Integrating Qualitative Research Approaches in Traditional Introductory Statistics Courses: Pros and Cons

In this paper we seek to add to a scholarly dialogue concerning the arguments for and against integrating selected qualitative research approaches in traditional introductory statistics courses. Given recurring concerns about students' motivation, achievements, and eventual understanding of the role of (quantitative and qualitative) data in providing answers to real-world problems, we look beyond the strict borders of the discipline of statistics. We advocate a guided exposure of learners to qualitative methods based on a 'triangle model' of context, demands of the learning process, and learners' acquired knowledge and skills. Some of our arguments pertain to expectations and needs of learners and their prospective employers; emerging knowledge regarding the nature and complexity of the learning of statistics; and the structure of real-world data-based queries. The model points to a need for a broad multi-method-grounded knowledge as well as communicative and interpretive skills that are not being developed in many introductory statistics courses.