Refining statistical problems: a hybrid problem-based learning methodology to improve students’ motivation

• Autores: Josep Maria Mateo Sanz, Agusti Solanas, Dolors Puigjaner Riba, Carme Olivé Farré
• Localización: The International journal of engineering education, ISSN-e 0949-149X, Vol. 26, no. Extra 3, 2010, págs. 667-680
• Idioma: inglés
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• Resumen

  • Statistics is fundamental to many disciplines and plays a central role in Engineering and Sciences. To understand and apply statisticsrequires students to be highly motivated. Therefore, fostering students’ learning and reducing dropout rates implies increasing students’motivation. We present a guided problem-based learning approach to teaching statistics in hybrid learning environments and we analyseits impact on students’ motivation. We pay special attention at subdividing problems into small sections to obtain detailed sets ofquestions associated with specific concepts or procedures. This degree of detail guarantees that students can easily tackle theseproblems in virtual learning environments. In addition, thanks to the use of automatically generated log files, our proposal allowsteachers to finely analyse the steps in which students have difficulties. We assess our proposal in terms of student satisfaction andmotivation. The results show that although success rates are not improved, students’ motivation for the subject increases. Consequently,our approach is a good choice to improve motivation and reduce the dropout rate in difficult subjects such as Statistics.