No abstract

Computational thinking describes key principles from computer science that are broadly generalizable. Robotics programs can be engaging learning environments for acquiring core computational thinking competencies. However, few empirical studies evaluate the effectiveness of a robotics programming curriculum for developing computational thinking knowledge and skills. This study measures pre/post gains with new computational thinking assessments given to middle school students who participated in a virtual robotics programming curriculum. Overall, participation in the virtual robotics curriculum was related to significant gains in pre- to posttest scores, with larger gains for students who made further progress through the curriculum. The success of this intervention suggests that participation in a scaffolded programming curriculum, within the context of virtual robotics, supports the development of generalizable computational thinking knowledge and skills that are associated with increased problem-solving performance on nonrobotics computing tasks. Furthermore, the particular units that students engage in may determine their level of growth in these competencies.

Background Working effectively in teams is an important 21st century skill as well as a fundamental component of the ABET professional competencies. However, successful teamwork is challenging, and empirical studies with adolescents concerning how the collaboration quality of team members is related to team performance are limited. Purpose/Hypothesis This study investigated the relationship between team collaboration quality and team performance in a robotics competition using multiple measures of team performance, including both objective task performance and expert judge evaluations, on a diverse set of supporting performance dimensions. Design/Method Data included Table Score, Robot Design, Research Project, Core Values, and Collaboration Quality scores for 366 youths on 61 K‐8 robotics teams that participated in a FIRST LEGO League Championship. Regression and mediation analyses were conducted to explore the relation between effective team collaboration and team performance. Furthermore, analysis of variance was conducted to explore the relationship between Collaboration Quality and team experience. Results Collaboration Quality was a good predictor of robotics team performance across all measures (with R2 = .50 and p < .001). Mediation analysis revealed that the Robot Design acted as a full mediator for the predictive effect of Collaboration Quality on the Table Score. In addition, the cumulative amount of team experience was significantly related to Collaboration Quality. Conclusions Overall, this study using collaboration performance assessments and actual competition data with a large number of teams confirms the importance of high‐quality teamwork in producing superior products with students engaged in authentic engineering tasks.

Background: Robotics competitions are increasingly popular and potentially provide an on-ramp to computer science, which is currently highly gender imbalanced. However, within competitive robotics teams, student participation in programming is not universal. This study gathered surveys from over 500 elementary, middle, and high school robotics competition participants to examine (1) whether programming involvement in these competitions is associated with motivation to pursue additional programming experiences and (2) whether opportunities to learn programming varied by gender, age, and competition type. Results: Results showed a significant association of students' programming involvement with their motivation to learn more programming. Interestingly, in the youngest groups/entry-level competitions, girls were heavily involved in programming. Unfortunately, in older/more advanced competitions, girls were generally less involved in programming, even after controlling for prior programming experience. These gendered effects were substantially explained by programming interest. Conclusions: While robotics competition experiences may motivate students to learn more programming, gender gaps in programming involvement persist in these learning environments and appear to widen as students grow older and enter more advanced competitions. Therefore, addressing gender imbalances in programming will likely require greater attention to particular curricular and pedagogical characteristics of robotics competitions that support girls' interest and involvement in programming.

Educational robotics programs offer an engaging opportunity to potentially teach core computer science concepts and practices in K-12 classrooms. Here, we test the effects of units with different programming content within a virtual robotics context on both learning gains and motivational changes in middle school (6th-8th grade) robotics classrooms. Significant learning gains were found overall, particularly for groups introduced to content involving program flow, the structural logic of program execution. Relative gains for these groups were particularly high on items that require the transfer of knowledge to dissimilar contexts. Reaching units that included program flow content was also associated with greater maintenance of programming interest when compared with other units.Therefore, our results suggest that explicit instruction in the structural logic of programming may develop deeper transferrable programming knowledge and prevent declines in some motivational factors.