A Gender-Related Analysis of a Robots' Math Class

Abstract

Using robot programming activities for learning in the classroom is one way to drive interest and engagement in the STEM field among students, especially girls. And this is a field that is particularly characterized by an underrepresentation of women. Accordingly, many countries are increasingly integrating activities related to computer science concepts into their education systems. The EU also sets the goal of considering the connections between STEM disciplines in schools and having students gain experience with robots as well. The use of robots for teaching purposes creates opportunities for motivating and meaningful mathematics lessons that are linked to the fundamental concepts of computer science. Mathematics teaching in such a context offers possibilities for an experimental and problem-oriented approach to the content and a deep insight into mathematical concepts. Research in this area shows that the use of robots can promote understanding of mathematical concepts, change attitudes and motivation, and develop metacognitive and problem-solving skills. However, as for gender differences in this context, little is known to date. Addressing this gap, for this work, we investigated learners' performance, mathematical and computational ideas and experiences, problem-solving strategies, and help used in an ER (Educational Robotics) activity. In addition, the learners’ mathematical competence and computational thinking skills as well as possible correlations of these measures with the learners’ performance on an ER activity were examined. For these purposes, an ER activity on the topic of plane geometric figures was designed, which was carried out in a 6th grade (11-12 years) class (n=24) of an Austrian middle school in the city of Salzburg using the TI-Innovator Rover. The comparison of six female and six male student groups, each consisting of two students, made it possible to address the above research questions. For this purpose, a mixed-methods approach was chosen. Qualitative data, consisting of the audio recordings of the student groups' conversations during the ER activity, the constructions made on the posters, the student notes, and the saved programs, form the basis for thematic analysis. The quantitative data include the number of tasks solved during the ER activity by the student groups, the mathematics grade of the last school year by the students, and the results of a test on the students' computational thinking skills with the related self-assessments. Appropriate quantitative methods for analysis include the Wilcoxon rank-sum test (Mann-Whitney test), the Welch Two Sample t-test, and Kendall's tau and Pearson's correlation coefficient to test for differences and correlations. The main results indicate that groups with female students perform better while showing high engagement in the activity, exhibit a more systematic approach to problem-solving and at the same time use less intensive help from the teachers than their male counterparts in this class. The paper concludes by giving future directions for research and the limits of the present work.