Developing postgraduate students statistical thinking in university: Evaluation of a statistical thinking learning environment model
MetadataShow full item record
Introduction: Statistics education has been critical for researchers in health disciplines as it underpins quantitative approaches to empirical research. This presentation evaluates a model for an interactive, postgraduate level statistics course in university that is designed to develop students' statistical reasoning and thinking. The model used for this study is called a 'Statistical Thinking Learning Environment' (SRLE) and is built on the constructivist theory of learning. The contemporary view of learning in accordance with the constructivist theory is that new knowledge and understandings are based on the existing knowledge and beliefs we already have and are grounded in our experiences (e.g., Cobb, 1994; Vygotsky, 1978). We learn by doing. And when we learn, our previous knowledge does not go away; it is integrated with the new knowledge. The implication of current theories of learning is that good education practice consists of designing learning environments that motivate students to construct knowledge. This involves activities that provide students many opportunities to think, reason, and reflect on their learning, as well as discussing and reflecting with their peers. Methods: The SRTE model was developed to enhance students understanding of statistics, their ability to think and reason statistically, and apply the statistical skills in practice. The SRTE is the interactive combination of course materials, class activities and culture, discussion, online technology, teaching approach, and assessment. 90 students in the current cohort and 35 students in previous year cohorts were invited to participate in study to evaluate the six principles of the model: 1. Focus on developing central statistical ideas rather than on presenting set of tools and procedures. 2. Use real and motivating data sets to engage students in making and testing research hypotheses. 3. Use classroom activities to support the development of students' reasoning and critical thinking. 4. Integrate the use of appropriate technological tools that allow students to test their inferences, explore and analyse data, and develop their statistical reasoning. 5. Promote classroom discourse that includes statistical arguments and sustained exchanges that focus on significant statistical ideas. 6. Use assessment to learn what students know and to monitor the development of their statistical learning as well as to evaluate instructional plans and progress. Mixed research methods using both qualitative and quantitative method were used to evaluate the effectiveness of SRTE method to enhance students learning and applications of their learning in their research and work related projects. Results: The majority of students who responded to the qualitative interview and quantitative survey indicated that the SRTE model significantly enhanced their capacity to use statistical skills in the research project and their work place, use the knowledge and skills for further learning, and transfer the skills to new projects and learning. Discussions and conclusions: The six principles outlined earlier are key elements in developing a class where students are engaged in making and testing inference using data, discussing and explaining statistical reasoning, and focusing on the implication and implementation of statistical principles in further research and work. Keywords - Teaching, Active Learning, Statistical Thinking, Postgraduate Statistics Course, Constructivism.
EDULEARN 10: Publications
Copyright 2010 IATED. The attached file is reproduced here in accordance with the copyright policy of the publisher. For information about this conference please refer to the conference's website or contact the authors.
Public Health and Health Services not elsewhere classified