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6 Validity and reliability There are many different types of validity and reliability. Threats to validity and reliability can never be erased completely; rather the effects of these threats can be attenuated by attention to validity and reliability throughout a piece of research. This chapter discusses validity and reliability in quantitative and qualitative, naturalistic research. It suggests that both of these terms can be applied to these two types of research, though how validity and reliability are addressed in these two approaches varies. Finally validity and reliability are addressed, using different instruments for data collection. It is suggested that reliability is a necessary but insufficient condition for validity in research; reliability is a necessary precondition of validity, and validity may be a sufficient but not necessary condition for reliability. Brock- Utne (1996: 612) contends that the widely held view that reliability is the sole preserve of quantitative research has to be exploded, and this chapter demonstrates the significance of her view. Defining validity Validity is an important key to effective research. If a piece of research is invalid then it is worthless. Validity is thus a requirement for both quantitative and qualitative/naturalistic research (see http://www.routledge.com/textbooks/ 9780415368780 – Chapter 6, file 6.1. ppt). While earlier versions of validity were based on the view that it was essentially a demonstration that a particular instrument in fact measures what it purports to measure, more recently validity has taken many forms. For example, in qualitative data validity might be addressed through the honesty, depth, richness and scope of the data achieved, the participants approached, the extent of triangulation and the disinterestedness or objectivity of the researcher (Winter 2000). In quantitative data validity might be improved through careful sampling, appropriate instrumentation and appropriate statistical treatments of the data. It is impossible for research to be 100 per cent valid; that is the optimism of perfection. Quantitative research possesses a measure of standard error which is inbuilt and which has to be acknowledged. In qualitative data the subjectivity of respondents, their opinions, attitudes and perspectives together contribute to a degree of bias. Validity, then, should be seen as a matter of degree rather than as an absolute state (Gronlund 1981). Hence at best we strive to minimize invalidity and maximize validity. There are several different kinds of validity (see http://www.routledge.com/textbooks/ 9780415368780 – Chapter 6, file 6.2. ppt): content validity criterion-related validity construct validity internal validity external validity concurrent validity face validity jury validity predictive validity consequential validity systemic validity catalytic validity ecological validity cultural validity descriptive validity interpretive validity theoretical validity evaluative validity.

134 VALIDITY AND RELIABILITY It is not our intention in this chapter to discuss all of these terms in depth. Rather the main types of validity will be addressed. The argument will be made that, while some of these terms are more comfortably the preserve of quantitative methodologies, this is not exclusively the case. Indeed, validity is the touchstone of all types of educational research. That said, it is important that validity in different research traditions is faithful to those traditions; it would be absurd to declare a piece of research invalid if it were not striving to meet certain kinds of validity, e.g. generalizability, replicability and controllability. Hence the researcher will need to locate discussions of validity within the research paradigm that is being used. This is not to suggest, however, that research should be paradigm-bound, that is a recipe for stagnation and conservatism. Nevertheless, validity must be faithful to its premises and positivist research has to be faithful to positivist principles, for example: controllability replicability predictability the derivation of laws and universal statements of behaviour context-freedom fragmentation and atomization of research randomization of samples observability. By way of contrast, naturalistic research has several principles (Lincoln and Guba 1985; Bogdan and Biklen, 1992): The natural setting is the principal source of data. Context-boundedness and ‘thick description’ are important. Data are socially situated, and socially and culturally saturated. The researcher is part of the researched world. As we live in an already interpreted world, a doubly hermeneutic exercise (Giddens 1979) is necessary to understand others’ understandings of the world; the paradox here is that the most sufficiently complex instrument to understand human life is another human (Lave and Kvale 1995: 220), but that this risks human error in all its forms. There should be holism in the research. The researcher – rather than a research tool – is the key instrument of research. The data are descriptive. There is a concern for processes rather than simply with outcomes. Data are analysed inductively rather than using aprioricategories. Data are presented in terms of the respondents rather than researchers. Seeing and reporting the situation should be through the eyes of participants – from the native’s point of view (Geertz 1974). Respondent validation is important. Catching meaning and intention are essential. Indeed Maxwell (1992) argues that qualitative researchers need to be cautious not to be working within the agenda of the positivists in arguing for the need for research to demonstrate concurrent, predictive, convergent, criterionrelated, internal and external validity. The discussion below indicates that this need not be so. He argues, with Guba and Lincoln (1989), for the need to replace positivist notions of validity in qualitative research with the notion of authenticity. Maxwell (1992), echoing Mishler (1990), suggests that ‘understanding’ is a more suitable term than ‘validity’ in qualitative research. We, as researchers, are part of the world that we are researching, and we cannot be completely objective about that, hence other people’s perspectives are equally as valid as our own, and the task of research is to uncover these. Validity, then, attaches to accounts, not to data or methods (Hammersley and Atkinson 1983); it is the meaning that subjects give to data and inferences drawn from the data that are important. ‘Fidelity’ (Blumenfeld-Jones 1995) requires the researcher to be as honest as possible to the self-reporting of the researched. The claim is made (Agar 1993) that, in qualitative data collection, the intensive personal

134 VALIDITY AND RELIABILITY<br />

It is not our intention in this chapter to<br />

discuss all of these terms in depth. Rather the<br />

main types of validity will be addressed. The<br />

argument will be made that, while some of<br />

these terms are more comfortably the preserve of<br />

quantitative methodologies, this is not exclusively<br />

the case. Indeed, validity is the touchstone of<br />

all types of educational research. That said, it<br />

is important that validity in different research<br />

traditions is faithful to those traditions; it would<br />

be absurd to declare a piece of research invalid<br />

if it were not striving to meet certain kinds<br />

of validity, e.g. generalizability, replicability and<br />

controllability. Hence the researcher will need<br />

to locate discussions of validity within the<br />

research paradigm that is being used. This is<br />

not to suggest, however, that research should be<br />

paradigm-bound, that is a recipe for stagnation<br />

and conservatism. Nevertheless, validity must be<br />

faithful to its premises and positivist research<br />

has to be faithful to positivist principles, for<br />

example:<br />

<br />

<br />

<br />

<br />

<br />

<br />

<br />

<br />

controllability<br />

replicability<br />

predictability<br />

the derivation of laws and universal statements<br />

of behaviour<br />

context-freedom<br />

fragmentation and atomization of research<br />

randomization of samples<br />

observability.<br />

By way of contrast, naturalistic research has<br />

several principles (Lincoln and Guba 1985;<br />

Bogdan and Biklen, 1992):<br />

<br />

<br />

<br />

<br />

<br />

The natural setting is the principal source of<br />

data.<br />

Context-boundedness and ‘thick description’<br />

are important.<br />

Data are socially situated, and socially and<br />

culturally saturated.<br />

The researcher is part of the researched world.<br />

As we live in an already interpreted world, a<br />

doubly hermeneutic exercise (Giddens 1979) is<br />

necessary to understand others’ understandings<br />

of the world; the paradox here is that the most<br />

sufficiently complex instrument to understand<br />

human life is another human (Lave and Kvale<br />

1995: 220), but that this risks human error in<br />

all its forms.<br />

There should be holism in the research.<br />

The researcher – rather than a research<br />

tool – is the key instrument of research.<br />

The data are descriptive.<br />

There is a concern for processes rather than<br />

simply with outcomes.<br />

Data are analysed inductively rather than using<br />

aprioricategories.<br />

Data are presented in terms of the respondents<br />

rather than researchers.<br />

Seeing and reporting the situation should be<br />

through the eyes of participants – from the<br />

native’s point of view (Geertz 1974).<br />

Respondent validation is important.<br />

Catching meaning and intention are essential.<br />

Indeed Maxwell (1992) argues that qualitative<br />

researchers need to be cautious not to be<br />

working within the agenda of the positivists in<br />

arguing for the need for research to demonstrate<br />

concurrent, predictive, convergent, criterionrelated,<br />

internal and external validity. The<br />

discussion below indicates that this need not be<br />

so. He argues, with Guba and Lincoln (1989),<br />

for the need to replace positivist notions of<br />

validity in qualitative research with the notion<br />

of authenticity. Maxwell (1992), echoing Mishler<br />

(1990), suggests that ‘understanding’ is a more<br />

suitable term than ‘validity’ in qualitative research.<br />

We, as researchers, are part of the world<br />

that we are researching, and we cannot be<br />

completely objective about that, hence other<br />

people’s perspectives are equally as valid as our<br />

own, and the task of research is to uncover<br />

these. Validity, then, attaches to accounts, not<br />

to data or methods (Hammersley and Atkinson<br />

1983); it is the meaning that subjects give to<br />

data and inferences drawn from the data that<br />

are important. ‘Fidelity’ (Blumenfeld-Jones 1995)<br />

requires the researcher to be as honest as possible<br />

to the self-reporting of the researched.<br />

The claim is made (Agar 1993) that, in<br />

qualitative data collection, the intensive personal

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