Gender differences in kindergarteners’ robotics and programming achievement
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Early childhood is a critical period for introducing girls to traditionally masculine fields of science and technology before more extreme gender stereotypes surface in later years. This study looks at the TangibleK Robotics Program in order to determine whether kindergarten boys and girls were equally successful in a series of building and programming tasks. The TangibleK Program consisted of a six lesson robotics and programming curriculum that was implemented in three different kindergarten classrooms (N = 53 students). Although previous research has found that males outperform females in robotics and programming related fields, it was hypothesized that the young age of participants and their limited cultural indoctrination regarding gender stereotypes would allow boys and girls to have equal success in this program. Although boys had a higher mean score than girls on more than half of the tasks, very few of these differences were statistically significant. Boys scored significantly higher than girls only in two areas: properly attaching robotic materials, and programming using Ifs. Overall, both boys and girls were able to successfully complete the program.
KeywordsEarly childhood Gender differences Stereotypes Robotics Computer programming-Powerful ideas STEM fields
This research was funded by the National Science Foundation (NSF Grant DRL-0735657 and NSF Career award IIS-0447166). Any opinions, findings, and conclusions or recommendations expressed in this article are those of the authors and do not necessarily reflect the views of the National Science Foundation. The authors would like to extend many thanks to the wonderful and creative teachers who used our curriculum in their classrooms for this study: Jared Matas, Catherine Tighe, and Mary Beth Morgan; to their principals for embracing a new venture into classroom technology; and to the Tufts graduate and undergraduate students who assisted in the classrooms. We also thank members of the Tufts community for their involvement: former student and now Northwestern University professor Mike Horn, for developing TERN during his PhD work; Jordan Crouser and David Kiger for their work on CHERP; and professors Robert Jacob, from the Human–Computer Interaction Laboratory, and Chris Rogers, from the Center for Engineering Education Outreach.
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