutions to Common GitHub Copilot Problems

Transforming Programming Education: Gender-Sensitive Pair Programming Insights

Igniting Young Minds: SCRATCH & Pair Programming for Early CS Success

Sparking Coding Enthusiasm: Introducing Pair Programming to Young Learners in SCRATCH

Cultivating Coding Success: A Supervised Approach to Pair Programming for Youth

Mastering Play: Our SCRATCH Course Blueprint for Learning Pong & Coding Concepts

Light-Mode

Classic

Newspaper

Minty

Dark-Mode

Neon Noir

Minty

HN StartUps