Strengthening Statistical Reasoning in Students of Engineering Programs through Active Methodologies
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| Title: | Strengthening Statistical Reasoning in Students of Engineering Programs through Active Methodologies |
|---|---|
| Language: | English |
| Authors: | Hugo Alvarado Martínez (ORCID |
| Source: | Teaching Statistics: An International Journal for Teachers. 2026 48(2):116-129. |
| Availability: | Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us |
| Peer Reviewed: | Y |
| Page Count: | 14 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Engineering Education, Logical Thinking, Data Analysis, Active Learning, Statistics, Student Attitudes |
| DOI: | 10.1111/test.70011 |
| ISSN: | 0141-982X 1467-9639 |
| 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. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1504600 |
| Database: | ERIC |
| 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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| ISSN: | 0141-982X 1467-9639 |
| DOI: | 10.1111/test.70011 |
