Inventory of Mathematics Attitudes for STEM University Students: An Example of Engineering Courses

Resumo

Background: The attitude of students toward mathematics is a fundamental factor in their academic progress and performance. In this context, it is important to rely on reliable instruments capable of capturing these attitudes, such as the Attitudes Toward Mathematics Inventory (ATMI), which consists of 49 items, designed to measure six different psychological dimensions.  Objectives: We present an instrument developed by researchers from Brazil and the Czech Republic to identify mathematical self-efficacy and anxiety. First, we want to test the statistical validity of this instrument, based on the ATMI and adapted to the context of university education. Then, we use it to assess the mathematical attitudes of engineering students at a university in Brazil. Design: We adapted and validated a 20-item version of the Attitudes Toward Mathematics Inventory (ATMI), using a five-point Likert scale ranging from "strongly disagree" to "strongly agree." We conducted an Exploratory Factor Analysis (EFA) using SPSS 22 software, and obtained results regarding the self-efficacy and anxiety of the studied population. Setting and Participants: The study was conducted with 323 first-year undergraduate STEM students at the University of Campinas in Campinas, SP, who responded freely to the questionnaire presented. Data collection and analysis: The data were obtained from responses to the questionnaire presented in this study, using 20 Likert-scale items, ranging from “strongly disagree” to “strongly agree”. We then conducted an exploratory factor analysis (EFA) using the SPSS 22 software. Results: The instrument demonstrated high reliability (Cronbach's alpha = .91). The method indicates the independence of the factors, suggesting that the methodological processes were aimed at understanding how these emotional and cognitive factors influence student success and professional identity. Students in Computer Engineering demonstrated a high level of self-efficacy. Simultaneously, the students of Food Engineering exhibited lower levels of self-efficacy and higher levels of anxiety, suggesting disengagement with mathematics. Conclusions: The adaptation of the ATMI is a reliable and efficient instrument for measuring mathematical attitudes, providing an important tool for future research for engineering curricula. Our results are consistent with the pattern that mathematical self-efficacy and anxiety are inversely related.