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Math self-concepts, stereotypes, and self-esteem deeply influence kids' interest in science, technology, engineering, and math (STEM) which accounts for their STEM self-esteem. All of these impact student learning and have been shown to predict standardized test achievement, future course enrollment, and a student’s chosen career path.
The Institute for Learning & Brain Sciences (I-LABS) at the University of Washington is uncovering scientific evidence needed to assist parents, educators, and policymakers to develop scalable, cost-effective interventions during our children’s most formative years.
We were fascinated to find that elementary school children have unconscious thoughts about whether or not they are a math person. They're already beginning to develop an implicit identity of ‘math is for me’ or ‘math is not for me’ at an early age."
The STEM self-esteem gender gap starts at and early age
The gender gap in STEM engagement and STEM self-esteem is large and persistent. Cultural stereotypes influence gender disproportions in STEM achievement. These gaps begin early—young girls report less interest and self-confidence in technology compared to boys in elementary school. In brief, I-LABS is finding that children’s views about themselves and who is good at STEM mirror current American cultural stereotypes.
The sources of these stereotypes, however, and their influence early in the STEM pipeline have not yet been sufficiently studied. Dr. Dario Cvencek, research scientist at I-LABS, is currently leading studies focused on the idea that the elementary school period is a critical time that begins to shape children’s interests, motivation, and skills in STEM. Dr. Cvencek’s research zeroes in on the mechanisms of transfer of information within the family and school environment, and the ways in which this is tied to students’ actual math achievement in the classroom and their future career interests in STEM.
Developing a method to test STEM self-esteem in kids
Dr. Cvencek has developed a patented, first-in-the-world method for examining students’ and teachers’ beliefs and biases that function at an unconscious or implicit level: the Child Implicit Association Test (IAT). The Child IAT is a precise measurement tool that allows us to distinguish among four kinds of ‘non-academic’ beliefs that influence early interest in math: stereotypes, attitudes, identities, and self-esteem.
It is also a powerful diagnostic tool: the Child IAT generates computerized measures that can identify students who may be at risk for lower academic performance, reduce teachers’ own biases, and evaluate the effectiveness of teaching practices. The Child IAT is easy to carry out – it takes less than 10 minutes and is simple for teachers to use. It is suitable for children ages 4-10 years old and no minimum reading level is required.
They're already beginning to develop an implicit identity of ‘math is for me’ or ‘math is not for me’ at a surprisingly early age. These self-concepts matter because they are correlated with actual behavior, such as math achievement in the classroom." says Dr. Cvencek.
It is of profound importance to understand how family, peers, teachers, and society-at-large influence children’s beliefs and attitudes about STEM. Creating Learning Mindsets could also make schools work for all.
Implementing intervention programs in schools would facilitate more positive feelings about math, greater self-confidence in students, and diffuse negative biases, both conscious and unconscious. It would level the playing field by providing all students with the opportunity to strive for their full potential.
Original contribution from Dan Johnson, Advancement Officer at I-LABS, the Institute for Learning & Brain Sciences at the University of Washington