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Theoretical Issues in Ergonomics
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There are no qualitative methods
– nor quantitative for that matter:
the misleading rhetoric of the
qualitative–quantitative argument
a
b
Rodney Åsberg , Daniel Hummerdal & Sidney Dekker
c
a
Department of Education, Gothenburg University, Gothenburg,
Sweden
b
Centre de recherche sur les Risques et les Crises, École des
Mines de Paris, Sophia-Antipolis, France
c
Key Centre for Ethics, Law, Justice and Governance, Griffith
University, Brisbane, Australia
Published online: 06 Jul 2011.
To cite this article: Rodney Åsberg , Daniel Hummerdal & Sidney Dekker (2011): There are
no qualitative methods – nor quantitative for that matter: the misleading rhetoric of the
qualitative–quantitative argument, Theoretical Issues in Ergonomics Science, 12:5, 408-415
To link to this article: http://dx.doi.org/10.1080/1464536X.2011.559292
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Theoretical Issues in Ergonomics Science
Vol. 12, No. 5, September–October 2011, 408–415
There are no qualitative methods – nor quantitative for that matter: the
misleading rhetoric of the qualitative–quantitative argument
Rodney Åsberga, Daniel Hummerdalb* and Sidney Dekkerc
a
Department of Education, Gothenburg University, Gothenburg, Sweden; bCentre de recherche
sur les Risques et les Crises, École des Mines de Paris, Sophia-Antipolis, France; cKey Centre for
Ethics, Law, Justice and Governance, Griffith University, Brisbane, Australia
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(Received 30 August 2010; final version received 19 January 2011)
This article is about the comprehensive but meaningless rhetoric encircling the
pseudo issue of quantitative–qualitative method. Two questions get clarification
in this article. First, what does the term method mean, and second, what
constraints should be attached to the term when moving into the theory and
practice of science. Based on an examination of these two, we subsequently
address the question of what the quantitative–qualitative argument is about. Our
reasoning leads to the conclusion that the quantitative–qualitative argument
should be removed from the agenda, so that significant and important a priori
choices may be given due attention instead.
Keywords: qualitative; quantitative; ontology; epistemology; critical theory;
method
1. Introduction
A decade ago, Xiao and Vicente (2000) pointed out that it is not very common for
ergonomics research to spend much time on the epistemological foundations of its work.
This article suggests that one of the reasons for a muted debate is the misleading
rhetoric surrounding the pseudo issue of quantitative versus qualitative methods
(Desnoyers 2004, Hancock and Szalma 2004, Kanis 2004). In both research and the
debates surrounding it, the false choice between qualitative versus quantitative methods is
often conflated with applied versus basic research. Advocates of the latter might question
the truth value of findings by more interpretative methods of real-word settings. And those
relying on qualitative methods can seek creditability through ecological appeals that
implicitly or explicitly criticise the narrowness of quantitative approaches. In this article,
we argue that the quantitative–qualitative argument masks more essential epistemological
questions. By clarifying some of these, we hope that discussions about the status of one
approach over another can be discarded so that more crucial issues can be tackled and
progress can be made in our understanding of the multifaceted nature of ergonomic
questions.
*Corresponding author. Email: daniel.hummerdal@mines-paristech.fr
ISSN 1464–536X online
ß 2011 Taylor & Francis
DOI: 10.1080/1464536X.2011.559292
http://www.informaworld.com
Theoretical Issues in Ergonomics Science
409
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2. What is ‘method’?
Method, as a term, is derived from the Greek me´thodos (from meta: after and ho’dos: path)
along a path. Hence, a method describes the steps along a path, how to go about it, an
approach, or as defined in the English language: ‘A way or manner of doing something’
(The Advanced Learners Dictionary 1958, p. 792). When we say interview method, survey
method and observation method, the term method stands for ‘the way one goes about it’
when collecting data through interviews, questionnaires and observation. Thus, these are
different data collection processes. Here, we can already begin to see that a quantitative or
qualitative way of doing things hardly exists.
The problem is that it is not this sense of the word we use when we speak of
hermeneutic ‘method’, phenomenological ‘method’, ethnographic ‘method’ or positivistic
‘approach’. The same data collection procedures (for e.g. interview or observation) can, of
course, be used in several of these ‘methods’. Hence, what distinguishes them cannot be the
method, in the sense of how data are collected, but rather what kind of knowledge is
wanted, or even what knowledge is assumed to be or represent. This has to do with
epistemological considerations. Such considerations are of a different nature, but this is
seldom clarified. Often the use of the method concept is vague and broad, which creates
confusion with respect to choices and positions to be taken in the research process (Holme
and Solvang 1986, Patton 1990, Starrin and Svensson 1994, Hartman 1998, Denzin and
Lincoln 2000). This confusion surfaces notably with da Silva and Wahlberg (1994, p. 41, t):
The term ‘method’, which sometimes is used in an ambiguous and vague way, will hereafter be
used as a synonym to ‘approach’, ‘perspective’, ‘strategy’ and ‘methodology’.
But how does this reduce ambiguity? And how can method be synonymous with
‘methodology’? The obscurity of it all intensifies when they add the dichotomy
quantitative–qualitative (da Silva and Wahlberg 1994, p. 51, t):
As examples of specifically quantitative methods we find empirical observation, experiments
and statistics. As examples of specifically qualitative methods there are participant
observation, empathic understanding (the use of vivid realisation and empathy), in-depth
interviews, hermeneutics, phenomenology, phenomenography, and ‘grounded theory’ as well
as morphological or structural interpretation of myths . . . and existential analysis.
The category of qualitative methods thus contains anything from phenomenology,
hermeneutics and participant observation to in-depth interviews. The distinction quantitative–qualitative, however, usually tends to be grouped with the methodology issue. As
such it is adopted as a natural starting point for reasoning around methods. For example,
Hartman (1998, p. 14, t) writes in the preface: ‘In theory of methods one must make a
distinction between two types of examinations; quantitative and qualitative’. The question
is why we must make such a distinction.
3. Theory of science
To clarify the departure points for later reasoning, we can divide the field of science into
theoretical levels: from the level of ontology to the level of data. This is in order to
underscore the specific questions and determinations to be addressed at each level. The
borders between the levels are, however, not absolute. Both include discourse and
determinations of an ontological as well as an epistemological nature. And the distinction
idiographic – nomothetic may be traced partly to the level of method, and partly to the
epistemological level. But the levels are still sufficiently clear in showing a way out of
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unnecessary confusion. Below is a sketchy division:
(1) Ontology, the question of ‘o’ntos’ (Greek) the nature of being, of reality: is about
our perception of reality, our worldview. Idealism and materialism are perhaps the
two most distinct approaches found here, existentialism and dialectics are two
others.
(2) Epistemology, the study of ‘Episteme’ (Greek; knowledge, knowing), the sources of
knowledge and its validity: The main approaches are rationalism, that knowledge is
based on reasoning and empiricism, that knowledge is based on observations.
Kant’s studies (criticism) on the conditions and limitations of human knowledge,
and his criticism of ‘pure reason’ are fundamental to this level. The realistic starting
point, that there is a world independent of our consciousness and that it is possible
to obtain knowledge about this, versus the idealistic, that the ideas, the mental
representations are primary and knowledge relates only to these, have clear links to
ontological determinations. Relativism, constructivism and structuralism represent
different epistemological starting points, while hermeneutics, phenomenology and
positivism represent different approaches to knowledge.
(3.a) Methodology, the study of the ways we go about scientific investigations and how
to establish scientific knowledge; critical distinctions include idiographic (looking
for the uniqueness in individual cases) versus nomothetic (looking for law-like
connections) approaches. Also in this category, we find inductive – deductive –
abductive studies, or descriptive versus hypothesis- or theory-confirming. The
so-called hypothetical–deductive method is therefore a determination of methodological nature.
(3.b) Method, in the sense of a data collection process: when considering examples of
data collection methods, such as interview, questionnaire or observation method,
these distinctions relate to the approach taken (talk, write, observe) when
collecting data on different phenomena.
(4) Level of data, from data meaning facts, information, the plural of the Latin datum.
Divisions exist between hard data, soft data, numerical (numbers), non-numeric
(word) data or, if it should be necessary, quantitative and qualitative data. Data,
which we are aware of but by deduction, mirrors thus, quantitative and qualitative
characteristics of the phenomena or the objects we investigate. So the quantitative–
qualitative distinction belongs to this level. But once the distinction has been put in
place here, it becomes trivial. There is nothing more to say about it.
The first two levels are of an a priori character and therefore polemical, i.e. consensus
does not exist within the scientific community about these two. Therefore, there are crucial
choices to be made about what kind of world (ontology) one is looking at, for what kind of
knowledge (epistemology). Level three is more complementary. Particularly in the sense of
the data collection process (3.b) as several methods can be used to establish empirical
evidence for the same knowledge objective. Level 4, the data level, is totally complementary, since data in both numerical and non-numerical form are usually valid when we want
to find out about something.
It might be good if a fairly common terminology could be reached on the distinctions
within the epistemological field. Not primarily to create a semantic straitjacket, and for
that at all times use the ‘correct’ words, but to reduce some confusion of the terms and to
surface critical choices to be made. Here is a suggestion:
. The term ‘method’ is used for determinations on level 3, methodology.
Theoretical Issues in Ergonomics Science
411
. The term knowledge approach is used for defining starting points associated with
Level 2, epistemology.
. The term ‘perception of reality’ or ‘ontological assumptions’ are used for
distinctions at Level 1, the ontology.
4. Qualitative method?
Let us analyse the consequence of taking the dichotomy quantitative–qualitative entered at
the data level and add it to the term method. One example is found in this quote from
Larsson (1994, p. 164, t) which seeks to clarify the significance of qualitative method:
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Qualitative method is about how to characterise something, how to represent it. The word
comes from the Latin qualitas, which means ‘character, state, type’. Qualitative method is
consequently systemised knowledge about how to go about to portraying the character of
something.
The phrase ‘Qualitative method is consequently systemised knowledge about how to go
about portraying the character of something’ (emphasis added) is strange. The part that
says ‘how to go about it’, is the very definition of method, after all. And the part that says
‘to depict the character of something’ denotes that method as qualitative. So the phrase
actually means: ‘Qualitative method is systemised knowledge of qualitative method’, which
of course is a tautology. But that is not all. Knowledge of how to go about data collection
is comprehended by the concept of methodology (Logo: knowledge, learning (about)
méthodos) but can hardly be captured by the term method. So it really says: Qualitative
method is qualitative methodology! This is entirely meaningless.
Qua’litas (Latin; quality) is about the properties, the nature of something. But this
‘something’ relates to the phenomena one is seeking knowledge about. It does not relate to
the method, to the way one goes about collecting data, information or any other empirical
evidence on the characteristics of certain phenomena. The method cannot be qualitative.
Qua’ntitas (Latin; quantity) also refers to properties: properties in the form of, for
example, volume, number and size. We sometimes speak of these as primary properties,
properties of things that are independent of our perception of them. These are unlike the
secondary characteristics (e.g. colour, smell, taste), which are not possessed by the
phenomena themselves but which occur in our perception of something. But again, these
are properties of the phenomenon about which we seek knowledge. Not characteristics of
the method. The way we go about it, the method, cannot have quantity, or size or volume.
The method itself cannot be quantitative.
The dichotomy quantitative–qualitative method is thus an absurdity. Both
qua’litas (quality) and qua’ntitas (quantity) refer to different characteristics of phenomena,
which is what different types of data aim to illuminate. This is thus not the way we go
about collecting – or for that matter analysing – such data. Methods (approaches,
perspectives, etc.) cannot be quantitative or qualitative. Data, however, can be so. Data
reflect, represent, assert or illustrate the qualitative and quantitative characteristics
of phenomena.
5. Analyses cannot be quantitative or qualitative
Sometimes there is hope that the dichotomy quantitative–qualitative could be saved with
respect to what kind of analysis is carried out and that, if so, the question would be about
something more sophisticated than the rather trivial fact that the data can include numbers
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R. Åsberg et al.
or words. For instance, Patel and Davidsson (1994) explain the difference between
quantitative and qualitative research on the basis of what kind of analysis one carries out:
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Somewhat simplified one could say that the labels ‘quantitative’ and ‘qualitative’ refers to how
one chooses to treat and analyse the information collected. By quantitative research one refers
to such research that uses statistical methods to treat and analyse. By qualitative research one
refers to such research that use verbal methods of analysis. (Patel and Davidsson 1994, p. 12, t)
Our position is, of course, that it is not the analytical methods that are verbal, but
rather the format of the data. Analytical methods can neither be quantitative nor
qualitative – only data can. It is better, if at all necessary, to talk about the analysis of
numerical data and analysis of non-numerical data. This is contained in the character of
the data. Within the same study, data can take on the shape of words as well as numbers.
If the quantitative–qualitative distinction is moved to the level where it belongs, the
data level, the essential methodological issues need not be confusing. But if it has already
been assumed that quantitative versus qualitative is an over-arching dichotomy under
which everything else has to be subordinated, it is very likely that an almost endless
rhetoric is maintained – taking lots of pages in methodological handbooks, essays and
dissertations. But it is all about a pseudo choice.
It can also stop when one realises that one ends up in obvious contradictions; that the
arguments surrounding the differences in qualitative and quantitative method are
entangled in absurdities. This is as much an absurdity as a convenient exit, however, a
way out. The quantitative–qualitative argument should be linked to the data level, not to
method. It is data that can be quantitative and qualitative, they can be compiled in the
form of words and in terms of numbers. And indeed, ‘Numbers and words are both needed
if we are to understand the world’. (Miles and Huberman 1994, p. 40).
6. The qualitative–quantitative smokescreen
What if we start at the other end? This leads to contradictions and inconsistencies, which
may prevent a genuine understanding of what the different a priori choices of
epistemological and ontological nature mean. They get obscured by ‘The Gunsmoke in
the quantitative/qualitative battlefield’ (Kvale 1989, p. 110). Hartman (1998) clearly
sets out from a quantitative–qualitative dichotomisation and couples it to different
epistemological starting points, to positivism versus hermeneutics:
Quantitiative studies . . . are based on a positivistic theory of science . . . Qualitative
studies . . . are characterised by the ambition to understand how people experience themselves
and their surroundings. It is a method based on hermeneutics. (Hartman 1998, p. 14, t)
Similarly, when we discuss different ‘principles and beliefs’ regarding ontology,
epistemology and methodology under the label ‘qualitative researchers’ it amounts to
something which ‘may be termed paradigm’:
All qualitative researchers are . . . guided by highly abstract principles . . . These principles
combine beliefs about ontology (What is the nature of reality?) . . . epistemology . . . and
methodology (How do we know the world and gain knowledge of it?). These beliefs shape how
the qualitative researcher sees the world and acts in it . . . The researcher is bound within a
net . . . of epistemological and ontological premises . . . This net may be termed paradigm.
(Denzin and Lincoln 1998, p. 26)
But, of course, ‘these principles’ do not apply exclusively to how a qualitative
researcher looks at and acts in the world, but applies to all researchers. There is no
group, nor a paradigm, of qualitative a priori assumptions and another set of
Theoretical Issues in Ergonomics Science
413
quantitative assumptions. There are different ontological and epistemological a priori
assumptions that connect to the question for in what kind world (ontology) one is looking
for what kind of knowledge (epistemology). But these can not in any meaningful way be
associated with or subordinated by the dichotomy quantitative–qualitative.
Consistent with an English-speaking tradition, Patton (1990, p. 37) claims that there is
a longstanding ongoing epistemological debate on two global paradigms, on one hand a
positivist that uses quantitative methodologies, and, in this case, a phenomenological
paradigm that uses qualitative approaches:
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Philosophers of science and methodologists have been engaged in a long-standing epistemological debate about how best to conduct research. This debate has centered on the relative
value of two fundamentally different and competing inquiry paradigms: (1) logical-positivism,
which uses quantitative and experimental methods to test hypothetical-deductive generalisations, versus (2) phenomenological inquiry, using qualitative and naturalistic approaches to
inductively and holistically understand human experience in context-specific settings.
Even if Patton (1990, p. 38) confesses: ‘I prefer pragmatism to one sided paradigm
allegiance’ he still discusses around a kind of qualitative paradigm and normatively
attributes possibilities such as ‘holistic understanding’, ‘personal contact and insight’, and
‘flexibility’ (Patton 1990, p. 40, f). It seems to be clear that non-positivistic research, which
basically means all other knowledge approaches except positivism, is considered
qualitative research, which means not working with numeric data. And those who were
engaged in that non-positivist research, what methods did they use? Well, they observed,
described and recounted and interpreted. Which is also what positivists do. Positivism per
se has no preference for quantitative data, but rather assumes that the knowable is equal to
the observable. It emphasises empiricism rather than rationalism as the basis for scientific
knowledge, ‘that imagination is subordinated observation’, as the father of positivism
Comte (1979, p. 19) put it in 1844.
7. Conclusion
In the end, the pseudo choice between qualitative and quantitative ‘methods’ may not be
about that supposed choice at all. Instead, debates surrounding it invoke the question of
the presumed scientific status of the ergonomic enterprise. Uncertainty about the
provenance and objectivity of qualitative data seem to be born out of a lack of
epistemological self-confidence of ergonomics as a science (Parasuraman et al. 2008). Not
unlike the historical attempts to make psychology more into a hard science (from Freud to
Watson and beyond), ergonomics may feel that a reliance on qualitative data mars its
progress towards becoming a ‘normal’ science, in essential ways like the natural sciences.
Most fields of scientific enquiry have wanted to emulate the ideal of physical science,
where detached scientific observation and experimentation generate facts that are
objective, time- and observation-independent, and value-free, and where a steady
accumulation of such facts means ever more powerful science. To the question, then,
why ergonomics has not lived up to this ideal, there are at least two possible answers
(Flyvbjerg 2001):
7.1. The pre-paradigmatic answer
Ergonomics is still a young science and there is nothing, in principle, to prevent it from
becoming a ‘normal’ science in the future, other than a softening through too much
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qualitative work. It has not been persuasively demonstrated, after all, that it is impossible
for ergonomics to achieve the rigour and objectivity of the ‘hard’ sciences. It just takes
more time, and more evidence, particularly of the quantitative kind. In the preparadigmatic view, it is hard science that lies at the core of any field’s scientific identity.
Hard science functions as a kind of benchmark against which any other field’s
epistemological confidence gets ranked.
The problem, of course, is that even hard science has become relativised during the past
decades through what has been called the ‘universality of hermeneutics’ (Feyerabend
1993). Hermeneutics, the study of interpretation, is no longer linked only to the study of
humans, but to all sciences. Even natural sciences are now seen as historically conditioned
and human constructed (Wallerstein 1996). They too must constantly re-assess what
constitutes relevant facts, methods and theories, and what counts as ‘nature’.
Interpretation in ergonomics (whether of qualitative or quantitative data) involves the
taking (often implicitly) of a priori ontological positions that get obscured if the debate is
merely cast as a choice between qualitative and quantitative.
7.2. The hermeneutic answer
Giddens (1984) argues that the study of human activity must be based on people’s
situational self-interpretation. Ergonomics is an activity in which humans study humans.
Humans are self-reflecting actors, not objects in the natural world that do not answer
back. For Giddens (1984), this involves a double hermeneutic. First, there are selfinterpretations among those people who are studied in ergonomics research. The second
hermeneutic applies to the human researchers themselves, who are, of course, constituted
in a particular context that offers a particular set of constructs and methods and
techniques. Findings reported in any study, says Giddens (whether based on qualitative or
quantitative data), are only as stable as their interpretations. They have no trans-historic
truths that can progress towards a greater accumulation of facts or ‘science.’
It could be argued that none of this matters. After all, ergonomics is a field born out of
pragmatic concerns, not out of a pre-occupation with ontology or epistemology. As long
as ergonomics is able to produce tangible results, better displays, better work environments, we should perhaps not care about the extent to which it is ‘science,’ by whatever
criteria. But when fundamentally different a priori assumptions are still brought together
under the umbrella of a supposed choice between qualitative or quantitative research,
there is a significant risk that essential and crucial questions are obscured. We might fail to
see the world and its critical problems that need exploring. Instead we concentrate on the
inside of the umbrella and are trapped in a futile rhetoric around a methodical pseudo
question.
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About the authors
Rodney Åsberg was associate Professor at Gothenburg University and is currently involved in
international education and aid projects.
Daniel Hummerdal is PhD candidate at the Centre de recherche sur les Risques et les Crises at Ecole
des Mines de Paris, France.
Sidney Dekker (PhD, 1996, The Ohio State University) is Professor and Director of the Key Centre
for Ethics, Law, Justice and Governance in Brisbane, Australia.