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INTRODUCTION
CONTENTS
1.1 Empirical research – data
1.2 Quantitative and qualitative data
1.3 Relaxing the qualitative–quantitative distinction
1.4 Some simplifying devices
1.5 Essentials and logic
1.6 Science, the social sciences and education research
1.7 A model of research
1.8 Organisation of the book
Chapter summary
Key terms
Further reading
Exercises and study questions
LEARNING OBJECTIVES
After studying this chapter you should be able to:
• Explain the phrase ‘empirical research’ and define what is meant by an empirical research question
• Describe the differences between qualitative and quantitative data and their implications for different approaches to research
• Describe and explain the relationship between research questions and research methods
• Explain and relate to your own research the model of research shown in Section 1.7.
Being a researcher and doing research in education carries with it the possibility of deep and creative, sometimes playful, sometimes frustrating engagement with families of practices that weave together different forms of knowledge and value judgements about enabling and sustaining human flourishing. There is a wide diversity of approaches to educational inquiry that feed off and complement each other, but it can also be a fiercely disputatious field. This may be bewildering for the novice researcher, but struggling through this bewilderment is part of developing as a researcher in one’s own right: part of growing to speak with one’s own voice and of calibrating one’s own methodological compass while encountering a range of concrete research situations and of different ways of constructing educational problems. This book aims to assist this process not by providing technical recipes, but by making explicit, from the authors’ own perspectives and experiences as researchers, some of the deliberative processes and conceptual complexities that constitute educational research.
This book is about empirical research in education. It covers research with both qualitative and quantitative data, and focuses on the essential features of each. It places both types of approaches within the same framework for organising research, and it deals with them under the same main headings – design, data collection, data analysis. These main headings follow logically from the view of research outlined in this chapter, and elaborated in Chapters 5 and 6. The stress in the book is on the logic of what is done in research, rather than its technical aspects. Therefore it is not a ‘how to do it’ book, but aims instead to develop a basic understanding of the issues involved and of the ideas behind the main techniques.
The general audience for the book is anybody who wants to learn about research in education. A more specific audience is postgraduate and upper level undergraduate students in universities, who need to learn about empirical research, and many of whom need to execute a research project, often as a dissertation for a higher degree. We hope also that the book will be useful to those who teach research methods, to practitioner-researchers and to early career education researchers.
At the end of each chapter we have offered a reading list consisting of a mixture of classical texts about research methodology, philosophy, social and educational theory, and more recent specialist textbooks. Reading the classics is as important as keeping up to date with new developments, and both can be equally gratifying or disturbing – but neither of the two is a full replacement for reading research monographs, reports and articles. We also encourage the reader to explore the examples provided throughout the text in full; in as much as possible, we have provided references not only to the original texts, but also to reflective pieces by their authors, in which they give an account of the research process and of the decisions and impulses that had moved it along. Many of these examples are pieces of research that made us think differently, or more deeply, or in a more focused way, about research – and we are hoping that they may do the same for the readers.
1. 1 Empirical research – data
Our subject is empirical research in education. Empiricism is a philosophical term to describe the epistemological theory that regards experience as the basis or source of knowledge (Audi, 2011: 116). Experience refers here to what is received through the senses, to sense data or to what can be observed, as well as to the interaction between the person and the world. Thus ‘empirical’ means based on direct experience or observation of, or interaction with, the world. To say that a question is an empirical question is to say that we will answer it – or try to answer it – by obtaining direct, observable information from the world, rather than, for example, by reasoning alone, or by arguing from first principles (although the latter forms of inquiry are also crucial to the well-rounded development of educational research). The key concept is ‘observable information about (some aspect of) the world’. The term used by researchers for the ‘observable information’ or ‘direct experience’ that forms the basis of their claims about the world is data. The essential idea in empirical research is to use data in order to answer questions, and to develop and test ideas.
Empirical research is not the only type of research in education today. Examples of other types of research are theoretical research, conceptual-philosophical research and historical research. This book concentrates on empirical research, but many of the points it makes may apply also to other types of research.
1. 2 Quantitative and qualitative data
‘Data’ is obviously a very broad term, so we subdivide data for empirical research into two main types:
• Quantitative data – which are data in the form of numbers (or measurements), and
• Qualitative data – which are data not in the form of numbers (most of the time, this means words, but it can also mean other things, such as images, artefacts, or music).
This leads to two simplifying definitions:
• Quantitative research is empirical research where the data are in the form of numbers.
• Qualitative research is empirical research where the data are not in the form of numbers.
These simplified definitions are useful for getting started in research, but they do not give the full picture of the quantitative–qualitative distinction. For many researchers, the term ‘quantitative research’ means more than just research that uses quantitative or numerical data. It refers to a whole way of thinking, or an approach, which involves a collection or cluster of methods, as well as data in numerical form. Similarly, for many researchers qualitative research is much more than just research that uses non-numerical data. It points to a heterogeneous set of approaches to research, drawing on different ways of thinking about social reality and involving a collection of methods for working with data that are in non-numerical or qualitative form. Quantitative researchers typically conceptualise the world in terms of variables (which can be measured) and study relationships between these variables. Qualitative researchers, by contrast, typically study cases and processes, rather than variables.
Some argue that the terms ‘quantitative research’ and ‘qualitative research’ point to distinctions not just between types of data, but between fundamentally different ways of conceptualising and exploring the social reality being studied, and to the designs and methods used to represent these ways of thinking. We will come back to this argument, and to responses to it, in Section 1.3.
In teaching about research, we find it useful to approach the quantitative–qualitative distinction primarily through the nature of the data. Later, the discussion can encompass and question the distinctions between ways of conceptualising the reality being studied and the methods. Also, in the practical business of planning and doing research for their dissertations, students very often focus on such questions as: Should the data be numerical, textual, or visual? Am I going to measure variables in this research, or not? Am I going to elicit detailed information about particular cases? Am I going to combine different types of data? Or, in other words, should my research be quantitative, qualitative or a combination?
For these reasons, we will keep the nature of the data at the heart of the distinction between quantitative and qualitative research, and that is why we start with the simplified definitions shown above. But we need also to remember that research is much more diverse than this distinction might imply, in its philosophical underpinnings (or ways of thinking about the social world and its values, and about the ways in which we may gain knowledge of it), in its methods and in its data.
1. 3 Relaxing the qualitative–quantitative distinction
The qualitative–quantitative distinction has long been a basic organising principle for the research methods literature. However, the value of this sharp distinction has been questioned in the literature (see, for example, Hammersley, 1992: 41–3; Pring, 2004: 44–57), and important similarities, overlaps and complementarities have been noted between different approaches (Tashakkori and Teddlie, 2010). According to Pring (2004: 44–57), it can be very tempting to describe the distinction between quantitative and qualitative research in terms of a sharp opposition between mutually exclusive epistemological and ontological positions. However, he argues, such a move is ‘mistaken’ and leads to a ‘false’ methodological dualism.
Therefore, once understood, this distinction can be relaxed. This book deals with both qualitative and quantitative approaches to research, and is based on the view that neither approach is better than the other, that both are needed, that both have their strengths and weaknesses, and th...