This study examines the impact of grouping by gender and group roles on robotics performance, computational thinking skills, and learning motivation towards computer programming. One hundred ninety-one students in fourth and fifth grade completed the project. LEGO Mindstorms EV3 robotics were used to compose and program music in groups of three to four students. The robotics project was completed over the course of fourteen weeks for one hour each week. Gender-structured groups of all female, all male and mixed female and male were randomly assigned in each class. All groups in participating six classrooms were assigned one of three group roles implementation, which were fixed, rotating and no role. This study is significant towards identifying group scaffolds and supports that can produce benefits for all students in robotic activities. Results indicated that group roles matter when students are working on collaborative robotics projects. Three different implementations of group roles in robotics activities demonstrated an impact on robotics performance scores. Gender composition of the group did not impact groups’ robotics performance. Group roles also impacted student computational thinking skills, while gender composition of the group still demonstrated no significant difference. Finally, while group roles demonstrated a difference in learning motivation towards computer programming, gender composition demonstrated no difference in learning motivation towards computer programming.
This is an author-produced, peer-reviewed version of this article. © 2019, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial- No Derivatives 4.0 license. The final, definitive version of this document can be found online at Computers in Human Behavior, doi: 10.1016/j.chb.2018.12.010
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Taylor, Kellie and Baek, Youngkyun. (2019). "Group Roles Matter in Computational Robotic Activities". Computers in Human Behavior, 93, 99-105. http://dx.doi.org/10.1016/j.chb.2018.12.010
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