Research-Problems-and-Variables PowerPoint

Research
Problems
And
Variables

Problem Conceptualization
A research always starts with a
research problem. A major problem is
usually stated clearly, followed by
specific questions that need to be
answered by the research. Research
takes a great deal of time and energy
and one must make sure that the area
chosen is of interest

Sources of Research Problem
There are many possible sources for a research
problem. Personal experiences and first-hand
knowledge can be the catalyst for starting research
(researcher’s specialization). Often, the curiosity
and creative ideas of the researcher helps in
formulating the research problem. In the academic
setting, one might look for a research question that
reflects the next step in the research process. Most
of these can be found in recommendations from
theses, dissertations, and published journals

Considerations in selecting a research
problem
When selecting a research problem or topic
there are a number of considerations to keep
in mind which help ensure that your study will
be manageable and that you remain
motivated.

Interest – Interest should be the most
important consideration in selecting a
research problem. A research endeavor is
usually time consuming and involves hard
work and possibly unforeseen problems. If
you select a topic which does not greatly
interest you, it could become extremely
difficult to sustain the required motivation
and put in enough time and energy to
complete it.

Magnitude – You should have sufficient
knowledge about the research process to
be able to visualize the work involved in
completing the proposed study. Narrow the
topic down to something manageable,
specific and clear. It is extremely important
to select a topic that you can manage
within the time and with the resources at
your disposal. Even if you are undertaking
a descriptive study, you need to consider
its magnitude carefully

 Measurement of concepts – If you are using a
concept in your study (in quantitative
studies), make sure you are clear about its
indicators and their measurement. For
example, if you plan to measure the
effectiveness of a health promotion
program, you must be clear as to what
determines effectiveness and how it will be
measured.

Level of expertise – Make sure you
have an adequate level of expertise for
the task you are proposing. Allow for the
fact that you will learn during the study
and may receive help from your research
supervisor and others but remember that
you need to do most of the work
yourself.

Relevance – Select a topic that is of
relevance to you as a student and as a
professional later on. Ensure that your
study adds to the existing body of
knowledge, bridges current gaps or is
useful in policy formulation. This will help
you to sustain interest in the study.

Availability of data – If your topic entails
collection of information from secondary
sources (office records, client records,
census or other already-published reports,
etc.) make sure that this data is available
and in the format you want before finalizing
your topic.

 Ethical issues – Another important consideration in formulating
a research problem is the ethical issues involved. In the course
of conducting a research study, the study population may be
adversely affected by some of the questions (directly or
indirectly); deprived of an intervention; expected to share
sensitive and private information; or expected to be simply
experimental ‘guinea pigs’. How ethical issues can affect the
study population and how ethical problems can be overcome
should be thoroughly examined at the problem-formulation
stage.

Research Problem
A research problem is an educational
issue or concern that an investigator
presents and justifies in a research study.
Research is conducted because of a
problem that needs to be addressed,
question to be answered, and knowledge
gap that should be filled.

One common mistake is to state titles first then try
to identify the components of the title. Titles can be
reworded even after the conduct of the study, but
the research problem cannot be changed because
a change in the problem means a change in the
entire study. However, the title becomes a major
road sign in a research. It is a tangible idea that the
researcher can keep refocusing on and changes as
the project goes on.

The research problem is important as it
establishes the importance of the topic
and creates interest for the reader.
Also, the research problem focuses the
reader’s attention on how the study will
add to the literature and body of
knowledge.

Formulating a research problem is a difficult
stage of the research process for most of
beginning researchers. But when a
researcher has identified and formulated the
research problem, the researcher has a
direction and basis in choosing the
appropriate methodology and in
accomplishing all the other parts of the
research activity

There are five characteristics to consider as bases in stating
problems or objectives using the acronym SMART.
1. Specific – the question should specify what variables are to be
determined.
2. Measurable – the variables involved can be subjected to
measurement, with any level of measurement and with the use
of measuring instruments.
3. Attainable – the question can be answered, or the objective can
be attained because the needed data can be collected and can
be analyzed with appropriate tools.

1.Relevant – results can be obtained
because the data can be obtained following
scientific procedures and techniques.
2.Time-bound – there is a time frame for
every activity or step in the research work.

Research-Problems-and-Variables PowerPoint

Creating the Problem Statement
A problem statement is usually one or two sentences to explain
the problem your research will address. In general, a problem
statement will outline the negative points of the current situation and
explain why this matters. It also serves as a great communication
tool, helping to get support from others. One state the problem in
the opening paragraph (i.e., something that needs a solution). Here,
the researcher must identify an issue, either research-based
research problems or practical problems. Reference and support
the problem using the literature.

The purpose of a problem statement is to:
 Introduce the reader to the importance of the topic being
studied. The reader is oriented to the significance of the
study and the research questions or hypotheses to
follow.
 Places the problem into a particular context that defines
the parameters of what is to be investigated.

Provides the framework for
reporting the results and indicates
what is probably necessary to
conduct the study and explain how
the findings will present this
information.

A common pitfall is defining the research problem
based on the proposed software tool to be
developed . In this case, after doing a literature
review (step 1) and perceiving something to be the
research problem, the researcher directly formulate
a solution in the form of a software tool (step 2)
without clearly defining the problem and the
variables under study. Thus, when asked what
particular research problem is being tackled, the
researcher then tries to look for literature (step 3) to
support the solution or tool being developed. This
practice may be bias as previous studies or
literature may not be included.

As much as possible, prior to the formulation of a research problem,
one must take time in performing a literature review (step 1),
exhausting all avenues to gather relevant paper and information.
The formulated research problem is based on the different issues
and concerns being addressed by previous research and the gaps
identified. From here, the researcher must conduct another
literature review (step 2), this time in order to identify existing
solutions that have been developed and formulated in order to
answer or help solved the research problem that have been
identified. We do this, in order to know what exists and identify
gaps. Also, this second literature review is undertaken in order not
to repeat existing solutions.

After these two steps, we formulate our own
solution (step 3) to the research problem. The
solution can be a modification to an existing
solution, taking into account that the proposed
enhancement can provide a significant change or
effect. Or the solution is a novel alternative to
existing solutions. In the computing field, we
developed tools to implement the solutions being
proposed. Thus, the software tool is not the actual
solution but just an implementation of our solution.

Locating the Research Problem
In the conduct of a literature review, one can easily identify the research problem being
addressed by reading the opening paragraphs of existing studies for one or more of the
following:
 What is the issue or problem?
 What controversy leads to the need for a study?
 What concern is being addressed behind the study?
 Is there a sentence such as, “The problem being addressed in this study is…”?
A well written paper can easily provide answers to those questions and will make it
easier for you to do the review.

Formulating A Research Problem
Formulating your research problem
enables you to make a purpose of your study
clear to yourself and target readers. Focus
your paper on providing relevant data to
address it. A problem statement is an
effective and essential tool to keep you on
track with research and evaluate it. Consider
5 ways to formulate the research problem:

1.Specify your research objectives;
In some research, rather than writing research
questions, one uses research objectives. A clear
statement that defines all objectives can help you
conduct and develop effective and meaningful
research. They should be manageable to bring you
success. A few goals will help you keep your study
relevant. This statement also helps professors
evaluate the questions your research project
answers and different methods that you use to
address them.

1.Review its context or environment;
It’s necessary to work hard to define and test all
kinds of environmental variables to make your project
successful. This step can help you define if the
important findings of your study will deliver enough
data to be worth considering. Identify specific
environmental variables that may potentially affect
your research and start formulating effective methods
to control all of them.

1.Explore its nature;
Research problems may range from simple to
complex, and everything depends on a range of
variables and their relationships. Some of them can
be directly relevant to specific research questions,
while others are completely unimportant for your
project.

1. Determine variable relationships;
Scientific, social, and other studies often focus on creating a certain sequence
of repeating behaviors over time. Completing the entire process involves:
 Identifying the variables that affect possible solutions to your research problem;
 Deciding on the degree to which you can use and control all of them for study
purposes;
 Determining functional relationships between existing variables;
 Choose the most critical variables for a solution of your research problem.

1.Anticipate the possible consequences of alternative
approaches.
There are different consequences that each
course of action or approach can bring, and that’s
why you need to anticipate them. Why
communicate possible outcomes? It’s a primary
goal of any research process.

Structuring your research problem
Look at scientific papers and take notice of the
research questions because they are crucial for
determining the quality of answers, methods, and
findings. Quantitative designs use deductive
reasoning to state a testable hypothesis.
Qualitative methods use inductive reasoning to
make a strong statement of your future thesis

Elements of a Quantitative Purpose Statement
A quantitative purpose statement identifies the
variables, their relationships, and the participants and
site for research. You can use the following guidelines
for writing the purpose statement:

 Use a single sentence.
 Use wording such as The purpose of this study . . . .
 If using a theory, state the theory you plan to test.
 Use quantitative words (e.g., “relate,” “compare,” “describe”) to describe the
relationships between variables.

 Present the independent variable (1st position in sentence)
 Present the dependent variable (2nd position in sentence)
 Identify control and/or mediating variable (3rd position in
sentence)
 Also include the research site and the participants

The types of quantitative research questions:
 Describe results of your variables.
 Compare two or more groups on the independent variable in terms of the dependent
variable.
 Relate two or more variables.

You write the quantitative research questions similarly to that of the
quantitative purpose statement with some modifications:
 Pose a question
 Begin with “how”, Begin with “how,” “what,” or “why.”
 Specify the independent, dependent, and mediating or control variables.
 Use the words describe, compare, or relate to indicate the action or
connection among the variables.
 Indicate the participants and the research site for the study.

Designing Qualitative Purpose Statements and
Research Questions
In designing qualitative purpose statements and
research questions, one must understand how these
statements and questions differ from quantitative
research. Also, the researcher must understand the
role of a central phenomenon in qualitative research
and that qualitative research as an emerging
process.

Differences also exist in terms of how one
look at variables in relation to the research.
Quantitative research focuses more on
explaining or predicting variables whereas
Qualitative research looks more on
understanding or exploring a central
phenomenon.

Elements of Qualitative Purpose Statement
The following guidelines can be used in order to write a
qualitative purpose statement:
 A single sentence
 A statement such as, “The purpose of this study . . . ”
 The central phenomenon

 A statement identifying the type of qualitative design
 Qualitative words (e.g., “explore,” “understand,”
“discover”)
 The participants
 The research site

Types of Qualitative research questions
 Central question is the overarching question you explore in the research study.
 Sub questions divide the central question into smaller, specific questions.
o Issue sub questions: Narrow the focus of the central question into specific
issues.
o Procedural sub questions: Indicate the steps to be used in analyzing the data in
a qualitative study.
 Interview questions are asked during your interview and are based on your sub
questions and central question.

Both quantitative and qualitative research
require research questions. The kind of question
you use depends on what you want to find out
about and the type of research you want to do. It
will shape your research design.

The table below shows some of the most
common types of research questions. Bear
in mind that many academic research
questions will be more complex than these
examples, often combining two or more
types.

Research Concepts and Variables
All about Variables
In research one has to gather data or a set of
observations of persons, informants, respondents,
participants, etc. These observations are classified and
categorized into groups that have similar characteristics
that belongs to different categories or groups.

Variables represents a class of outcomes that
can take more than one value. The outcome is a
characteristic of a unit of observation. Example a
hair color can have a value of red, brown, black,
or blond. Height can have a value short, tall, 5’3”
or 6’1” as weight can have the value heavy, light,
128 lbs, or 70 kilos. The more precisely that a
variable is measured, the more useful the
measurement is.

When the value of a variable is observed
and recorded, it is known as an observed
value. The set of observed values is called
data. In research, we can classify data into
two categories: quantitative data and
qualitative data.

Qualitative data is a type of data where the
values of variables are expressed in words or
statements. This is sometimes called categorical
data as values of variables are more descriptive
in nature. Example is gender as variable with
male and female as possible values. Another is
civil status with possible values of ‘single’,
‘married’, ‘widowed’, and ‘separated’ among
others.

Quantitative data, on the other hand, are values
of variables expressed in numerical terms,
either counted or measured. It is also often
called numerical data. Example is age,
temperature readings, number of live births,
etc.

Type of Variables
A variable is a measurable characteristic that
varies. It may change from group to group,
person to person, or even within one person over
time. There are several types of variables that
you will encounter when doing research.

Discrete variables. Discrete variables are
variables that can take only a finite number of
possible values within a limited range of
values.
Example: number of female students in a
class, number of male mayors in a province

Continuous variables. Continuous variables are
variables that can take an infinite number of possible
values within a range.
Example: weight of babies born, cost of gasoline,
time it takes to finish a test

Dependent variables. Dependent variables represent the measure that
reflects the outcomes of a research study. It is sensitive to changes in the
different levels of the independent variable. Dependent variable is a type of
variable that is measured to see whether the treatment or manipulation of
the independent variable had an effect. Other terms for dependent
variables are outcome variable, results variable, and criterion variable.
Example: Effect of parental involvement in school on children’s grades
Dependent variable: Children’s grades

Independent variables. Independent variables represent the treatments
or conditions that the researcher has either direct or indirect controls over
the dependent variables to test their effects on a particular outcome.
Independent variables as much as possible be independent of any other
variable that is being used in the same study. Simply, it is a type of
variable that is manipulated to examine its impact on a dependent
variable. Other terms for independent variables are treatment variable,
factor, and predictor variable.
Example: Age differences in stress for people ages 30-39, 40-49, and 50-
59
Independent variable: Age, in 3 levels (30-39, 40-49, 50-59)

When researchers are not interested in looking at
the effects of one thing on another, but only
interested on how variables may be related, then
there are no independent variables.
Example: Relationship between the amount of time a
father spends with his children and his job
performance.

In some research especially that of experiments, there could be more than one
independent variable. Such type of is called a factorial design.

Confounding variables. A confounding variable is an ‘extra’ variable that is not
accounted for which can ruin a research as it compete to explain the effects of the
independent variable to the dependent variable.

Control variables. A control variable is a variable in an
experiment which is held constant in order to assess the
relationship between multiple variables. This type of variable
is related to the dependent variable, the influence of which
needs to be removed.
Example: Hypothesizing plants grow optimally at 4 hours of
light a day.
Control variable: fertilizer level
Reason: if plants are receiving different fertilizer levels, we
may not know if the conclusion is correct based on our
hypothesis.

If control variables are not kept constant, the
experiment compromises internal validity and
control variables turn to confounding variables
which affect results of research.

Extraneous variables. An extraneous variable
is a type of variable that is related to the
dependent variable or independent variable that
is not part of the experiment but could affect the
results of the experiment. These variables have
unpredictable impact upon the dependent
variable. As much as possible one must make
sure that it is the manipulation of the
independent variable that has an effect on the
dependent variable.

Example: Effects of television watching on
achievement
Extraneous variable: Television programs
Reason: Programs may have positive or negative
impacts on achievement

Moderator/Intervening variables. Finally we have moderator variable or
intervening variables. Moderator variables or intervening variables are
types of variable that is related to the variables of interest (whether
independent and dependent), masking the true relationship between the
independent and dependent variables.
Example: Relationship between crime rate and ice cream consumption
Moderator variable: Temperature
Reason: Temperature must be observed because it moderates the
relationship

Hypothesis
According to dictionary.com, a hypothesis is a proposition, or set
of propositions, set forth as an explanation for the occurrence of
some specified group of phenomena, either asserted merely as a
provisional conjecture to guide investigation (working hypothesis) or
accepted as highly probable in the light of established facts. Simply,
a hypothesis is an educated guess. Its most important role is to
reflect the general problem statement.

There are two types of hypothesis, the null hypothesis
and the research hypothesis.
Null Hypothesis (H0)
The null hypothesis is considered as a statement of
equality. It acts as a starting point and a benchmark
against which the actual outcomes of a study will be
measured
Example: Average scores of 9th
graders and 12th
graders on the ABC memory test
H0: No difference in the scores of 9th
graders and 12th

Research Hypothesis (H1)
The research hypothesis, on the other hand, is
considered to be a statement of inequality. There can
be more than one research hypothesis for any one null
hypothesis
Example: Average scores of 9th
graders and 12th
H1: Difference in the scores of 9th
graders and 12th

Types of Research Hypothesis
 Non-directional. Posits no direction to the inequality
(“different from”)
Example: The average score of 9th
graders is different from
the average score of 12th
 Directional. Posits a direction to the inequality (“more than”,
“less than”)
Example: The average score of 9th
graders is greater than the
average score of 12th

Purposes of Hypothesis
Hypothesis is to be tested directly as one step in the research
process. It is a conjectural statement about a relationship between
two or more variables. Hypothesis is needed when the research
objective or problem statement calls for determining relationship
between variables. The results of this test are compared with what
is expected by chance alone to see which of the two explanations
is the more attractive one for observed differences between
groups.
We do not prove the hypothesis. Rather than setting out to
prove anything, always set out to test the research. Hypothesis is
developed to examine to refute, and not to prove it to be correct.

Formulating Research Hypothesis
Formulating a research hypothesis begins by
formulating an inferential question in your
problem statement. This is because a research
hypothesis can be patterned from this inferential
question. The following list pertains to the same
question but presented and written differently.

Sample 1: Is the computer literacy level of the respondents related to the following
characteristics?:
a. Age
b. Gender
c. Length of service

Sample 2: What is the relationship between the computer literacy
level and each of the following characteristics of the respondents?:
a. Age
b. Gender

Sample 3: Is there a relationship between the
computer literacy level and each of the following
characteristics of the respondents?:
a.Age
b.Gender

Sample 4: Are the following variables associated with the
computer literacy level of the respondents?:
a. Age
b. Gender

Testing the Hypothesis
Hypothesis testing is a formal process for testing research
predictions about the population using samples. Particularly, we
make use of inferential statistical analysis in order to perform this
testing. With hypothesis testing, we can perform:
 Comparison tests which assess group differences in outcomes
 Regression test that assess cause-and-effect relationships
between variables.
 Correlation tests that focuses on relationships between
variables without assuming causation.

Hypothesis testing give two main outputs:
1.A test statistic that tells you how much your data
differs from the null hypothesis of the test.
2.A p value which tells you the likelihood of obtaining
your results if the null hypothesis is actually true in
the population.

Can the hypothesis be rejected or retained via
statistical means? Again, a hypothesis is tested
using statistical tools as the use of these tools
provide stability and validity. However, it is
important to have a reliable measure or to use
the most appropriate tool for the test. Also, there
is a need to use large enough sample to detect
the true effect and avoid Type I & II errors.

 Type I Error (False Positive Error). Type 1 Error
occurs when the null hypothesis is true but is
rejected. This is often called the false positive
error.
 Type II Error (False Negative Error). This occurs
when the null. Hypothesis is false but erroneously
fails to be rejected. Often, this is called the false
negative error.

Example: Type I vs Type II error
You decide to get tested for COVID-19 based on mild
symptoms. There are two errors that could potentially occur:
 Type I error (false positive): the test result says you have
coronavirus, but you actually don’t.
 Type II error (false negative): the test result says you do not
have coronavirus, but in fact you actually do.

Type I and Type II errors are highly dependent upon
the language or positioning of the null hypothesis.
Changing the positioning of the null hypothesis can
cause Type I and Type II errors to switch roles.

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