Invoking interactive qualitative analysis as a methodology in statistics education research

Anisha Ananth,Suriamurthee Maistry

doi:10.4102/td.v16i1.786

Abstract

This study investigated the use of interactive qualitative analysis (IQA), as a research methodology, to develop an understanding of students’ experiences of learning statistics in a threshold concepts-enriched tutorial programme. Interactive qualitative analysis methodology offered a systematic, rigorous and accountable approach to conducting qualitative research. The participants constructed their own meaning of reality from their experiences of interacting with the phenomenon in context and, in its refutation of traditional qualitative norms of enquiry that casts the role of the researcher as the expert, IQA stands out – entrusting participants with data generation, analysis and interpretation. Participants’ reflections of their experiences of the phenomenon under study are classified according to variously identified emergent themes called ‘affinities’. Relationships between these affinities are extricated and characterised in a visual representation of the phenomenon called a systems influence diagram. Thus, the researcher’s role was purely facilitative, greatly limiting the potential for skewed power relations and bias which is often hazardous in qualitative research. The paramount value of this article was that it offered a practical methodological approach to using IQA in qualitative statistics education research, in particular, and mathematical sciences education research, in general. A summarised account of the main findings of the broader study was also presented.

Highlights

In today’s data-driven technocratic society, data and statistics form the bedrock for informed decision making.[1,2] As such, almost all disciplines have incorporated an introductory statistics course into their academic programme structure
The focus group identified four affinities – themes or components of meaning of their learning in the tutorial programme – and the interactive qualitative analysis (IQA) processes led to the construction of the systems influence diagram (SID) above, which captures how the group theorised the inter-relationships among these affinities
Tut group – the group interactions and processes arising through the multiplicity of pedagogical approaches adopted in the tutorial programme – enabled and supported cognitive, metacognitive and affective aspects of learning

Summary

Introduction

In today’s data-driven technocratic society, data and statistics form the bedrock for informed decision making.[1,2] As such, almost all disciplines have incorporated an introductory statistics course into their academic programme structure. Students majoring in other disciplines often make for very reluctant learners of statistics This may be attributable to statistics often being described as a difficult subject to learn, because of the abstract nature of some of its concepts, the distinct way of thinking and analysis of problems that it requires, or the way in which it is traditionally taught. In South Africa, features of this country’s higher education context may intensify the challenges faced by both students and teachers of statistics, with research reflecting concerns around poor academic performance and low throughput in introductory statistics classes across higher education institutions This literature is dominated by quantitative studies determining the impact on performance because of students’ characteristics and prior academic attainment, behaviour and motivation, or educational interventions, in terms of pedagogical or teacher-focused interventions.[5,6,7,8,9,10,11]

Methods

Results

Conclusion