Dataset - Business School Master students’ awareness and perception of SDGs
Description
Dataset used in the investigation titled Business School Master students’ awareness and perception of SDGs (Not published yet). Purpose – This study investigates the dynamics of awareness, perception, and sustainability literacy regarding the Sustainable Development Goals (SDGs) among Master's students at a leading Latin American business school. It addresses how educational programs integrating sustainability content contribute to students' understanding and engagement with the SDGs, as well as the specific academic and professional factors that impact on these dimensions in the Latin American higher education context. Design – The authors ran a quantitative study using a survey instrument, adapted from Leiva-Brondo et al. (2022), collecting data from a representative sample (n=403) of Master's students. ANOVA and Tukey post hoc tests assessed significant differences between demographic groups, academic programs, and professional backgrounds. Random forest algorithms determined the relative importance of various variables in predicting student learning outcomes in the sustainability area. Findings – Student progress within their Master's program significantly enhances SDG awareness, perception, and sustainability literacy, with face-to-face programs proving more effective than other formats. Students in sustainability-focused sectors demonstrated a higher level of awareness. Predictive modeling indicates program progress as the most important variable. These findings have implications for curriculum design and the global pursuit of developing a well-educated generation equipped to contribute to the achievement of the SDGs. Originality – This research contributes empirical evidence from a Latin American business school to the global discourse on SDG integration in higher education. It examines how different curriculum delivery modes impact sustainability literacy and further, goes beyond awareness, exploring student participation in SDG-related activities and the impact of progress within programs. Authorship: Sanchez S. ; De las Casas, F.; Zegarra, J. & Iglesias, J.
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The study was conducted among students enrolled in a Master’s Program in a Peruvian Business School. The selection of this particular institution, a distinguished Triple-Accredited Latin American business school, as the focus for this investigation is well-founded due to its significant standing and influence within the region. Studying the student body of this institution offers valuable insights into the perspectives and competencies being cultivated amongst future business leaders in this key economic region. To ensure the reliability of the results, the study focused on the entire population of 3,060 students enrolled in the various master's programmes offered by the business school. Using a simple random sampling method, a minimum sample size of 342 students was estimated; however, it was decided to conduct more surveys, anticipating the possibility that some selected students might decide not to participate. A total of 407 responses were obtained, of which 403 gave their consent to participate and had the necessary information. This sample size guarantees a 95% confidence level with a corresponding margin of error of 4.5%, providing a statistically sound basis for analysing students' knowledge, perception and literacy regarding the Sustainable Development Goals in this specific institutional context. Student participation was entirely voluntary, and informed consent was obtained before data collection began. The survey utilized an adapted version of the instrument employed by Leiva-Brondo et al. (2022) for the measurement of these variables (Appendix 1). Additionally, questions aimed at measuring factors related to the demographic characteristics of the students, as well as their academic and professional background, were included. To analyze whether the studied factors are related to the levels of awareness (H1) and perception (H2) of the Sustainable Development Goals (SDGs) and sustainability literacy (H3) among students, the ANOVA mean comparison test, along with Tukey's test to analyze differences between groups, was employed (Leiva-Brondo et al., 2022). Moreover, given the interest in the relative importance of the factors, a data mining approach will be employed. Specifically, the random forest algorithm introduced by Breiman (2001) will be used to determine which factors have a greater influence (H4) on the results of the variables measured through the NodePurity and the decrease in Mean Squared Error. Prediction error, described as MSE is based on permuting out-of-bag sections of the data per individual tree and predictor, and the errors are then averaged. In the regression context, Node purity is the total decrease in the residual sum of squares when splitting on a variable averaged over all trees (i.e. how well a predictor decreases variance).
Institutions
- Pontificia Universidad Catolica del Peru CENTRUM Catolica