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What do you mean by that

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									The language of research

Part 1 - How can language be a barrier?
The language of research is the currency we use to exchange ideas,
constructs and findings with colleagues and students. It is integral to the
research process. As undergraduates, students will have acquired the basic
terminology of their discipline. But with the transition to postgraduate research,
they are expected to master a more esoteric language.
Once we have entered the research community as fully paid-up members, we
tend to forget that there was a time when we did not know the meaning of the
words we now use so easily. Yet many students find it difficult to acquire and
confidently use this accepted language. Ownership of the terminology seems
to be a key to crossing the threshold of, and being welcomed into, the
research community.
If disability is added to the equation, then the use of complex terminology can
be a real barrier to understanding and to clear, unambiguous communication
between teacher and learner; it can inhibit the development of a professional
partnership between research supervisors and disabled students and even
the progress of the research project.
BSL users
Deaf students whose first language is BSL (British Sign Language) will work
with a BSL/English interpreter, or usually a team of interpreters. It could well
be that the subject-specific words we take for granted do not have equivalents
in BSL. Both interpreters and student need not just to know the word but to
have a clear understanding of its meaning. Only then can it be spoken,
interpreted, comprehended, absorbed and internalised.

In my experience I find that .. terms and various types of concepts can be
extremely difficult to interpret. Mainly this is related to the meaning value
attached to any particular stretch of discourse. This will change according to
the context of the subject.

In many cases this means the supervisor and tutor need to bring the intended
(denotative/connotative) meaning to the surface making it more accessible to
the Deaf and disabled student. A good tutor will provide examples and
analogies to unpack meaning (situate the example in real life). This goes a
long way to supporting the interpreter and student and enhancing the learning
experience. Once a concept or term is understood usually a Deaf student
creates their own sign that can be used. This encapsulates the essence of the
meaning and if embraced by the Deaf Community can become part of the
BSL lexicon.

Interpreting within an education environment requires a specific approach - a
mixture of 'Literal' and 'Free' interpretation has advantages. Clearly students
need access to technical terminology as this is crucial to their future written
work. A literal approach entails fingerspelling the word in question followed by
a free approach - expanding the meaning to give it some focus as it could be
an entirely new concept. This can be extremely challenging given the time


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constraints with interpreting. Supervisors and tutors aware of the interpreter’s
approach would hopefully pace their dialogue to facilitate interpretation.

It's necessary to discuss each participant's communication needs within the
interpreted event. It is very important to provide sufficient preparatory
information to the interpreter so they can prepare - explanations of terms may
also be necessary. This information would also be useful to the Deaf and
disabled student as they can not always access power point presentations
and watch the interpreter at the same time.

Paul Hann, BSL/English interpreter (2005)

Students who lip read
A deaf PhD student who lip reads spoke about the impact of a new
vocabulary which came with their research:

Discussions with my supervisor have been difficult because of the huge
amount of technical and superior language he uses. This is probably a
problem for any PhD student who is starting work in a new field and doesn’t
understand all the technical terms. But for a deaf student with a more limited
vocabulary it can be a huge barrier to their understanding of the project.

I have a very wide vocabulary but people who are high up in academia … will
use long words where I would use short ones. When they are doing this all the
time in every sentence, it can take me ages to realise what they are saying
because I am just not used to these words being used. It is hard to describe,
but this is the problem I have had with my supervisor. He talks like this all the
time; I’m not going to ask him to change the way he talks.
PhD student

Dyslexic students
No two dyslexic students will demonstrate the same responses within a
learning environment. The impact of research on three dyslexic research
students interviewed as part of the research underpinning this programme
was very different. For one student who reads quite slowly, intensive and
rapid reading presented a very real difficulty. For another planning and
organising their research was the barrier. For the third, it was the task of
extensive writing which was the major challenge. That student was unable to
write and their computer is their ‘wheelchair’. In order to use the speech
activated software which enables the student to write, they have had to teach
it the language of their research. To do that they have had to comprehend
fully the meaning of that language.

For more information on working with deaf students, go to:
http://www.uclan.ac.uk/student_services/accentre/dld/guidelines/deafstudents/
language/index.htm

You will find more information about working with dyslexic students at:




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http://www.campus.manchester.ac.uk/disability/informationforstaff/workingwith
disabledstudents/supportingstudentswithadisability/practicalissues/dyslexiaoth
erspld/
______________________________________________________________

Part 2 - Demystifying language
In the introduction to his book ‘Demystifying Postgraduate Research’
(University of Birmingham Press 2001) Jonathan Grix writes:

‘If you command the basic vocabulary of generic research, you are far more
likely to choose the correct theories, concepts or methods to use in your work.
By grasping the core tools used in research, much of the mystery that can
surround it begins to disappear. …..
Time is not a guarantee for good scholarship, but knowledge of the ‘nuts and
bolts’ that make it up can go a long way to ensuring that the tools of research
are used properly. If you have the right tools and you know how to employ
them, the research process becomes a great deal easier and quicker.’

It will benefit all research students to have the appropriate toolkit of language
and concepts from the beginning of their research. Indeed it is vital they are
able to assemble their toolkit before their research begins. If disabled students
experience additional barriers to managing research language, then there is
even more reason for simplifying the process.
Clear, unambiguous explanations or definitions of research terms are
essential ‘nuts and bolts’. As Jonathan Grix states: ‘Fear of the unknown, the
esoteric and the complex only hinders progress.’
It may be that we need to ask ourselves:
   •   Do we make assumptions that all students will know before they start
       key terms relating to the research process?
   •   Do we check out that students understand those terms?
   •   Do we make clear that students can ask us with confidence to explain
       what we mean?
   •   Do we make it possible for the student to acquire key terms before they
       embark on planning their research?
Below is a glossary of generic research terms with plain English definitions. It
is by no means a definitive glossary but it may provide a framework for
starting to demystify the language of research for students. A dyslexic student
coming to the end of a Masters degree by research who saw a first draft of the
glossary commented that they had never before understood the difference
before between qualitative and quantitative research.




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                  GENERAL RESEARCH TERMINOLOGY
Abstract
A summary of a paper usually 100 to 500 words which describes the most
important aspects of the study including: problem investigated, subjects and
instruments involved, design and methods, main results.
Applied research
Research undertaken with the intention of applying the results to an identified
problem; the term often implies a commercial/practice problem.
Bias
Any influence that may distort the results of a research study and lead to error;
the loss of balance and accuracy in the use of research methods.
Biographical research
A narrative approach to research which is primarily qualitative, and includes
gathering and using data in the form of diaries, stories and life histories.
Case study
The presentation of data about selected settings, persons, groups or events.
The data can have been gathered using a variety of different research
methods ( e.g. questionnaire, observation, historical analysis). It is mainly
descriptive and analytical, and is usually based on qualitative data, though
statistics such as survey findings may be included.
Causal relationship
A relationship between variables where movements in one or more variable(s)
are held to cause changes in the other(s).
Coded data
The data are put into groups or categories, such as age groups, and each
category is given a code number. Data are usually coded for convenience,
speed, and handling and to enable statistical analysis.
Constant
A factor identified as relating to the research subject which has the same
value and does not change over time or space.
Construct
A concept developed (constructed) for describing relations among or between
phenomena or for other research purposes.
Controls
Processes used to make uniform or constant the conditions for carrying out an
investigation.
Control group
In experimental research, the group or item which does not receive the
treatment or intervention under investigation and is used to compare
outcomes with the one which does.




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Correlation
The extent to which two or more factors vary in relationship to one another;
the extent of association between two or more variables.

Correlation coefficient
A measure of the degree of relationship between two variables. It usually lies
between +1 (showing a perfect positive relationship), 0 (showing no
relationship between two variables) to -1.0 (showing a perfect negative
relationship).

Critiquing
Using the same method as a literature review, the analysis of the content and
method of a paper or piece of research.

Cross-tabulating
The process of analysing data according to one or more key variables. It is
also known as cross-referencing.

Data analysis
A systematic analysis of data, manually or electronically, which can range
from statistical to textual analysis.

Data set
A collection of related data items, such as the answers given by all
respondents to all the questions in a survey.

Deductive research
Research that sets out with clear assumptions or previous knowledge to
understand a particular problem or to find an answer to a problem (theory-
driven research).

Dependent variable
In a research project, usually in an experimental or quasi-experimental
project, it is the variable which is thought to be determined or influenced by
the others.

Determinism
The belief that everything is caused by specified factors in a predictable way
rather than by chance. It is a key assumption in the positivist paradigm
which assumes that ultimately you can explain everything logically.

Empirical research
Research that is the collection and analysis of data which might include, for
example, surveys and experiments.

Epistemology
Theories of knowledge which may underpin academic disciplines, particularly
relating to their methods and validation.




                                                                                 5
Experimental group
In experimental conditions it is common to test the validity of a cause/effect
relationship by having two groups of research subjects, an experimental group
and a control group. In the experimental group the causal (independent)
variable is present: in the control group it is explicitly excluded.

Filter
When only a section of the total sample are required to answer the question.

Frequency tables
A set of data which provides a count of the number of occasions on which a
particular answer has been given across all those respondents who answered
the question.

Generalisability
The extent to which results from a sample can be generalised according to
the outcomes of statistical tests of significance.

Grounded theory
Mainly in qualitative research, an approach in which evidence is gathered on
a topic and then the researcher sees what theoretical propositions the
evidence will support. This is described as an inductive process, one in
which the theory that arises is 'grounded' in the evidence.

Hypothesis
A proposition which research sets out to prove or disprove: ‘experimental’
where the hypothesis is a positive statement, or 'null' where the statement
contains a negative.

Hypothesis test
A formal test, using probability and sampling distributions to decide which of
two or more conflicting hypotheses should be accepted. Also referred to as a
significance test.

Independent variable
A variable that the researcher believes precedes, influences or predicts the
dependent variable.

Inductive reasoning
A logical process of reasoning used to develop more general rules from
specific observations; it moves from the specific to the more generalised.

Inferential statistics
They allow a researcher to make inferences about the probability that
relationships observed in a sample are likely to occur in the wider population
from which the sample was drawn.

Literature review
Often one of the first steps in the research process, it is a review of the
literature on and around the subject of enquiry. Its main purposes are to avoid



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duplication, to identify gaps in research and to place the researcher’s
approach within the work and approaches of others.

Longitudinal research
Research which is repeated on several occasions over a period of time, as far
as possible replicating the chosen methodology and sample each time. The
key aim of such research is to monitor changes over time.

Macro
A level of analysis focussing on countries, systems, institutions, structures
and organisations as opposed to micro.

Mean
The arithmetic average of a set of data in which the values of all observations
are added together and divided by the number of observations.

Median
The middle value of a rank-ordered data set; a measure of the central
tendency.

Meta-analysis
A statistical technique for combining and integrating the data drawn from a
number of experimental studies undertaken on a specific topic; an analysis of
a range of papers for a new or different attribute.

Micro
A level of analysis which includes the study of individuals as opposed to
macro.

Nonsignificant result
The result of a statistical test which indicates a high probability that the
outcome of an experimental research study could have happened through
chance, rather than as a result of the outcome of a specified process.

Operational definition
The procedures used to observe or measure a specific concept.

Operationalise
To turn a concept into a variable which can be measured in fieldwork or in the
gathering of information.

Paradigm
A worldview based on a set of values and assumptions that are shared by a
particular academic community which guides their approach to research.

Peer review
A process in which research studies are examined by an independent panel
of researchers to open the study to examination, criticism, review and
replication by peer investigators.



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Population
A well-defined group or set that has particular specified properties.

Positive correlation
A relationship between two variables where higher values on one or more
variables tend to be associated with higher values on the other variable(s).

Positivism/positive approach
A principle in the philosophy of science that mainly says that science can only
deal with observable things. The positivist aims to build general laws or
theories which express relationships between phenomena. Observation and
experiment will then show whether the phenomena fit the theory.

p value
p is the symbol for the probability associated with the result of a test of the
null hypothesis. If the p value is less than or equal to the stated
significance level (often set at 5% (p < 0.05) or 1% (p < 0.01) the conclusion
is that the results are unlikely to have occurred by chance. The results are
said to be statistically significant. If the p value is greater than the
significance level, the conclusion is that the results are likely to have occurred
by chance. The results are said to be nonsignificant.

Primary/secondary sources
Primary sources are original firsthand records or materials relating to an event
or happening. They may include, for example, official minutes of meetings,
diaries, verbatim transcripts of interviews, completed questionnaires or
records of the results of experiments. Secondary sources are accounts based
upon these, which usually offer an interpretation, commentary, analysis, or re-
statement of the primary sources. They can include, for example, books,
journal articles, and conference papers.

Pure
Can be used in the same way as 'basic research'; sometimes it implies an
emphasis on what is methodologically correct with minimal compromise with
practical issues.

Qualitative data
Information gathered in narrative, non-numerical form e.g. transcript of an
interview.

Quantitative data
Information gathered in numerical form.

Quasi-experimental
A type of experimental design where random assignment to groups is not
used, but where there are certain methods of control and the independent
variable(s) is/are manipulated.

Reliability
The extent to which the same result will be repeated/achieved by using the
same measure.


                                                                                 8
Research methodology
Approaches to systematic inquiry developed within a particular paradigm with
related epistemological assumptions.

Research methods
Specific procedures used to gather and analyse research data.

‘Soft’ data
Data such as people's ideas and opinions. A characteristic of qualitative
research.

Standard deviation
A descriptive statistic used to measure the average degree of variability
within a set of scores.

Statistical probability
How far it is possible to draw an inference from a sample and generalise it to
a wider population.

Statistical significance
Tests used to estimate the likelihood that the finding in a sample is true of the
population from which the sample is derived and not due to chance.

Systematic review
A summary of relevant literature that uses clear methods and criteria to do a
thorough literature search and critical appraisal of individual studies; it uses
appropriate statistical techniques to combine these studies (studies validated
by meeting the specified criteria).

Tabulation
See frequency tables for definition

Textual analysis
It involves working on a text in depth, looking for keywords and concepts and
making links between them. The term also extends to literature reviewing.
Increasingly much textual analysis is done using computer programmes.
Triangulation
A multi-method or pluralistic approach, using different methods in order to
focus on the research topic from different viewpoints and to produce a multi-
faceted set of data. It is also used to check the validity of findings from any
one method.
Typology
A classificatory system with which the researcher categorises data;
frameworks with which to organise observations.
Validity
The extent to which research findings can be said to be accurate and reliable;
the degree to which the conclusions are justified. Internal validity is the extent




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to which researchers can show that they have evidence for the statements
they make; external validity refers to a study’s generalisability.

Variable
A factor identified as relating to the research topic which changes over space
and time.

Variance
A measure of variability/spread, calculated by squaring the value of the
standard deviation.

Viva
An oral examination for PhD and some MPhil students with internal and
external examiners to decide whether the thesis has reached the required
standard.
_____________________________________________________________




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Part 3 - Subject-specific language
While it is essential that all students have a good understanding of generic
terms and concepts, there is a need to create opportunities for subject specific
language acquisition.

There is an expectation that everyone will grasp the meaning of research
language immediately. From day one, lecturers talk in the language of
research and it has been assumed that I will understand without any
guidance. And I didn't.

Masters by research student with dyslexia

Deaf and disabled students can and do find ways of coping.

I have used the same two interpreters for three years really so they know
what I’m talking about. They’ve been through the process with me. I feel that’s
important.

PhD student who is deaf

Some are assertive when they do not understand.

My problem with studying is .. mainly due to the language barrier which exists
for those deaf people with a smaller vocabulary than hearing people. Making
people aware when I mishear or don’t understand what they are saying is
usually the only way to get past this problem, along with noting words and
phrases down and learning them for future reference.

PhD student who is deaf

Students also seek assistance from other sources.

( I had a)big issue round the language of research. Especially in our first year,
this is something we talked about quite a lot. And again that was nice because
5 or 6 of us first year students (shared an office) and this is one we all felt
completely lost with.
PhD student with dyslexia


.. It has been better recently. ..I’ve been lucky in that I get an award from a ..
company. There are two youngish people … who I meet up with in this
company once a month or so. They go through my project with me because it
is in the company’s interest and they have given me ideas and helped me to
develop research skills and my project was developed with their help. Having
discussed it with them I have gradually built up some more technical
knowledge and language so can understand my supervisor a bit more now.

PhD student who is deaf




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But there may be many who struggle to grasp technical words because we
sometimes fail to define what we mean and do not always make it possible for
students to ask. To ensure that there are not students slipping through the net,
it would be a good idea to put together a subject specific glossary, to make it
available electronically and to signpost students to it. Here are some
examples of subject glossaries on the Internet, including subject glossaries
with plain English definitions translated into BSL (British Sign Language):

   •   The BioTech Biotechnology Dictionary:
       http://biotech.icmb.utexas.edu/search/dict-search.html

   •   Statistics glossary from Lancaster University
       www.cas.lancs.ac.uk/glossary_v1.1/main.html

   •   Economics glossary
       http://econterms.com/econtent.html

   •   Glossary of sociological terms
       www.soci.canterbury.ac.nz/resources/glossary/index.shtml

   •   Glossary on Stephen Hawking’s website of terminology in theoretical
       physics: cosmology
       www.hawking.org.uk/activity/acindex.html

   •   Glossary of art and design terms in British Sign Language, but also
       with plain English definitions
       http://artsigns.ac.uk

   •   Glossary of science terms in British Sign Language, including
       environmental science
       http://www.sciencesigns.ac.uk/home_glossary.asp

   •   Glossary of engineering and built environment terms in British Sign
       Language (and general terms too)
       http://www.engineeringsigns.ac.uk

   •   Glossary of medical terms
       http://cancerweb.ncl.ac.uk/omd/




Section 7 The language of research (Amended January 2007) These resources are outcomes
of the Premia project based at Newcastle University (2003 – 06) and funded by HEFCE.




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