Using Data Visualization and Data Science to Explore Self-efficacy in the Classroom and Academic Mindset by Grouping Demographic Variables

Abstract

This study explored the effects of students’ demographic characteristics on the outcome variable students’ Self-efficacy on classroom tasks (SE) using data visualization and data science techniques, which aims to discover the pattern in the data. Grouping variables included students’ self-reports of their gender (Male vs Female) and cultural identification. Data was drawn from five elementary schools (n=1986 students) and two middle schools (n=1257 students) in one suburban school district in the south-western U.S. School contextual variables included socio-economic status (operationalized as percent enrollment Free and Reduced Meal Plan) and school level (elementary vs middle school). Main effect variables explored included Individual Mindset (IM), Belonging in the classroom, and Relevance of classroom tasks. JMP Pro 15 and SPSS 26 were used to perform the analyses. Teachers can learn the methods and use the results of this study to improve their understanding of their students in diverse populations. Teacher skills in developing student self-efficacy promote student motivation leading to improved outcomes.

Keywords: self-efficacy, classroom culture, demographic influences, data visualization, socio-economic status, elementary and middle school, gender, teaching online

DOI: 10.7176/JEP/11-24-01

Publication date:August 31^st 2020