Strengthening statistical reasoning in students of engineering programs through active methodologies

Abstract Data analysis is essential in engineering sciences for the making of informed decisions. This article characterizes the level of statistical reasoning in engineering students based on the model of Wild and Pfannkuch. Through a research focus, the creation of statistical problems, the formulation of researchable questions, and the validation of hypotheses are promoted. It was observed that, even though the students valued the model of reasoning, there were difficulties in the bivariate data analysis. However, the research strategy fostered a more active role, encouraging the elaboration of questions and argumentation based on the descriptive analysis of the data. The results show a positive attitude toward statistics and the analysis of real situations, suggesting the potential of this methodology to strengthen statistical reasoning in engineering contexts.

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Publication Details

Journal
Teaching Statistics
Published
2025-09-27
DOI
https://doi.org/10.1111/test.70011
Primary Topic
Statistics Education and Methodologies
Type
article
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article

Strengthening statistical reasoning in students of engineering programs through active methodologies

Hugo Alvarado Martínez, María Lidia Retamal Pérez, Luis Roberto Pino-Fan, Jeanne Miranda
Teaching Statistics
Statistics Education and Methodologies
article

Strengthening statistical reasoning in students of engineering programs through active methodologies

Hugo Alvarado Martínez, María Lidia Retamal Pérez, Luis Roberto Pino-Fan, Jeanne Miranda
article en

Abstract

Abstract Data analysis is essential in engineering sciences for the making of informed decisions. This article characterizes the level of statistical reasoning in engineering students based on the model of Wild and Pfannkuch. Through a research focus, the creation of statistical problems, the formulation of researchable questions, and the validation of hypotheses are promoted. It was observed that, even though the students valued the model of reasoning, there were difficulties in the bivariate data analysis. However, the research strategy fostered a more active role, encouraging the elaboration of questions and argumentation based on the descriptive analysis of the data. The results show a positive attitude toward statistics and the analysis of real situations, suggesting the potential of this methodology to strengthen statistical reasoning in engineering contexts.

Teaching Statistics
Universidad Católica de la Santísima Concepción (CL), Universidad de Sonora (MX), Universidad Tecnológica de Santiago (DO), Metropolitan University of Technology (CL)
Openalex Percentile: Top 75%
Statistics Education and Methodologies
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Strengthening statistical reasoning in students of engineering programs through active methodologies — Hugo Alvarado Martínez, María Lidia Retamal Pérez, et al. · Teaching Statistics (2025) | TGRS Research Map | TGRS