research problem statement construct, concept and variables

Research Problem StatementConstruct, Concept and Variables

Research Process

The research process:• Characteristics of research:

– Proprietary vs. scholarly research– Research is based on curiosity and asking questions (creativity)– Research is a systematic process– Research is potentially replicable– Conceptualization, planning and designing research, methodologies for

conducting research, analyzing and interpreting data, reconceptualization– Research is reflexive and self critical– Research is cumulative and self-corrective– Research is cyclical

• Research paradigms:– Physical sciences– Humanities– Social sciences

Assumption Question Positivist paradigm Naturalistic paradigmOntological assumption What is the nature of

realitySingularObjective

MultipleIntersubjective

Epistemological assumption

What is the relationship of the researcher to that being researched

Independent Interdependent

Axiological assumption What is the role of values in the research process

Value-freeUnbiased

Value-ladenBiased

Methodological assumption

What is the process of research

DeductionSearch for cause and effect relationships between variablesStatic designResearcher-controlled settingQuantitative methodsContext-free generalizationsGoals of explanation, prediction and control

InductionHolistic understanding of patterns of behaviorEmergent behaviorNatural settingQualitative methodsContext-bound findingsGoals of understanding and social change

Rhetorical assumption What is the language of research reports?

FormalImpersonal voice

InformalPersonal voice

Concept

• An abstraction encompassing observed events; a word that represents the similarities or common aspects of objects or events that are otherwise quite different from one another.

• The purpose of a concept is to simplify thinking by including a number of events (or the common aspects of otherwise diverse things) under one general heading (Ary 1985).

• Chair, dog, tree, liquid, a doughnut, etc…

Construct• Constructs are the “highest highest-level abstractions” of

complicated objects and events, created by combining concepts and less complex constructs. – used to account for observed regularities and relationships, and to summarize observations and explanations (Ary 1985).

• A concept with added meaning of having been deliberately and con consciously invented or seriously adopted for a special scientific purpose.

1) it enters into theoretical schemes and is theoretical related in various ways to other constructs.

2) it is defined and specified so that it may be observed or measured (Kerlinger 1986).

Construct

• Scientists measure things in three classes: direct observables, indirect observables (not experienced or observed first hand), and constructs.

• These constructs are defined as constructs theoretical creations based on observations but cannot be observed directly or observed indirectly (Kaplan 1964).

• Motivation, visual acuity, justice, problem solving ability, …not a doughnut, …but hunger. problem-

Operational Definition

• It describes meaning to a concept or construct by specifying the operations that must be performed in order to measure or manipulate the concept, as the data collected during research is in terms of observable events (Ary 1985).

• It defines or gives meaning to a variable by spelling out what the investigator must do to measure it (Kerlinger 1986).

• “Operational definitions are essential to research because they permit investigators to measure abstract concepts and constructs and permit scientists to permit move from the level of constructs and theory to the level of observation” (Ary 1985).


• Two Types of Operational Definitions:

• Measured Operational Definition: Operations by which investigators may measure a concept.

• Experimental Operational Definition: Steps taken by a researcher to produce certain experimental conditions.


• Examples of an Operational Definition:

• Measured Operational Definition: An actual (score) value from a test or questionnaire the researchers would develop to measure “hunger.”

• Experimental Operational Definition: A manipulated scenario to produce the condition of “hunger.” (such as preventing the subject from consuming anything for x number of hours) x-

Variable

• Characteristics or attributes of an object, individual or organization that can be measured or observed, and that varies among those objects or individuals being studied (Creswell 2002).

• They possess values and levels (the dimensions on which they vary) (Sommery 1997).

• “The concepts that are of interest in a study become the variable variables for s investigation (Ary 1985).”

Different Kinds of Variables

• Dichotomous: Two valued variables. Example: Sex (male/female) Two-

• Polytomous: Multiple values for variables. Example: Religion (Catholicism, Islam, Judaism, Hinduism, Buddhism, etc…)

• Continuous: A variable that takes on an infinite number of values within a range. Example: Height & Weight

More Kinds of Variables

• Independent: The variable manipulated by the experimenter (also: Experimental, Predictor, Manipulated, Antecedent, Treatment).

• Active: Any variable that is manipulated by the researcher • Attribute: Any variable that cannot be manipulated by the

researcher. For example, all human characteristics are attribute variables: intelligence, sex, socioeconomic status etc.

• Dependent: The dependent variable is the phenomenon that is the object of study and investigation (also: Outcome, Response, Criterion, Effect). - -


• Categorical: Referred to as nominal measurements. One creates ‘categories,’ and classifies all variables that fall under this definition without rank order. All variables under the same category are considered of equal value, and not differentiated.

• Latent: An unobserved ‘entity’ that “stands between” the independent variable and the dependent variable, and mediates the effect of the independent variable on the dependent variable. It is dependent on the independent variable as well as other constructs, yet still plays a role in determining the outcome (possibly: Intervening, Mediating, Hypothetical construct).


• Control: An independent variable that is measured in a study because the y potentially influence the dependent variable. It is a more clearly defined independent variable in attempts to eliminate all bias in regard s to its effects on the dependent variable. (Keeps the study in check). they clearly regards

• Confounding: Variables not actually measured or observed in a study, yet they exist, and its influence cannot be directly detected or understood in a study. One becomes aware of a confounding variable at the end of a study, they realize that there is an effect that was not measured or accounted for, but should be addressed.

Concepts, Construct and Variables

• Concepts (Oxford definition) general notation, abstract ideas.

• Construct (Oxford definition) make by fitting together; build; thing constructed; especially by the mind.

• Variables (Oxford definition) a situation, number or quantity that can vary or be varied

• Constant (Oxford definition) a number or quantity that does not vary

Concepts, Construct

• Concepts are abstract ideas which have been "defined" according to particular characteristics or generalizations (constructs) about them.

• A construct is based on concepts, or can be thought of as a conceptual model that has measurable aspects.

• This will allow the researcher to "measure" the concept and have a common acceptable platform when other researches do a similar research.

Concepts, Construct

• E.g • Measuring advertising effectiveness is an

construct, and concepts related would be brand awareness and consumer behavior.

• Pain is a concept, a theoretical model of pain would be a construct, and a pain assessment tool would give a measurable variable.

Concepts, Construct

• An idea is a plan, suggestion, or possible course of action. ex...I really like the idea of helping people.

A concept is an idea or abstract principle. ex....She added that the concept of arranged marriages is misunderstood in the West.

• Science uses:i. Conceptsii. Links concepts by propositionsiii. Testing theory with observable evidenceiv. Publication of definitions and proceduresv. Control of alternative explanationsvi. Unbiased selection of evidencevii. Reconciliation between theory and observation

Concepts, Construct

• A concept is a verbal abstraction drawn from observation of a number of specific cases

• A theoretical definition explains what is meant by the concept.

• Operational definitions translate the verbal concepts into corresponding variables which

• can be measured. Operational definitions can be either: measured, or experimental.

• Also, a variable can be either measured (e.g., surveys) or manipulated (e.g., experiment).

Concepts, Construct

• A construct serves the same function as a concept, but it is more abstract.

• It is not characterized by a direct link between the abstraction and its observed manifestations.

• For instance, “source credibility” is a construct which has been used in studying persuasion.

• This term can be used in the same way as a concept, but we should recognize that we cannot directly observe different levels of source credibility in individuals.

• However, we can observe the various parts which make up the construct individually, and then combine them to get some overall summary.

Concepts, Construct

• Constructs are built from the logical combination of a number of more observable concepts. In the case of source credibility, we could define the construct as the combination of the concepts of expertise, objectivity, and status.

• Each of these concepts can be more directly observed in an individual.

• We might also consider some of these terms to be constructs themselves, and break them down into combinations of still more concrete concepts

What we see if we do this is a set of constructs at decreasing levels ofabstraction. Only at the bottom of this hierarchy are directly observable concepts.

Concepts, Construct

• A scientific concept really consists of three parts: a label, a theoretical definition, and an operational definition.

• The theoretical definition specifies the verbal meaning which is attached to the concept label.

• We call self-defining concepts like “age” primitive terms. • Primitive terms are adequately defined by their attached

concept labels. • These are the labels which appear at the bottom of the

level of abstraction hierarchy.• RECOMMENDATION: explicitly specify the meaning

associated with each concept, regardless of the extent to which we think the meaning is shared.

Concepts, Construct

• An operational definition translates the verbal meaning provided by the theoretical definition into a prescription for measurement.

• Although they may be expressed verbally, operational definitions are fundamentally statements that describe measurement and mathematical operations.

• An operational definition describes the unit of measurement. Examples of units of measurement are minutes (to measure time), word counts (to measure newspaper coverage of a particular event), percent correct responses, etc.

• An operational definition adds three things to the theoretical definition.

• Operationalization is to take a fuzzy concept, such as 'helping behavior', and try to measure it by specific observations, e.g. how likely are people to help a stranger with problems.

Concepts, Construct

• An operational definition specifies the level of measurement.

• Levels of measurement can range from the simple nominal variables which only make distinctions between categories like “present or absent” or “yes or no”; to ordinal variables which contain some information about the quantity (“more or less”) of the concept present, but have no real measurement scales; to continuous variables which have real scale points which are equally spaced, and which can take on any value.

Concepts, Construct• The operational definition must be very closely associated with

the theoretical definition. • It must state clearly how observations will be made so they will

reflect as fully as possible the meaning associated with the verbal concept or construct.

• The operational definition must tell us how to observe and quantify the concept in the “real world”.

• This connection between theoretical and operational definitions is quite critical.

• This connection establishes the validity of the measurement. • The amount of validity in measurement is proportional to the

extent to which we actually measure what we intend to measure, that is, the degree to which the operational definition and the theoretical definition correspond.

Relationships between variables/concepts

• Null relationships• Covariance relationships:

– In a covariance relationship, changes in the values of one variable (the measured concept) are associated with changes in the values of the other variable.

– That is, the variables shift values simultaneously, or covary. – This does not mean that one concept is the cause and the

other is the effect. – A cause-effect relationship between concepts requires

more than just covariance, as we’ll see shortly. – A covariance relationship is typically diagramed with a

curved, double-headed arrow between the concept


– Two variables which are related proportionally can covary either positively or negatively.

– While covariance relationships can provide prediction, they can’t provide explanation of the relationship.

– Spurious relationships (artifacts): two variables may covary because they are both the effects of a common cause. The unobserved, but real, causal variable sometimes is called a confounding variable, since it may mislead us by producing the appearance of a relationship between the observed variables.

– Control variables


• Causal relationships:– Causality means that a change which occurs in one

variable (the cause) brings about a change in another variable (the effect).

– Alternative terms for cause and effect variable are independent variable and dependent variable.

– This terminology is based on the logic that in a causal relationship the state of one variable (the effect) depends on the state of the other (the cause).

– The state of the cause is independent of the state of the effect variable.


• There is a critical difference between covariance and causality:

• Covariance means that a change in one variable is associated with a change in the other variable; causality requires that a change in one variable creates the change in the other.

• In other words, covariance alone does not imply causality.


– Covariance is only one of four conditions which must be met before we can state that a relationship is causal:

• Spatial contiguity• Covariance (necessary but not sufficient condition)• Temporal ordering• Necessary connection (This necessary connection is a

statement which specifies why the cause can bring about a change in the effect. It is the logical statement of the process or mechanism by which the two variables are related to one another in a cause-effect relationship.

SOME DEFINITIONS OF CONSTRUCTSPERMISSIVENESS:• Oxford def. a) tolerant; liberal; b) giving permission• Experimental def. Extending the boundaries of acceptable findings.• Measured def. Confining the boundaries of acceptable findings.REINFORCEMENT:• Oxford def. Strengthen or support, especially with additional personnel,

material etc.• Experimental def. To build credibility by strengthening your research findings.• Measured def. To build structural credibility to strengthen your research

findings.READING ABILITY:• Oxford def. none• Experimental def. To understand through written text the research findings.• Measured def. same as above

SOME DEFINITIONS OF CONSTRUCTS

ACHIEVEMENT:• Oxford def. a) something achieved b) act of achieving achieve: a) attain by effort acquire;

gain earn b) accomplish• Experimental def. To accomplish what you have set out to prove.• Measured def. To put your research findings into a written format to be used as

documentation.INTERESTS:• Oxford def. a) curiosity, concern b) quality existing curiosity c) note worthiness,

importance 2) subject, hobby in which one is concerned 3) advantage or profit 4) self interest, excite the curiosity or attention to take a personal interest.

• Experimental def. An educational topic that concerns you and is worthy of your research.• Measured def. same as aboveNEEDS:• Oxford def. archaic of necessity, requirement• Experimental def. The requirements of research in order for it to be valid.• Measured def. The requirements for charting the research findings in order to give

documented support.


TRANSFER OF TRAINING:• Oxford def. none• Experimental def. To give another researcher the information needed so that

they can continue researching from where you left off.• Measured def. same as aboveLEADERSHIP:• Oxford def. A person that leads or is followed by others.• Experimental def. A person who has the ability to direct others through a

research experiment, and who will set the tone of the research.• Measured def. A person who will design the way in which the research

findings will be documented.CLASS ATMOSPHERE:• Oxford def. none• Experimental def. The tone of a class setting that will allow for similar testing

conditions.• Measured def. same as above

SOME DEFINITIONS OF CONSTRUCTSDELINQUENCY:• Oxford def. Failing in one’s duty• Experimental def. Failing to plan out the way you are going to conduct you

research so that your findings are valid.• Measured def. Failing to document your findings in a way that another

researcher can duplicate your research findings.ORGANIZATIONAL CONFLICT:• Oxford def. none• Experimental def. Lack of agreement within a research group.• Measured def. Lack of consistent findings and charting.SELF-OTHER-ATTITUDE:• Oxford def. none• Experimental def. Ability to work together for the good of the research• Measured def. same as above


CONFORMITY:• Oxford def. Accordance with established practice,

agreement• Experimental def. To follow a specific plan that has

already been established and agreement as a research team to stick to a research method that was agreed upon.

• Measured def. To chart the research findings in a way that would best support your findings and based on a method that was used prior by another research team when studying the same subject area.

Variables

• A variable is something that changes. • It changes according to different factors. • Some variables changes easily, like the stock-

exchange value, while other variables are almost constant, like the name of someone.

• Researchers are often seeking to measure variables.

• The variable can be a number, a name or anything where the value can change.

Variables

• An example of a variable is temperature. • The temperature varies according to other variable and

factors. • You can measure different temperature inside and

outside. • If it is a sunny day, chances are that the temperature will

be higher than if it's cloudy. • Another thing that can make the temperature change is

whether something has been done to manipulate the temperature, like lighting a fire in the chimney.

Variables

• A variable is any entity that can take on different values.

• Anything that can vary can be considered a variable.

• For instance, age can be considered a variable because age can take different values for different people or for the same person at different times.

Variables

• Variables are not always 'quantitative' or numerical. • The variable 'gender' consists of two text values: 'male' and

'female'.• We can, if it is useful, assign quantitative values instead of (or in

place of) the text values, but we don't have to assign numbers in order for something to be a variable.

• It's also important to realize that variables aren't only things that we measure in the traditional sense.

• For instance, in much social research and in program evaluation, we consider the treatment or program to be made up of one or more variables (i.e., the 'cause' can be considered a variable).

• An educational program can have varying amounts of 'time on task', 'classroom settings', 'student-teacher ratios', and so on.

Variables

• Variables may have the following characteristics:– Period: When it starts and stops. – Pattern: Daily, weekly, ad-hoc, etc. – Detail: Overview through to 'in depth'. – Latency: Time between measuring dependent and

independent variable (some things take time to take effect).

Variables

• In research, you typically define variables according to what you're measuring.

• The independent variable is the variable which the researcher would like to measure (the cause), while the dependent variable is the effect (or assumed effect), dependent on the independent variable.

• These variables are often stated in experimental research, in a hypothesis, e.g. "what is the effect of personality on helping behavior?“

Variables

• In explorative research methodology, e.g. in some qualitative research, the independent and the dependent variables might not be identified beforehand.

• They might not be stated because the researcher does not have a clear idea yet on what is really going on.

• The independent variable, also known as the manipulated variable, lies at the heart of any quantitative experimental design.

• A researcher manipulates an independent variable, to influence a dependent variable, or variables.

• There may be more than two dependent variables in any experiment.

Variables

• The independent variable is what you (or nature) manipulates -- a treatment or program or cause.

• The dependent variable is what is affected by the independent variable -- your effects or outcomes.

• For example, if you are studying the effects of a new educational program on student achievement, the program is the independent variable and your measures of achievement are the dependent ones.

Variables

• The independent variable (IV) is often thought of as our input variable.

• It is independent of everything that occurs during the experiment because once it is chosen it does not change.

• In our experiment on college performance, we chose two groups at the onset, namely, those with work experience and those without.

• This variable makes up our two independent groups and is therefore called the independent variable.

Variables

• The dependent variable (DV), or outcome variable, is dependent on our independent variable or what we start with.

• In this study, college grades would be our dependent variable because it is dependent on work experience.

• If we chose to also look at men versus women, or older students versus younger students, then these variables would be other independent variables and the outcome, our dependent variable (college grades), would be dependent on them as well.

• Remember that whatever is the same between the two groups is considered a constant because they do not vary between groups but rather remain the same and therefore do not affect the outcome of each group differently

Variables

• Descriptive variables are those that which will be reported on, without relating them to anything in particular.

• Categorical variables result from a selection from categories, such as 'agree' and 'disagree'. Nominal and ordinal variables are categorical.

• Numeric variables give a number, such as age.• Discrete variables are numeric variables that come from a

limited set of numbers. They may result from , answering questions such as 'how many', 'how often', etc.

• Continuous variables are numeric variables that can take any value, such as weight.

• Extraneous variables are additional variables which could provide alternative explanations or cast doubt on conclusions.

Variables

• Researchers must be aware that variables outside of the independent variable(s) may confound or alter the results of a study.

• Confounding variables are variables with a significant effect on the dependent variable that the researcher failed to control or eliminate - sometimes because the researcher is not aware of the effect of the confounding variable.

• The key is to identify possible confounding variables and somehow try to eliminate or control them.

Variables

• A confounding variable, also known as a third variable or a mediator variable, can adversely affect the relationship between the independent variable and dependent variable.

• This may cause the researcher to analyze the results incorrectly.

• The results may show a false correlation between the dependent and independent variables, leading to an incorrect rejection of the null hypothesis.

Variables

• If, for instance, we had two groups in the above mentioned study but did not control for age then age itself may be a confound. Imagine comparing students with work experience with a mean age of 40 with students without work experience and a mean age of 18.

• Could we reasonably say that work experience caused the student to receive higher grades?

• This extraneous variable can play havoc on our results as can any intervening variable such as motivation or attention.

• Addressing confounds before they alter the results of your study is always a wise decision

Variables

Every Problem Needs Further Delineation

• To comprehend fully the meaning of the problem, the researcher should eliminate any possibility of misunderstanding by– Stating the hypotheses and/or research questions: Describing

the specific hypotheses being tested or questions being asked.– Delimiting the research: Fully disclosing what the researcher

intends to do and, conversely, does not intend to do.– Defining the terms: Giving the meanings of all terms in the

statements of the problem and subproblems that have any possibility of being misunderstood.

– Stating the assumptions: Presenting a clear statement of all assumptions on which the research will rest.

• These matters facilitate understanding of the research – called the setting of the problem

Stating the Hypotheses and/or Research Questions

• Hypotheses are tentative, intelligent guesses posited for the purpose of directing one’s thinking toward the solution of the problem

• Necessary in searching for relevant data and in establishing a tentative goal

• Hypotheses are neither proved nor disproved. They are nothing more than tentative propositions set forth to assist in guiding the investigation of a problem or to provide possible explanations for the observations made

Accept/Reject Hypotheses

• Hypotheses have nothing to do with proof• Their acceptance or rejection is dependent on what

the data – and the data alone – ultimately reveal• Hypotheses may originate in the subproblem, could

be 1 to 1• Hypothesis provides a position from which a

researcher begins to initiate an exploration of problem and subproblems and checkpoints to test the findings that the data reveal

Accept/Reject Hypotheses

• If the data do not support the research hypothesis, don’t be disturbed – it merely means that the educated guess about the outcome of the investigation was incorrect

• Frequently, rejected hypotheses are a source of genuine and gratifying surprise – truly made unexpected discovery

• Another type of hypothesis is the null hypothesis

Null Hypothesis

• It is an indicator only• Reveals some influences, forces, or factors

that have resulted in a statistical difference or no such difference

• Most researches stop at this point – getting off at mezzanine instead down to the basement where the foundations are

Null Hypothesis Dynamics

• If null hypothesis shows the presence of dynamics, then the next logical questions are as follows:– What are these dynamics?– What is their nature?– How can they be isolated and studied?

• For example, let’s say that a team of social workers believe that one type of after-school programme for teenagers (we’ll call it Programme A) is more effective than another programme (we’ll call it Programme B) in terms of reducing high school dropout rates.

Null Hypothesis Dynamics

• The null hypothesis stating that there will be no difference in the high school graduation rates of teenagers enrolled in Programme A and those enrolled in Programme B has been rejected – encouraging news – it is mezzanine conclusion

• What specifically were the factors within the programme that cause the null hypothesis to be rejected?

• These are fundamental questions – will uncover facts that may lie very close to the discovery of new substantive knowledge – the purpose of all research

Delimiting the Research• Know PRECISELY what the researcher intends to DO and does

NOT intend to do• What the researcher intends to do is stated in the problem

statement• What the researcher is not going to do is in the delimitations• The researcher can easily be beguiled (deceived, cheated) by

discovering interesting information that lies beyond the precincts of the problem under investigation

• Only a researcher who thinks carefully about the problem and its focal centre can distinguish between what is relevant and what is not relevant to the problem

• All irrelevancies to the problem must be firmly ruled out in the statement of delimitations

Defining The Terms• Without knowing explicitly what a term means, we cannot

evaluate the research or determine whether the researcher has carried out what was proposed in the problem statement

• Need not necessarily agree with such a definition, but as long as we know what the researcher means when using the term, we are able to understand and appraise it appropriately

• A formal definition contains three parts: (a) the term to be defined; (b) the genera, or the general class to which the concept being defined belongs; and (c) the differentia, the specific characteristics or traits that distinguish the concept being defined from all other members of the general classification

Defining The Terms

• To make the software more USER-FRIENDLY?• What is the relationship between the user

interface metric and user acceptance?• The researcher must be careful to avoid

circular definitions, in which the terms to be defined are used in the definitions themselves

• A classic example is Gertrude Stein’s “A rose, is a rose, is a rose”

Stating the Assumptions

• Assumptions are so basic that, without them, the research problem itself could not exist

• Example, to determine by pretest-posttest whether one method of instruction has produced the results hypothesised

• The assumptions are:– The test measures what it is presumed to measure– The teacher(s) in the study can teach effectively– The students are capable of learning the subject

matter• Without these assumptions, we have no problem, no

research


• Assumptions are what researchers take for granted with respect to the problem

• But taking everything for granted may cause misunderstanding

• If others know the assumptions a researcher makes, they are better prepared to evaluate the conclusions that result from such assumptions

• Many students thought that assumption is stating the obvious

• In research, try to leave nothing to chance in the hope of preventing any misunderstanding


• All assumptions that have a material bearing on the problem should be openly and unreservedly set forth.

• Asking question “What am I taking for granted with respect to the problem?” will bring assumptions into clear view

Importance of the Study

• In dissertations or research reports, researchers frequently set forth their reasons for undertaking the study

• In a research proposal, such a discussion may be especially important

• Some studies seem to go far beyond any relationship to the practical world

• Of such research efforts, one might asks “Of what use is it? What practical value does the study have?”

• For example, the time, money, effort spent on early space exploration flights

research problem statement construct, concept and variables

Documents

scholarly research research

characteristics of research

reconceptualization

systematic process research

cyclical research paradigms

selfcorrective research

self critical research

questions creativity