Compiled by: Mona Osman & Kariman Kira
Page 1 of 4
RESEARCH PAPER WRITING STUDY GUIDE
Empirical research:

Empirical means inquiry that requires actually observing and recording
entities, events or relationships.

Reports that only involve thinking about the world even if this thinking is
systematic and precise do not qualify as empirical research.

Empirical research starts with a theory, which the researcher develops to try
to predict what happens in the real world. The purpose of the research is to
test the theory and possibly refine it.
Secondary sources: summarize other people’s research rather than provide 1st
hand research.
e.g. Position paper: The writer proposes an opinion or hypotheses based on
previous research, but further primary research is needed to support his contention.
Again this does not substitute for reading primary sources ourselves.
Literature review: Summarizes all primary sources on a given topic trying to make
sense of them & trying to point at areas that need further research. A literature
review does not substitute for a primary source reading because the writer of review
writes only what is relevant to his search and he may be biased.
Books: Provide key concepts, theories, and foundations and do not substitute for
primary sources.
Preliminary sources: are publications or CD ROMs that lead us to primary sources
(indexes and abstracts databases that are organized based on keywords). We use
Keywords from our research questions to guide our library search. Nowadays, most
searches are computerized.
Primary sources: first hand research. Derives its weight from being published,
refereed (peer – reviewed), and better yet blind-refereed.
Use titles & abstracts to differentiate between primary and secondary sources.
Examples P. 34 – 35 of Perry.
Parts of a primary research paper:
Title: Should reflect the research purpose and/or questions/hypotheses as well as
the type of research (primary, literature review, or position paper). It also needs to
be succinct.
The abstract: summarizes: 1) purpose, 2) source of data/ participants, 3) the
method used, 4) the results in general, 5) their interpretation. Does not substitute
for reading the study itself.
Compiled by: Mona Osman & Kariman Kira
Page 2 of 4
Introduction: reflects: 1) the purpose of the study, 2) its significances, 3) the
rationale behind needing this study which we tend to call review of the literature
though it is not a comprehensive one as in a proposal or a study classified as a
review of the literature; It rather gives the logic behind needing to do the study at
hand supported by examples of previous primary research, 4) definitions of variables
and constructs, and 5) the research questions/ hypotheses.
Research questions: the core & the beginning of any research process
Types: * what questions (correlation) (What phenomena are of importance, in
what context do these phenomena occur, and what important relationships exist
between phenomena?)
* Why questions (causation) (Why do these phenomena occur, and why do
people differ on certain traits?)
* investigating relation does not imply causation. Not because I find a strong
statistical correlation between eating ice-cream and increase in crime rate, can I say
that if I prohibit ice-cream sales crime rates will drop because the reason (causation)
behind both may be different (high temp that make people thirsty and more easily
irritated). Therefore, correlation is not causation.
Sources of research questions: - practical problems (personal experience
and/or observation)
- secondary sources (literature reviews end in suggesting
research)
- primary resources (to apply on a different population, and/or
limitations & recommendations for further research in the
conclusion section)
A hypothesis is a proposed solution to a research question based on theory or on
previous primary research that needs to be tested.
The constructs are the key terms in the research questions and are defined by
adopting or by adapting a definition by an authority in the field, or operationally by
using an instrument to measure them.
The operational definition is the way a term is defined in the study at hand for
research purposes.
Variables are the things that vary in a study. If they do not change, they are not
variables. They have to be mentioned in the research questions/ hypotheses, and
clearly defined in the study. There are several types. We focus on the most
important two:
Independent variables are variables of influence; they affect the change in the
dependent variables.
Dependent variables are the variables measured by our instruments and
influenced by the change in the independent one.
Methodology: reflects the sample, the research design, the data collection
procedures/ the instruments used, and the procedures followed.
The sample: the participants or the objects used in the study. The sample needs to
be randomly selected and representative (reflecting all the characteristics of the
Compiled by: Mona Osman & Kariman Kira
Page 3 of 4
target population) in order to be able to generalize the findings to the target
population. The sample size needs to be reasonable in order to be able to generalize.
The research design varies according to the research questions.
There are three continua for research designs:
1) Basic – Applied:
Basic: Theoretical, dealing with foundation values underlying the practical
applications.
Applied: Practical, directly applicable
2) Qualitative – Quantitative:
Quantitative: uses statistics to generalize from a sample to a population
Qualitative: uses observation and verbal description deeply and personally
involving the researcher and relies on expert analysis.
3) Exploratory – Confirmatory:
Exploratory: No hypothesis, trying to find answers to the research questions.
Confirmatory: involves an experiment to confirm a hypotheses
Most studies are not purely one or the other, but are more tilted towards
one side of the 3 continua.
More on quantitative/qualitative continua
Quantitative research:



The aim of quantitative research is to determine how one thing (variable)
affects another in a population.
Quantitative research is all about quantifying the relationships between
variables. Quantitative research methods collect numerical data (data in the
form of numbers) and analyze it using statistical methods.
Quantitative methods include experiments where researchers apply a
treatment and measure results before and/or after it. Another method is
surveys.
Qualitative research:

The aim of qualitative research is to provide a verbal description or
explanation of the studied phenomenon.

Qualitative research methods collect qualitative data in the form of
text, images, sounds drawn from observations, interviews and documentary
evidence, and analyse it using qualitative data analysis methods.

Qualitative data analysis methods include case studies in which
researchers conduct observations in a real world setting e.g. a software
development project. The objective is for the researcher to immerse himself
in the situation and gain a holistic understanding of the phenomenon in its
natural setting. Another qualitative research method is action research where
a researcher applies a research idea in practice and evaluates results.
Data Analysis
Quantitative data analysis: use of statistical methods to identify patterns and
relationships in the data.
Compiled by: Mona Osman & Kariman Kira
Page 4 of 4
Qualitative data analysis: analysis is more subjective and relies heavily on the
researcher’s knowledge and expertise to identify patterns, extract themes and make
generalizations
The instruments used are the data gathering procedures (surveys, tests,
observation).
Triangulation: is using more than one way of collecting data to increase the validity
of the results.
The material used is not the instruments but the stimulus used to prompt
response.
Validity is the degree to which a measurement/observational procedure accurately
captures data and is used correctly.
Reliability is the degree to which a data-gathering procedure produces consistent
results.
Procedures used details how the study was executed.
The results are expressed statistically for quantitative studies and verbally for
qualitative (observational) studies.
The statistical significance of quantitative data depends on the p value which
needs to be less than the .05 level. If the p level is higher than that it means the
chance of error, or in other words, of the results happening by coincidence or for any
reason other than that presented in the study is more than 5%. If the error chance is
higher than 5%, the results are statistically insignificant even if the researcher claims
otherwise.
Statistical significance p-value




The statistical significance of a result is the probability that the observed
relationship (e.g., between variables) or a difference (e.g., between means)
in a sample occurred by pure chance ("luck of the draw"), and that in the
population from which the sample was drawn, no such relationship or
differences exist.
The higher the p-value, the less we can believe that the observed relation
between variables in the sample is a reliable indicator of the relation between
the respective variables in the population.
Specifically, the p-value represents the probability of error that is involved in
accepting our observed result as valid, that is, as "representative of the
population." In many areas of research, the p-value of .05 is customarily
treated as a "border-line acceptable" error level.
Results that are significant at the p
.01 level are commonly considered
statistically significant, and p
.005 or p
.001 levels are often called
"highly" significant.
The conclusion relates the findings to the research questions/ hypotheses, as well
as to previous research findings. It gives the practical implications of the findings
Compiled by: Mona Osman & Kariman Kira
Page 5 of 4
(more in session 2), the limitations (weaknesses) of the study, its strengths, and
suggestions for future research.
In session 1 statistical significance was highlighted. In session 2 practical
significance is important.
It may be statistically significant that when a school pays 50,000 $ to buy a new
attendance software, students attendance will improve by 2% (at the p <.0001
level), but is it practical to pay 50,000 $ to increase students attendance by 2% not
20% or 30%.
You have to have both types of significance for results to be of any use.
Reference List
Adapted from
Perry, F.L. (2005). Research in Applied Linguistics: Becoming a discerning consumer. NJ: Lawrence
Erlbaum Associates.
Borg & Gall (1989) Educational research. New York: Longman.
Locke, L; Silverman, S; & Spirduso, W (1998) Reading and Understanding Research