Creative Teaching and Learning

Giving Sixth Formers Better Skills In Qualitative Data Analysis

When it comes to teaching data collection and analysis, the effective use of qualitative data is often overlooked. Andrew Shenton offers a method for training Sixth Formers to assess qualitative data and gain more widely applicable analysis skills.
A group of teenage students collaborating on a project in a classroom.
A group of teenage students collaborating on a project in a classroom

The Problem

From an early stage in children's education, we set them tasks that involve the collection and analysis of quantitative data. The most rudimentary may involve twisting a spinner, tossing a coin or rolling dice a certain number of times, noting the outcomes and then presenting the frequencies in a table or some sort of chart. Usually, such work is intended to help deliver the Mathematics or ICT curriculum. In later years, students may design their own questionnaires in more child-centred research projects or 'investigations', but an emphasis on the collection of figures – or at least data that are amenable to statistical treatment – often remains.

Notwithstanding the efforts of Kellett, who has promoted teaching a range of research methods to children and young people(1), qualitative material is rarely gathered. When it is elicited in – for example – a questionnaire that allows the participant to enter some responses in their own words, the ways in which it is analysed by young people tend to be superficial and lacking rigour, adding weight to the longstanding criticism that much qualitative inquiry is 'soft' and 'subjective'. 

The naivety of the methods adopted by youngsters typically results from the fact that, for many, training in qualitative inquiry and qualitative data analysis has been highly limited or even non-existent. I have discussed the reasons for this in a previous piece.(2)

Despite its low profile in the classroom, qualitative work plays a vital role in research, complementing and augmenting traditional numerical investigation. It allows participants to express their ideas and experiences in depth and using their own language and concepts, rather than those of the researcher.

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