23.5071, Review: Applied Linguistics; Ling. & Literature: Van Peer, Hakemulder & Zyngier (2012)

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LINGUIST List: Vol-23-5071. Tue Dec 04 2012. ISSN: 1069 - 4875.

Subject: 23.5071, Review: Applied Linguistics; Ling. & Literature: Van Peer, Hakemulder & Zyngier (2012)

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Date: Tue, 04 Dec 2012 16:36:50
From: Leonardo Campillos Llanos [leonardo.campillos at gmail.com]
Subject: Scientific Methods for the Humanities

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Book announced at http://linguistlist.org/issues/23/23-2645.html

Author: Willie van  Peer
Author: Frank  Hakemulder
Author: Sonia  Zyngier
Title: Scientific Methods for the Humanities
Series Title: Linguistic Approaches to Literature   13
Publisher: John Benjamins
Year: 2012

Reviewer: Leonardo Campillos Llanos, Universidad Autónoma de Madrid

SUMMARY

‘Scientific Methods for the Humanities’ is written by three experts with a
wide range of publications and experience in the use of empirical research in
Art, Media or Literature -- they are founding members of the International
Society for the Empirical Study of Literature (IGEL) and organize REDES
(Research for the Development of Empirical Studies) Seminars. Their book aims
at introducing readers from a Humanities background to the empirical methods
used in scientific research, and presenting a re-elaboration of a previous
volume (Van Peer et al., 2007). In that work, the authors already began
swimming against the tide in the Humanities, where, as they state,
“departments do not have a tradition of empirical research” (p. xxi).

Chapter 1 presents the authors’ approach to carrying out research in the
Humanities by applying a scientific methodology. In keeping with Charles Percy
Snow’s concept of the Third Culture (1959/1993), the authors propose a
contribution that “bridges the gap between the Humanities and the Natural
Sciences” (p. 7). In defense of this paradigm, Wundt’s curve -- described by
German psychologist Wilhelm Wundt (1832-1920) -- is explained. The Wundt’s
curve is a curvilinear shape which represents the increase of the pleasant
feeling aroused by any stimulus as a function of the intensity of the
stimulus; this feeling of ‘pleasantness’ gradually increases “but only up to
certain point, after which the pleasant feeling gradually diminishes”, thus
becoming “quite unpleasant” (p. 9). The Canadian psychologist Daniel E.
Berlyne adapted this curve to scientifically study the aesthetic experience.
Finally, to exemplify that the use of a scientific methodology may confirm or
reject speculative or deeply rooted ideas among scholars in the Humanities,
the authors quote two pieces of this type of research regarding
Psychoanalytical readings of Literature and Narratology.

Chapter 2 explains basic insights from the philosophy of science. Aristotle’s
theory of motion and Galileo’s famous experiment, which refuted it
empirically, are examples of how theories are replaced by new ones which are
more productive and free of internal contradictions. Science is continually
exerting a constant, systematic and ubiquitous critique of scientific theories
because scientific progress is based on learning from previous mistakes. Karl
Popper’s principle of falsification (1934) is an elaboration of this critical
method; empirical verification of a theory is not enough to accept it (as
Positivism advocated) because “verification is not fail-safe” (p. 40). As any
theory is just an approximation of reality, modesty is another requirement for
science. The chapter ends by explaining research on the formal and stylistic
similarities between Mark’s, Luke’s and Matthew’s gospels, and the hypotheses
about their sources.

Chapter 3 addresses research methodologies. One of the main choices deals with
the preference of quantitative or qualitative research. Qualitative methods
are recommended when addressing a topic that has scarcely been researched due
to the fact that it is more suitable for finding new insights. However, much
qualitative research lacks of rigor. On the contrary, quantitative methods are
more appropriate in cases where scientific studies about a topic abound, in
order to test hypotheses which have already been stated. Besides both types of
methods, three types of research are differentiated: explanatory, exploratory,
and descriptive. Subsequently, a plan for research is explained: consideration
of the problem to investigate; evaluation of the feasibility of the study;
literature search; construction of the conceptual model; choice of the
research method; and setting up variables and ways to measure them. Specific
suggestions about searching for literature in databases (e.g. PsycInfo) are
provided and the need for an evaluation and a critical discussion of these
sources is addressed.

Chapter 4 exposes methods of data collection: observation research (i.e.
participatory research or naturalistic observations), think-aloud protocols,
diaries, interviews (which are one of the richest sources of data), focus
groups, experiments, content analysis, and surveys (which allow addressing the
same questions with a large population).

Chapter 5 explains how to construct a questionnaire, which can include open or
closed questions. Levels of measurement are subsequently addressed: nominal,
ordinal, interval, and ratio. Every level of measurement is related to the
main types of questions which are discussed: checklist, multiple choice,
graphic rating scale, itemized rating scale, rank-order rating scale,
constant-sum rating scale, fractionation rating scale, Likert scale, and
semantic differential scales. The authors put forward some suggestions as to
how to formulate a question and how to design a questionnaire, as well as
other issues such as the procedure, the layout and the instructions of the
questionnaire.

Chapter 6 introduces key concepts about experiments, the aim of which is to
observe the effect of the independent on the dependent variable. In contrast
to subject variables (which cannot be completely controlled), independent
variables can be manipulated, and therefore, they make it possible to
generalize results. Following this, two types of experimental designs are
described: between-subject designs (comparisons of groups) and within-subject
designs (or repeated measures, comparisons of two or more measurements within
each individual case). Besides the classical pre-test/post-test control group
design, other experiments use a factorial design (e.g. two-way design). The
chapter explains the use of delayed (or post-post) tests (to confirm long term
effects of a treatment) and control groups (as a baseline measure), as well as
threats to the internal and to external validity of experiments when
estimating to what degree the conclusions are valid.
 
Chapter 7 introduces the SPSS program for statistical analyses, while the
basics of descriptive statistics, along with fundamental concepts such as
normal distributions of data and effect size, are explained in Chapter 8.
Measures of central tendency (e.g. mean, mode, and median) show group
tendencies, whereas measures of dispersion (e.g. the range, standard
deviation, and variance) describe the bandwidth of the observations in
relation to the average. The chapter illustrates how to generate all these
measures with SPSS and how to represent them in bar charts, line graphs and
boxplots.

Chapters 9 through 11 review some principles of inferential statistics: the
notion of significance level; the concepts of the ‘null’ hypothesis (Ho) and
the alternative hypothesis (Ha); the risk of observational errors; and the
notion of correlation (a similarity between two variables, which is not,
nonetheless, a synonym of causality). The chapter explains how to create
scatterplots with SPSS (in order to observe the data before a correlation is
calculated) as well as how to calculate them in parametric and non-parametric
tests. It concludes by addressing regression analysis, a sophisticated
technique used to figure out the relationship between several variables and
how much each individual variable predicts the value of another.

Some of the tests used in inferential statistics are introduced in Chapter 10.
A decision flowchart and a summary table help the reader to choose the correct
test depending on whether the data follow a normal distribution (parametric
tests) or not (non-parametric tests). To know whether the scores are normally
distributed, the Kolmogorov-Smirnov test can be used. This, and the following
tests (and the way to perform them in SPSS) are explained: first, a parametric
test such as the t-test; and second, non-parametric tests such as the Wilcoxon
test, the Mann Whitney (‘U-test’), the Kruskal-Wallis test, the Friedman test,
and the Chi square test (which can be used with data at all levels of
measurement).

Chapter 11 discusses Analysis of Variance (ANOVA) tests, which compare the
variance between groups with the variance within each group. The chapter
specifies the requirements of the data to perform an ANOVA and introduces the
Bonferroni correction (post hoc) test. If more than one independent variable
needs to be considered, the procedure to follow is the General Lineal Model
(GLM), of which there are three forms: Univariate ANOVA, Multivariate ANOVA
(MANOVA), and Repeated Measures. The conditions under which tests are
performed and the instructions to calculate them in SPSS are explained step by
step with sample tables and screenshots.

Chapter 12 addresses ways to communicate results. As to oral presentations,
the authors put forward recommendations regarding points such as the
submission of an abstract, how to introduce oneself, the timing, how to speak
to the audience, the way to deal with comments during discussion time, or the
use of media (e.g. PowerPoint presentations). As far as written presentations
are concerned, the chapter tackles issues such as the choice of a journal and
the structure of a paper (i.e. title, keywords, abstract, introduction,
explanation of the methods and presentation of results, and discussion).
Stylistic suggestions concerning scientific writing and citation guidelines
are also provided. Finally, the chapter includes some useful tips for
preparing a poster for a poster session.

EVALUATION

‘Scientific Methods for the Humanities’ is an honest title that deserves the
attention of scholars in the liberal arts. After turning the last page of the
Epilogue, the reader has undoubtedly gained such a wealth of knowledge on
research methods and techniques that he/she may no longer approach the study
of the Humanities with the same attitude. Covering the main contents from
research methodologies to experimental tests, the volume strikes a good
balance between theory and applied methods in research. The visual display of
the data (in graphs and tables) and the screenshots of the program used in the
tests are clean and easy to understand. Furthermore, the structure of the book
is very pedagogical, as topics and methods of the research methodologies are
explained gradually, from the easier to the more difficult. Indeed, two
chapters (the Interlude before Chapter 2 and the Epilogue) are written in
dialogue form, as was done in the Renaissance Humanism tradition. With this
didactical resource, the authors pose and answer questions which students or
scholars in the Humanities tend to form when they are guided toward an
empirical methodology. Also, some misconceptions about the empirical research
of culture are rejected: among others, the supposed need of a sophisticated
theoretical framework and ‘real’ experiments to be measured, or the
impossibility of dealing with a-theoretical issues that are subjective in
nature.

Surprisingly, the book does not include many examples of research performed in
a field related to the Humanities such as language learning/teaching or
language acquisition. This is mainly due to the authors’ background in Arts,
Media and Literature. However, it is also true that it may not be necessary to
go beyond the scope of these disciplines to achieve the aim of this work (i.e.
the understanding of scientific approaches and methodologies and their
application to a non-scientific area). Specifically for language disciplines,
there are volumes already devoted to research methods in Linguistics and
Second Language Acquisition -- such as Larsen-Freeman & Long (1991), Mackey &
Gass (2005), Dörnyei (2007) or Johnson (2008) -- as well as other books on
statistics for the study of language such as Oakes (1998), Baayen (2008),
Gries (2010) or Herrera-Soler et al. (2011). The authors stick to providing
further references on certain topics in their corresponding chapters,
considering that the aim of the book is not “a complete course in statistics”
(p. xxii) nor a manual for using SPSS, for which purposes there are
comprehensive volumes for the Social Sciences, such as Miller et al. (2002) or
Howell (2011).

Although I agree with the authors’ statement that “finding a good question or
formulating a problem (…) is even a difficult task for experienced
researchers” (p. 313), the tests provided are illustrated with experiments or
data related to research that could be performed in Arts or Humanities
disciplines. Indeed, in order to practice the contents explained, the book is
accompanied by a set of self-study materials (multiple choice questions and
simulation of exercises) that can be found on the publisher’s web site. These
complementary materials are undoubtedly an advantage for the reader. However,
there is a disadvantage in the way they are made available, since they are
only published on the Internet, and thus, it may not be always possible for
the reader to use them (e.g. if there is a lack of connection service or if
the web site is temporarily unavailable). A good improvement for a following
edition would be to include them in the volume or even on a CD attached to the
book. Thus, what is already a worthy reference book could be used as a
textbook for a course in a Humanities program. In any case, this practical
approach is very positive, given that “learning by doing is a better way of
learning”, as the authors state (p. 47). In fact, all the materials from the
book have been previously tested with students.

Overall, despite the weaknesses pointed out above, the authors’ purpose for
the book is mainly achieved. Written in a very accessible style, the reading
of the volume is fluid and stimulating, even in the sections devoted to
statistical tests. In my opinion, some of the chapters -- especially, Chapter
12 (Communicating Results) -- should be a must-read for students who are being
trained in a post-graduate degree program in the Humanities. Authors share
very useful tips and some of their personal know-how regarding methods for
performing an investigation and disseminating results. Moreover, they trying
to erase threats and misconceptions about what the practice of research is.
This inspiring, non-elitist approach for introducing scientific methods to
students in the Humanities is the main merit of the volume.

REFERENCES

Baayen, R. Harald. (2008). Analyzing Linguistic Data: A Practical Introduction
to Statistics using R. Cambridge: Cambridge University Press.

Dörnyei, Zoltan. (2007). Research methods in Applied Linguistics. Oxford:
Oxford University Press.

Gries, Stefan Th. (2010). Statistics for Linguistics with R: A Practical
Introduction. Berlin: Mouton de Gruyter.

Herrera-Soler, Honesto, Rosario Martínez Arias & Marian Amengual Pizarro.
(2011). Estadística aplicada a la investigación lingüística. Madrid: EOS.

Howell, David C. (2011). Fundamental Statistics for the Behavioral Sciences.
7th edition. Belmont, CA: Wadsworth Cengage Learning.

Johnson, Keith. (2008). Quantitative Methods In Linguistics. Malden:
Wiley-Blackwell.
 
Larsen-Freeman, Diane, & Michael H. Long. (1991). An introduction to second
language acquisition research. London: Longman.

Mackey, Alison & Susan Gass. (2005). Second Language Research: Methodology and
Design. London/N.J.: Lawrence Erlbaum Associates.

Miller, Robert L., Ciaran Acton, Deirdre A. Fullerton & John Maltby. (2002).
SPSS for Social Scientists. Hampshire/New York: Palgrave Macmillan.

Oakes, Michael. (1998). Statistics for corpus linguistics. Edinburgh:
Edinburgh University Press.

Peer, Willie van, Frank Hakemulder & Zyngier, Sonia. (2007). Muses and
measures. Empirical research methods for the humanities. Cambridge: Cambridge
Scholars Press.

Popper, Karl. (1934). The Logic of Scientific Discovery. New York: Routledge.

Snow, Charles Percy. (1959/1993). The Two Cultures. Cambridge: Cambridge
University Press.


About the Reviewer:
Leonardo Campillos Llanos is a PhD student at the Linguistics and Modern
Languages Department at Universidad Autónoma de Madrid (Spain). His interests
are corpus linguistics, Spanish as a second language acquisition and the
application of computers in the Humanities. He has attended international
conferences (LREC, Learner Corpus Research, and Corpus Linguistics), and he is
co-author of ‘Textos de español oral’, a corpus-based book for practicing the
listening comprehension skills in Spanish.








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