What you will learn?
Fundamentals of Research Methods – this includes definition and basic elements of scientific research.
Research Philosophy including approaches, paradigms and designs.
Sampling techniques, Data Collection and Data Analysis Techniques
Proposal Writing – includes sections of the research proposal and the structure of chapter 4 and 5
Referencing – APA style of referencing is explained in details.
About this course
Research Methods or Research Methodology is one of the common courses in most institution of higher learning. This is because both undergraduate and postgraduate students need to develop skills and competencies of conducting research so that they can find solutions to societal problems. Research is the only credible source of valid data that can help in decision making.
In her many years of teaching and mentoring students, Dr. Lydiah Wambugu has observed that Research Methods is one of the units with the highest failure rate in the examinations. This observation may be explained by either majority of the lecturers who teach Research Methods do so in a very abstract manner and do not break down the concept of research in ways that students can easily understand or students find research methods difficult because they are not able to link theory and practice. It is for this reason that Dr. Wambugu has developed this course from the simple concepts to the more complex concepts in research.
The beauty with this course is that the content is organized in lectures and each lecture builds on one another. The content is explained in a learner friendly language for ease of understanding. Whether you are undergraduate or postgraduate student, I believe that you will find this course quite useful as you go through the research methods course.
Materials Included
60 hours on-demand video
Downloadable resources
Downloadable revision questions
Full lifetime access
- Target Audience
- Undergraduate and postgraduate students learning research methods as a course unit
- Anyone struggling to understand research methods
- Anyone seeking clarity in any specific area in research
- Anyone in consultancy wishing to perfect their skills in data collection and data analysis
Requirements
Internet Access.
Mobile Phone/Tablet/TV or Laptop.
A pen.
A notebook.
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Research is one discipline that students find abstract. To research means to re-search, this clearly shows that there is repetition of search. The question we need to ask ourselves is, what are we searching in research? We are searching for knowledge. Why are we searching for knowledge? Because in the society, there are problems, there were problems and they will always be problems. Therefore, we need to find answers to these problems. This lesson will introduce you to the discipline of research. In this lecture, we are going to define research as search for knowledge. We shall also be asking ourselves, why is research scientific, systematic and objective? Once we explain the three concepts, we shall then discuss the characteristics of scientific research. Finally, we shall ask ourselves, is research a process in futility? This will lead us to the three main purpose of research as explore, describe and explain
In Lesson one, we defined the term research as search for knowledge. We also said that we search for knowledge because in the society there are problems. A problem is a discrepancy between the ways things are and the way they ought to be. This gap is what is referred to as a research problem. We need to note that a research problem is not an issue that is causing pain. A problem is when a research asks the question WHY? This WHY calls for an investigation. Therefore, even when things are going on well, there is need to find out WHY. In this lesson, we shall discuss sources of this knowledge that we need to find solutions to research problems. There are three sources of knowledge: Experience, Reasoning and Scientific Inquiry. Welcome
Do you know that every discipline has its own language? Research as a discipline has its language which is only understood by researchers. Language forms the building blocks of every discipline. In social science research, we call these building blocks, elements of scientific research. There are various elements. We shall discuss these elements in lesson 3, 6,7,8. In todays lesson, we are discussing three elements. These are Concepts, Constructs and Variables. Note that elements are not discussed in any order. However, the lessons will discuss the elements that are related in one lesson.
When constructs are defined in measurable terms, they are called variables. Variables are measurable characteristic that assumes different values within a class of objects or events. Variables must vary. A construct that does not vary within a class of objects or events is called a constant. This lesson introduces you to the various types of variables in social science research. There are three main types of variables: Independent (IV) and dependent variables (DV) where the independent influences the dependent variable; we have confounding variables that confuses the primary relationship between IV and DV and moderating variables that mediates the relationship between IV and DV. Confounding variables are of two types: Intervening and Extraneous variables. This lesson will take you through these variables giving examples and revision questions to ease our understanding.
Besides the types of variables we have discussed in lesson 4, Variables are also classified according to the role they play in a study and also based on the mathematical values that they take in a continuum. Thus we have experimental classification and mathematical classification. This lesson discusses the mathematical classification where variables are either classified as discrete or continuous. Discrete variables can only take whole numbers while continuous variables can take any value within a continuum, they do not have a minimum sized value. These two categories leads us to scales of measurement or in some books they are referred to as levels of measurement. Discrete variables are measured at nominal and ordinal scale or level. In this scale, numbers carry qualitative value meaning they are non-numeric. Continuous variables are measured at interval and ratio scale where numbers carry a quantitative value. Welcome to this lesson as we explore those classification and scales of measurement.
Research as a discipline is concerned with seeking solutions to social problems which we call research problems. We defined a problem as the gap between what is and what ought to be. Remember we said that research is not conducted out pf here say but on a problem that exists and is well anchored on data. This lesson will introduce you to research problem. What is a good research problem? What are the sources of a research problem?
Is there a difference between research problem and statement of the problem? The answer is yes. Statement of the problem is the statement that shows that there is a need for research to be conducted. It explains clearly what is so critical about this problem. It emanates from the research problem. A good statement of the problem should contain 3 key information: Statement of Need, Statement of Knowledge Gap and Statement of Researchers Intuition. Lets explore these truths together in this lesson.
Research is a very systematic process which is carried out with clearly defined objectives. Objectives are the focus of the study and should be stated in a SMART manner. Research questions are the questions that the research seeks to answer. Ideally, research questions should be more specific than the the objectives. Research questions should be investigative in nature; this means that they should not be yes and no response questions. When stating research questions, we use WHAT, HOW and TO WHAT EXTENT. Do these question tags mean anything? Of course they do and this has been explained in the lesson. Finally, hypotheses show the relationship between variables; its an educated guess that is tested mainly at 95% to determine whether there is empirical evidence to support (fail to reject) or not support (reject) the hypothesis. Welcome as we explore these elements of scientific research.
This lesson brings to a close the discussion on Elements of Scientific Research. So far, we have discussed the following elements: Concepts, Constructs, Variables, Research Problem, Research Objectives, Research Questions and Hypotheses. In this lesson, we are going to discuss Relations, Definition of Terms, Theoretical and Conceptual Framework.
Variables are said to be related if a change in the value of one brings a change in the value of the other i.e. when we say that there is a relationship between X and Y, we are saying that a change in X brings a change in Y. In statistics, relationship is established by calculating correlation coefficient, denoted as r. Correlation coefficient plays two roles: to determine the strength/magnitude and determine the direction.
Concepts are defined by conceptual definition while variables are defined by operational definition.
A theory is an explanation of a phenomena after observing it for a long time. Therefore every problem has a theory behind it and that is what theoretical framework is all about.
A conceptual framework is a mental picture that shows the relationship between variables. It is drawn by the researcher and should be explained.
Relations, Definition of Terms, Theoretical Framework & Conceptual FrameworkRelations, Definition of Terms, Theoretical Framework & Conceptual FrameworkRelations, Definition of Terms, Theoretical Framework & Conceptual FrameworkRelations, Definition of Terms, Theoretical Framework & Conceptual Framework
This revision lesson will address the relationship between concepts, constructs and variables. Concepts describe the empirical world; concepts that can be measured and they vary are called variables while concepts that are not observable and not measurable (or are less observable and measurable) are called constructs.
For instance: a man is a concept; gender is a variable while pain is a construct.
This lesson describes 5 types of variables that a social researcher measures in their study. These are independent and dependent variable, intervening or mediating variable, extraneous variables and moderating variables. The lesson will use practical examples to differentiate the variables.
Scales of measurements are one key area that the researcher should have at their finger tips. In Revision lesson 2, we have said that variables are measurable. The measurability of variables is not done blindly, it is determined by the scale of measurement. There are four scales/levels. These are nominal which is the lowest, followed by ordinal then interval and the highest is ratio.
Two variables are said to be related if they systematically change when one of them is manipulated. The relationship between the variables is determined by calculating correlation coefficient. Correlation coefficient determines the strength and magnitude of the relationship but does not determine causality.
Welcome to this lesson where we shall anchor research on philosophy. Lets start by asking ourselves? What influences the decisions you make in life? This could be decisions regarding the school you take your children to, the kind of car you drive, the kind of neighborhood you live in and the type of institution you enroll for a higher degree. In real sense, these decisions are influenced by the beliefs and assumptions that you hold regarding a particular issue. Similarly, development of knowledge by researchers is influenced by the beliefs and the assumptions they hold.
In research, there are three assumptions that influences how researchers develop knowledge in order to answer research questions/problem. This regards:
The nature of knowledge (Epistemology)
The nature of reality (Ontology)
The nature of Values (Axiology)
This lesson will discuss in details each of these assumptions.
Researchers hold different views regarding the above. Disagreements on these brought about paradigms with each paradigm holding its view on knowledge, reality and values differently. In social science research, we have 4 paradigms: Positivism, Social Constructivism, Emancipatory and Pragmatism. In the lesson, each of the paradigm is discussed based on the assumptions they hold.
In our last lesson, we have discussed philosophical assumptions and research philosophies. Todays lesson will discuss the approaches to social science research that emanates from the paradigms. Research Approaches are classified using various elements.
There are various research approaches but this lesson will discuss the two main approaches that are applicable in social science research. These are Basic Vs. Applied approach based on the utility of research findings and Quantitative and Qualitative approach based on the types of data collected.
Basic research is the type of research where the findings have no immediate use. It is used to develop principles, theories and laws and it is mainly theoretical. Applied research is the type of research that is aimed at solving a particular issue as experienced by the client. It seeks to alleviate current problems in various fields and is mostly concerned with end-usage.
Quantitative research is the type of research approach which collects numerical data while qualitative research is the type of research approach which collects narrative data. These approaches emanate from positivism and social-constructivism paradigm respectively. Welcome as we explore more of these approaches.
Welcome to this lecture that enumerates the differences between quantitative and qualitative research. In lesson 9, we said that at every stage in your research (whether consciously or unconsciously), you will make a number of types of assumptions. These include: assumptions about human knowledge (epistemological assumptions), about the realities you encounter in your research (ontological assumptions) and the extent and ways your own values influence your research process (axiological assumptions). These assumptions lead to paradigms.
Each of the paradigms explained in lesson 9 leads to research approaches which we have discussed in lesson 10. We have two main approaches: Basic Vs. Applied and Quantitative Vs. Qualitative. These two including their characteristics have been discussed. In todays lecture, we are going to explore the differences between Quantitative and Qualitative approaches. The two approaches have differences between they subscribe to different paradigms with different philosophical assumptions. While quantitative collects numerical data that is subjected to statistical analysis, qualitative collects narrative data that is inductively analyzed. Other differences are in terms of the purpose, reality, ontology, epistemology, sampling techniques, instruments used etc
Quantitative research is the type of research that collects numerical data. This means that variables are measured quantitatively. The design that enables collection of numerical data are the quantitative research designs. This lesson will discuss quantitative research designs.
A research design is a plan that enables a researcher to determine the methods of sample selection, instruments to use and methods of analyzing data based on whether the approach used is qualitative, quantitative or mixed methods.
There are 3 main quantitative designs: Survey, Ex Post Facto and Experimental. Survey describes the characteristics of a population at a particular time. There are 3 types of survey; Cross sectional survey, Correlational Survey and Longitudinal Survey. Ex Post Facto (or Causal Comparative Research) means 'After the Fact'. This means that the researcher investigates the causes after the effect has been observed on the dependent variable. However, the researcher is not able to manipulate the independent variable. It is similar to correlational survey in that both establishes relationship. However, correlational establishes relationship between variables in a single group while causal comparative establishes relationship between groups. Experimental design is unique because it establishes causality. This means cause and effect relationship. There are two categories of experimental design: True and Quasi Experimental.
As you go through this lesson, check also lesson 8 on correlation to remind yourself on how correlation is measured and interpreted.
Experimental design is a quantitative design that is unique because it determines causality. Causality determines cause and effect i.e. manipulation of X (independent variable) causes a change in the Y (Dependent or outcome variable). This lesson explains experimental design in details. We shall start by explaining the meaning of experimental design. As we have said in this introduction, experimental design is a quantitative design that measures causality.
The lesson will also discuss how causality is demonstrated. Causality is demonstrated by use equal numbers of two homogenous groups. One group is called the control group while the other group is the experimental group. Treatment is given to experimental while no treatment is given to control group. A pre-test and post test is given before and after the treatment respectively to determine whether a change has been brought about by the treatment or intervention.
To determine causality, two factors are key: ensure you avoid spurious relationships and control all extraneous variables. This lesson explains how to avoid a spurious relationship and how to control extraneous variables.
Finally, the lesson discusses the elements of an experimental designs and types of experimental procedures. There are two key types: true experimental design where randomization is feasible and quasi experimental where randomization is not feasible. Randomization means that every member of the population has an equal chance of being selected and assigned to either experimental and control group.
Welcome to this lesson where we are going to discuss threats to internal and external validity of experimental designs. Experimental procedures establishes causality, i.e. it allows the researcher to conclude that variable X causes variable Y. For a researcher to make this conclusion, s/he must ensure that there are no spurious relationships and all extraneous variables are concerned
Threats are factors that threatens the confidence of a researcher to conclude that X causes Y.
There are two types of threats:
Threats to internal validity of the experimental design
Threats to external validity of the experimental design
Internal and external validity are concepts that reflect whether or not the results of a study are trustworthy and meaningful. This lesson will discuss these concepts in details.
So far we have discussed quantitative research and quantitative research design. We said that quantitative research is the type of research that collects numerical data. We have three main quantitative designs: we have Survey (which can either be Correlational, Longitudinal and Cross-Sectional), Ex Post Factor or causal Comparative Research and Experimental which can either be true or quasi. We have covered this in lesson 12-14.
In this lesson, we are going to discuss qualitative research. Qualitative research is different from quantitative because it collects data that is narrative, that is data that is in form of words, pictures and videos. This type of research is also carried out in the natural setting of the phenomena. It is from this unique type of research that in this lesson, we shall first discuss the characteristics of qualitative research. There are about 10 distinctive characteristics of qualitative research.
There are situations that call for qualitative research. For instance when you need to explore a context in depth. So this lesson has listed the areas that calls for qualitative research.
Issues of validity and reliability are difficult to measure in qualitative research. Quantitative researchers accuse qualitative researchers that their studies cannot be 'believed'. This has forced the qualitative researchers to identify four criteria that ensures that their research work is trustworthy. This issue is well discussed in this lesson.
Qualitative research relies on different methods of data collection. This is referred to as triangulation. The four types of triangulation are discussed and finally the steps of conducting qualitative research. Remember that qualitative research plan is emergent therefore the steps are are not as prescribed as we have in quantitative research.
We have discussed Qualitative research method in details in lesson 15. This lesson will discuss the five qualitative designs. These are Case Study, Ethnography, Phenomenology, Grounded Theory and Biography / Narrative Research. These designs help researchers to collect narrative data. Regardless of the design one selects, the researcher is the main research instrument and must become an insider in the natural setting of the phenomena.
Case study is an investigation of one case which can either be a person, a school, a process, a community etc; Ethnography studies a peoples culture; Phenomenology studies lived experiences; Grounded Theory is a study that results in the development of theories while Narrative research is the study of a person as told by the researcher.
Mixed Method research is an approach that emanates from pragmatism paradigm. It does not subscribe to one approach but mixes quantitative and qualitative research methods. Mixed Method research is a systematic inquiry which mixes both qualitative and quantitative approaches simultaneously or sequentially in a single study or a series of studies in data collection, analysis and interpretation of findings.
There is a difference between mixed-method and multi-method research. Multi-method uses more that two designs from the same approach. This means using two or more quantitative designs or two or more qualitative designs. In this lesson, we are going to introduce mixed method research by discussing the definition, strengths and limitations.
In lesson 17, we have defined mixed method research as that type of research where a researcher mixes quantitative and qualitative designs either concurrently or sequentially. This lesson is a continuation of lesson 17 where we are discussing the MMR designs or strategies. These are the designs that a research may employ to collect both quantitative and qualitative data in a single study or a series of studies. MMR grew from the concept of methodological triangulation which refers to the use of more than one research method.
There are two key researchers who came up with the types of methodological triangulation. This is Denzin who came up with Within-methods triangulation and Between- methods triangulation. Within-methods triangulation is the same as multi-method research while between-methods triangulation is the same as mixed-method research. Morse came up with concurrent and sequential triangulation. Concurrent methodological triangulation means that the two methods are conducted simultaneously i.e. at the same time while in sequential, one design informs the other design.
With that Creswell came up with 4 factors to consider when using MMR. These are weight, timing, mixing and theories. From these 4 factors, Creswell came up with 4 MMR designs: 2 concurrent and 2 sequential. Further development led Bryman to come up with Priority-Sequence Decision Principle and from that principle, he came up with 9 MMR designs/strategies.
Watch Lesson 17 before Lesson 18 because lesson 18 is a continuation of lesson 17.
In lesson 1, we said that Research is a systematic, scientific and objective search for knowledge (https://youtu.be/se_JAiAyNWU). This means that there are defined steps that should be followed when conducting research.
In this lesson, we are going to discuss steps that are followed when conducting quantitative research. You may be asking yourself, why quantitative research? This is because quantitative research's' plan is quite predictive. It is therefore possible to have a starting point and an end point. In lesson 15 (https://youtu.be/2SxeRbnHNs8), we discussed, steps followed when conducting qualitative research. Remember, qualitative research plan is quite emergent therefore its a back and forth process.
There are researchers who advocate for a six-step process while others advocate for eight-step process. In this lesson, we shall discuss the eight-step process.
Have you ever asked yourself why hypotheses and theories in social science are tested at 95% confidence level? This is because you can never be 100% sure that the results you are presenting are 100% true. Therefore we leave 5% room for making an error.
Social science research is carried out with people and so bias and errors are almost invariably present in a research study. There are various errors that affect the research findings. We may have errors during measurement, processing data, analyzing etc. This lesson will discuss measurement errors.
Measurement is central in social science research. Measurement refers to assigning numbers to observations. When we are collecting data, we are using research instruments or tools to measure variables. Therefore, when measuring something, error is any deviation from the “true” value.
This lesson will introduce us to errors that may arise when one is measuring.
The reason for conducting research is to search for knowledge so that we can answer the research problem. This therefore needs that data collected must be of high quality so that we can get quality solutions. Therefore, the instruments used to measure the variables must have certain characteristics. The first characteristic is validity and the other one is reliability. These two characteristics evaluates the quality of research instruments. If the instruments are of good quality, then data collected will also be of good quality.
Validity refers to accuracy in measuring the intended construct. There are three common types of validity: content, construct and criterion-empirical.
Content validity refers to the extent to which a measuring instrument has the content of the variables and the indicators. There are two types of content validity: face and sampling validity.
In Lesson 21, we have introduced the concept of validity. We have defined validity as the usefulness or appropriateness of the inferences that a research makes. We have used a watch to explain the concept.
We have also said that, validity pertains to the results of the research and not the tool. There are three commonly types of validity that are applicable in social science research. These are content validity, construct validity and criterion-related validity. In lesson 21, we have explained content validity in details and the methods of determining content validity.
In Lesson 20, we said that measures that are free of random errors are said to be reliable. Reliability is the degree to which a measuring instrument or tool is consistent or demonstrates consistency on repeat trials.
There are two main methods of estimating reliability;
Repeated measurements and
Internal consistency.
In this lesson, we shall discuss repeated measurements method.
Repeated measurement method means that reliability is determined by administering an instrument to the respondent, take the score then after some time administer the same instrument to the same respondents and take the second score. Then correlate the two scores to obtain correlation coefficient value which is the reliability coefficient value.
There are three methods of determining reliability under repeated measurement method. This is test-retest, Alternative forms and Equivalent forms method. All these three are discussed in this lesson.
In lesson 23, we have defined reliability as the measure of stability of a test. We have also said that there are two main methods of determining reliability. This is repeated measurements and Internal Consistency method. Under repeated measurements, we have three main reliability tests: Test-retest, Alternative forms and equivalent forms.
Lesson 24 will discuss internal consistency methods of determining reliability. Internal consistency method of determining reliability indicates the degree of homogeneity among items in an instrument. It is estimated by determining the degree to which each item in a measure/instrument correlates with each other item in the same measure/instrument.
Internal consistency is based on a single administration of a measure. There are two types of Internal Consistency reliability:
Split-Half and
Alpha Coefficient methods
In this lesson, we shall discuss Split-half. This is where a measure is split into two before analysis to create two sets of tests. Each section is scored separately from the other section. Then a correlation coefficient is determined by correlating the two sets of scores.
This lesson will also demonstrate how to use SPSS to determine split-half. SPSS (Statistical Package for Social Science) is a software that analyses quantitative data.
Make sure you go through lesson 23 before lesson 24 so that there is coherence in your learning. This is the link to lesson 23 - https://youtu.be/8Pl9CXI23oo
In lesson 24, we have discussed internal consistency methods of determining reliability. Internal consistency method of determining reliability indicates the degree of homogeneity among items in an instrument. It is estimated by determining the degree to which each item in a measure/instrument correlates with each other item in the same measure/instrument.
Internal consistency is based on a single administration of a measure. There are two types of Internal Consistency reliability:
Split-Half
Alpha Coefficient methods
Split-half method and how to determine split-half reliability tests has been discussed in details in lesson 24.
In this lesson, we are discussing the second method of determining internal reliability which is Alpha coefficient method. We have two types of Alpha coefficient: Cronbach Alpha and Kuder-Richardson. Cronbach Alpha is mainly used for Likert kind of scale questions while KR 20 is used for knowledge questions.
This lesson will also demonstrate how to determine Alpha reliability using SPSS. Make sure you watch the lessons on reliability for you to have flow of content. The links are shared below: Lesson 23: Repeated Measurement Methods of Determining Reliability (https://youtu.be/8Pl9CXI23oo)
Lesson 24: Split-half Reliability (https://youtu.be/JudCvpWuV7g)
We have so far discussed validity and reliability in quantitative research. When it comes to qualitative research, some scientists question the validity and reliability in qualitative findings. In lesson 15 (https://youtu.be/2SxeRbnHNs8), we said Positivists normally questions the trustworthiness of qualitative research. This is because the researcher is the main instrument so the prospect of other researchers producing identical data and arrive at identical conclusions are equally slim. That is why qualitative researchers have come up with terms to explain accuracy rather than using the term validity. They talk of credibility and trustworthiness.
In this lecture, we are going to discuss the 8 methods of determining credibility in qualitative research.
We have mentioned in Lesson 26 that Positivists normally questions the issues of validity and reliability in qualitative research. This is because the researcher is the main instrument so the prospect of other researchers producing identical data and arrive at identical conclusions are equally slim. That is why qualitative researchers have come up with other terms to explain the two concepts. This lesson is going to discuss reliability which qualitative researchers refer to as dependability.
The use of sampling is a strategic decision by the researchers to focus on some, rather than all, of a population of interest. This is premised on the fact that it is possible to produce credible results without the need to collect data from each and every member of the population. This lesson will first explain 12 terms that are used in sampling. These terms are population, sample, sample size, sampling, sampling frame, subject, element, statistic, parameter, response rate, randomization & precision.
The second part of this lesson will discuss the 6 purposes of research. We shall be asking ourselves, is it prudent to use the whole or using the part is better? Finally, we shall explain the limitations of sampling.
In Lesson 28, we have defined a sample is a subset of the population that is chosen for participation in a study. Determining the adequate sample size is the most important decision that a researcher needs to make. Contrary to popular opinion, determination of sample size is a scientific process that requires the researcher to think through it carefully based on the research problem.
Like we said in Lesson 29, sampling is one of the critique decision that a researcher needs to make. This is because without an adequate sample who will respond to the research instruments, then the researcher cannot answer the research problem.
Quantitative research is that type of research which collects numerical data. We discussed Quantitative research in Lesson 12-19. Sampling in quantitative research uses Probability, random or quantitative sampling techniques.
This lesson is going to discuss random or probability sampling technique. This type of sampling allows each and every member of the population the chance to be selected as a sample. That is why it is called probability. In addition, the selection of the sample is random meaning that the selection is dependent on randomness.
For you to select the sample randomly, a researcher must generate random numbers. These are the numbers that determines who will be selected and who will not be selected. By this, we mean those who will take part in the study and those who will not. There are manual and electronic methods of generating random numbers. This lesson will take you through how to use the internet to generate random numbers.
Simple random sampling is the simplest design to use under random sampling which we have introduced in lesson 30. When we talk about random sampling, we mean that each and every member of the population has an equal chance of being selected to be part of the sample. The selection is random hence the use of random sampling.
Simple random sampling has a similar definition. In simple random sampling design is the design where each and every member of the population has an equal chance of being selected to be in the sample. Simple random sampling uses random numbers which are generated electronically. We discussed how to generate random numbers in Lesson 30.
This lesson will take you through the following:
Meaning of simple random sampling design;
Steps followed when using simple random sampling design;
Strengths and limitations of simple random sampling design
To stratify is to group a heterogenous population into homogenous sub-groups that have common characteristics. Therefore, Stratified sampling techniques are generally used when the population is heterogeneous, or dissimilar or where certain homogeneous, or similar, sub-populations can be isolated. Stratified sampling does not operate on its own. Once you stratify, you then need to simple random within the strata.
This lesson will discuss:
The meaning of stratified random sampling design
Steps followed when using stratified random sampling design;
Strengths and limitations of stratified random sampling design.
Systematic sampling design is another random sampling design where the selection of subjects is dependent on a system. The system is to select every nth or kth number and then selecting at equal intervals until an adequate sample is achieved.
To determine n or k, we divided the sample size from the population. It is also important to note that the starting point is randomly selected and not necessarily the first on the list.
This lesson discusses the following:
The meaning of systematic random sampling design
Steps followed when using systematic random sampling design
Strengths and limitations of systematic random sampling design.
Cluster sampling is a form of random sampling where the entire population is divided into groups or clusters and random sampling is used to select specific clusters;
Cluster sampling is similar to simple random technique. The difference is that in simple random design, the individual is the subject while in cluster sampling, the cluster is the subject i.e. in the selected clusters, all the persons or items are included in the sample to ensure representativeness.
This lesson will:
Explain the meaning of cluster random sampling design;
State the steps followed when using cluster random sampling design;
Explain the strengths and limitations of cluster random sampling design.
Multi-stage sampling is a form of random sampling where samples are selected in a sequence of stages where each sample is drawn from within the previously selected sample. It is similar to cluster sampling only that while cluster sampling conducts a complete enumeration of all the people in the cluster, multi-stage samples within the cluster. Sampling in multi-stage occurs in stages.
This lesson will complete the discussion on the 5 random sampling designs. In this lesson, we shall discuss:
The meaning of multi stage sampling design
Steps followed when using multi stage sampling design
Strengths and limitations of multi stage sampling design.
Non-probability sampling designs also called qualitative or non-random are the designs where the probability of each and every person being selected to be part of the sample is unknown. This technique deals with information rich sample based on the problem of the study.
This sampling technique is associated with qualitative research where generalizations is not the end result. There are four main non-probability designs. These are convenience, purposive, quota and snowball. This lesson will discuss the 4 designs in details.
Sampling is such an important part of research that without proper sampling, then the researcher will not have adequate sample from which to collect adequate data from. This in turn means that the research questions will not be adequately answered.
Sampling is a systematic process. There are six steps that are followed when conducting sampling. This lesson will take you through the the sampling process and discuss in details each and every step and what it entails.
Before going through this lesson, make sure you have gone through lesson 28-36
Data collection is an extremely important process in research because without it you cannot answer the research questions, test hypotheses, make recommendations and conclusions. The decision on which methods of data collection will be used to answer the research problem should be made at the development of the problem. At this point the researcher needs to ask him/herself which method and which instrument will answer the research questions.
Selection of the method of data collection depends on many factors. Among them is the approach of research because the approach determines whether data collected will be numerical, narrative or both.
This lesson is an introduction method. It will differentiate between an instrument and a method, types of data, sources of data and factors to consider when selecting a method of data collection.
Questionnaires are very common instruments that are used in social science research. Why is it common? What is a questionnaire? What are the type of information that a questionnaire should seek from the respondents?
These questionnaires including designs of constructing questionnaires, rules followed when constructing a questionnaire and the factors that determine the success of a questionnaire as an instrument will be discussed in this lesson.
In Lecture 39, we have said that a questionnaire is the most common instrument that is used in data collection. In this lesson, we are going to discuss the four main steps that are followed when designing a questionnaire. We shall also discuss the design of closed-ended and open-ended questions in a questionnaire.
Likert Scale is a scale that determines the liking or not liking towards an objective. It collects quantitative data. In a Likert scale each statement is weighted from 1 to 5. However, the issue of whether Likert collects continuous or categorical data should be made at the construction state. This is because, the score of 1 -5 for categorical data does not carry any quantitative value. However, if Likert is collecting continuous data, then the weight carry quantitative value.
This lesson will introduce to:
Meaning of a Likert Scale
Type of data collected using a Likert scale
Guidelines that should be followed when constructing Likert Scale
Myths about Likert Scales
Is there a difference between an interview and a conversation? What are the instruments that are used to conduct an interview? What are the types and structure of an interview? Are there skills that an interviewer needs to possess? These and much more will be answered in this lesson.
Interview is the second method of data collection that we are discussing. So far we have discussed Administration of Questionnaires as the first method (not that this is not in any order) and the instruments used in this method as questionnaires and interview schedule.
Under interviews, we are going to learn the types of interviews, the instruments used to conduct an interview, structure of an interview and skills that an interviewer needs to possess.
A focus group is a carefully planned discussion designed to obtain peoples’ perceptions, feelings and ideas on a specific topic in a permissive & non-threatening environment. These people are moderated by the researcher
In this lesson, you will learn:
The meaning of Focus Group Discussion;
Three features of Focus Groups;
Rules to be followed when conducting Focus Group Discussions.
Unlike questionnaires and interviews that relies on other people (respondent) to give the researcher the information s/he requires, observation requires the researcher to collect data himself through recording. S/he does not require another person to give him/her the information but s/he collects it through the use of his/her eyes.
Observation is a qualitative method of data collection. It uses an observation guide as an instrument for data collection. However, this guide should be structured so that all researchers can observe and record the phenomena in the same manner.
Document analysis relies on the use of documents to collect data. These documents may be written by the author or written on behalf of another person. This method is purely qualitative method and the instrument used to collect data from documents is called a document analysis guide. This lesson will conclude our lessons on methods of data collection.
This lesson will explain:
The meaning of document analysis as a method of data collection
The types of documents available to a researcher
The sources of documentary data
The methods of determining credibility of documentary data.
Data Analysis is such an important element in research because without analyzing data then you cannot answer the research questions. There are two forms of data: Numerical data is analyzed using statistics whereas narrative data is analyzed using thematic induction.
In this lesson and the coming lessons, our concentration will be on numerical data analysis. In this lesson, we are going to discuss terms that are relevant to remind ourselves as we discuss data analysis.
Data collected from the field needs to be analyzed, interpreted and presented to the audience of research. There are two ways in which numerical data can be analyzed: using descriptive statistics or inferential statistics.
This lesson will discuss descriptive statistics. This means the kind of analysis that limits generalizations to the sample data.
There are three ways of summarizing data descriptively:
Tabular
Graphical
Numerical These three methods are described in details in this lesson.
Inferential statistics makes inferences and predictions about a population based on a sample of data taken from the population in question. It is based on probability (to infer). It is a measure of the confidence we have in our descriptive statistics.
This lesson will introduce us to inferential statistics. We shall discuss the meaning of inferential statistics, types of hypotheses and use of hypotheses in inferential statistics.
Statistical tests provides a mechanism for rejecting or failing to reject a hypotheses. There are two types of statistical tests. These are parametric and non-parametric tests. Parametric is mainly for data that is measured at the scale level while non-parametric is for data that is ranked,
There are three forms of statistical tests: Correlation, Regression and Comparison test. This lecture will take you through:
Meaning of statistical tests
Types of statistical tests
The three forms of statistical tests.
One of the most common question that a researcher asks during data analysis is ‘Which statistical tool should should I use to analyze my data’ This lesson will take you through the factors that you need to consider when choosing a statistical test.
The outcomes for this lesson are:
State the factors to consider when choosing statistical tests
Identify the various types of statistical tools.
This lesson introduces you to the research proposal. Research proposal is a statement of intent which the researcher develops after identifying the research problem. It is thus prudent that the researcher develops a workable proposal.
This lesson will take you through:
The meaning of a research proposal
Importance of writing a research proposal
The structure of a research proposal. Under the structure, we shall discuss the preliminary pages, the main body, references and appendices
Chapter one of the research proposal is titled Introduction. Under this Introduction, we have 12 sections. The first one is Background to the study while the second one is the statement of the problem. This lesson discusses these first two sections of the first chapter of the research proposal.
After writing the background to the study and the statement of the problem, the next section is to state the purpose of the study. The purpose of the study is the same as the general objective of the problem.
The purpose is followed by specific objectives of the study and the research questions. Some institutions only write one of this. With the purpose, you may not need to write the objectives of the study. In contrast, there are others who will require all the three to be written. Make sure your structure is as per the approved structure in your discipline.
A hypothesis is a prediction about the relationship or the difference between variables. This lesson will explain the meaning of hypotheses and the two commonly stated hypotheses in social science research. These are the Null and the Alternative Hypotheses.
This lesson discusses 3 sections in the research proposal:
1. Research is done because it is significant and that is why we write significance of the study
Delimitations are the walls the research puts round his/her study;
Limitations are the unforeseen factors that may hinder the researcher from achieving his/her objectives
This lecture will conclude chapter one of the research proposal by discussing: assumptions of the study, definitions of significant terms which is the same as operational definition of terms and finally organization of the study.
From Lesson 51-56, we have discussed chapter one of the research proposal. From now until lesson 60, we shall discuss chapter two of the research proposal which is referred to as Literature Review.
Literature review entails extensive review and evaluation of literature that is related to your subject matter. Since research is anchored on literature, then it means that a lot has been written concerning your problem.
This first lesson is an introduction lesson. In this lesson, we shall: a) Explain the meaning of Literature Review; b) State the purpose of Literature Review; c) Identify the factors to consider when determining the scope of Literature Review
Literature review is not a haphazard process. Its a carefully thought out process that is highly systematic following distinct steps. Before beginning the process of literature review, it is important to identify the sources of literature.
This lesson will take you through:
Sources of Literature Review;
Steps that are followed when conducting Literature Review;
The most common online databases that a social science researcher may search literature from.
A theory is an explanation of phenomena after observing it for a long time. Theoretical framework is that section of the research proposal where the researcher describes the theory in which s/he is anchoring their study on.
This lesson will:
Explain the meaning of theory;
Discuss how to identify a theory to anchor your study on;
Discuss the steps of stating a theory in your study
A conceptual framework is a conception or a model of what you plan to study i.e. it defines the focus and direction of the study by organizing the key concepts and variables.
In this lesson, we shall:
Explain the meaning of a conceptual framework;
Explain the three sources of a conceptual framework;
Identify the two main methods of presenting a conceptual framework. A conceptual framework should always come after the theoretical framework.
Why is Chapter Three of the Research Proposal referred to as Research Methodology? Research Methodology refers to an explanation of methods. So then what are research methods? Methods are tools of conducting research.
This lesson will introduce you to Chapter three of the research proposal by first differentiating between Research Methods and Research Methodology.
The first section in Chapter three of the research proposal is the Research Paradigm. However, this may differ based on the discipline and the academic level of the student.
We discussed Paradigms in Lesson 9. Therefore before going through this lesson, first revise lesson 9 (https://youtu.be/-9PmIUAdGKk)
Definition of a research paradigm gives the research focus and direction. This lesson will remind you the meaning of a paradigm; the three basic questions about ones beliefs; and the three paradigms that a social science researcher anchors his/her study on.
Finally, we shall discuss the requirements of section 3.2 in terms of what is expected of the researcher in this section
In lesson 62, we have said that a research paradigm provides focus and direction to your research. Once the researcher states the paradigm, s/he identifies the plan that the study will use to collect and analyze data. This plan is called a research design. Without a plan, then the researcher cannot answer the research questions or test hypotheses.
It is important to note that there is no 'fit for all design'. Research design is informed by the paradigm. We discussed research design in Lesson 12 -18. So make sure you will first watch the 7 lessons before this lesson.
This lesson will:
Explain the meaning of a research design;
State the elements of a research design;
Identify Quantitative, Qualitative & Mixed Method Research design;
Explain the requirements of section 3.3
Section 3.4 of the research proposal discusses the target population from which a sample will be drawn. Target population refers to the population that the researcher wishes to study and the results of the study will be generalized to them. This population is also referred to as accessible target population because it is from this population that we shall draw our sampling frame.
In this lesson, we shall:
Explain the meaning of target population;
Differentiate between target & accessible population;
Explain the requirements of section 3.4
This lesson takes you identification of sample size and sampling techniques or procedures. Before going through this lesson, make sure you first go through the Sampling Lessons on Lesson 28-37.
It is important to note that this section starts from identification of the sample size. Sample size is drawn from the Target population which we have discussed in Lesson 64. Sample size is not drawn haphazardly . There are scientific theories that we use as researchers to draw the sample.
Once the sample size is identified, then you determine the technique(s) that you will use to draw the sample. This now calls for determination of the sampling procedures. Again, determination of the sampling procedures is dependent on the research approach that the study has adopted.
This lesson will thus take you through:
The meaning of sampling, sample and sample size
The theories of determining sample size
The sampling techniques emanating from the two main research approaches
The requirements of section 3.5
Data collection is the process of gathering, measuring, and analyzing accurate data from a variety of relevant sources to find answers to research problems, answer research questions, and test hypotheses.
This lesson will discuss:
The difference between Data Collection Methods & Data collection Instruments;
The four main methods of data collection;
The instruments that are used with the methods in (2) above
The requirements of section 3.6 & 3.7
Lesson 66 has taken us through the instruments that we use to collect data for quantitative and qualitative research. We have also discussed the data collection procedures.
In this lesson, we are going to discuss section 3.8 of Chapter three of the research proposal. This section deals with data analysis technique.
In Lesson 46-50, we have discussed Data Analysis Techniques in details.
A research can collect numerical and narrative data. This lesson will concentrate on how to analyze numerical data.
At the end of the lesson, you should be able to:
Explain the meaning of data analysis;
State the types of data analysis & statistical tests;
Identify statistical tools to use under descriptive & inferential statistics;
Explain the requirements of section 3.8
In Lesson 67, we have discussed how to write section 3.8 when the data you anticipate to collect is numerical data. In this lesson, we are going to discuss the steps you follow when analyzing data emanating from qualitative research. This is narrative data that is analyzed using thematic or inductive analysis method.
Qualitative research data is mainly narrative and its analysis involves a number of steps that we shall discuss in this lesson.
This lesson aims to achieve the following:
Discuss qualitative data analysis;
Explain the steps followed when conducting qualitative data analysis;
Explain the requirements of section 3.8 when data is narrative.
Social science researchers rely on people to answer the research questions. That is why ethics are central to the research process. Researchers need to take care of various ethical issues at different levels of this process. Ethics are the norms for conduct that distinguish between acceptable and unacceptable behavior.
They can be written or unwritten but they govern our expectations of our own and others’ behavior; Research ethics are the norms that govern how research is conducted and the findings disseminated. This lesson will introduce you to the ethical considerations that you need to bear in mind as you conduct research.
The outcomes of this lesson are:
1. Explain the meaning of Ethics;
2. Discuss the ethical principles of research;
3. Explain the requirements of section 3.9.
The last section in Chapter three is a table that tells the reader how the researcher has operationalized the variables. This table is called the Methodology Matrix Table or Operationalization of Variables Table.
To operationalize means how the researcher has measured the variables. Remember we said measurement does not mean data collection but data collection is part of measurement. Measurement is broad and covers scales of measurement, indicators as per the conceptual framework, methods of data collection and methods of analysis. That is why this table has a number of columns that captures how the variable has been operationalized.
Chapter Four is the Chapter where the researcher shows how they have analyzed data. After analysis, data should be presented, interpreted and discussed. This lesson will first introduce us to the structure of chapter four and how the researcher should organize the chapter. In addition, we shall look at some pitfalls to avoid in this chapter.
The learning outcomes for this lesson are:
a) Discuss the structure of Chapter Four;
b) Identify pitfalls to avoid while analyzing data.
This lesson discusses the meaning of data analysis, presentation, interpretation and discussion of findings. Using example of a research title, the lesson will take you through what s/he is expected to write under the four headings.
This lesson will explain the meaning of the various components in Chapter Four (These components stem from the title of Chapter Four)
So far we have discussed Chapter One titled Introduction, Lesson 51-56; Chapter Two titled Literature Review, Lesson 57-60; Chapter Three titled Research Methodology, Lesson 61-70; Chapter Four titled Data Analysis, Presentation, Interpretation and Discussion of Findings, Lesson 71 & 72. This lesson is discussing the last Chapter of a research project, thesis or dissertation.
In this chapter, the researcher is expected to summarize findings, make conclusions, recommendations and suggests areas of further research. This lesson will discuss this structure giving practical example as well explain what is expected in each component.
There are various referencing styles that academicians use in their work. The commonly ones are the MLA (Modern Languages Association) system, the APA (American Psychological Association) system, the Harvard system, and the MHRA (Modern Humanities Research Association) system.
In Social science research, APA is more used than the other styles. In 2019, APA 7th Edition was launched which replaced the 6th Edition which had been in use since 2009.
APA 7th edition came with a number of changes because of the changes that were happening across the globe and especially in the academic world. For instance, the use of online materials, the use of biased language in research etc.
APA 7th Edition was meant to replace the 6th Edition from the year 2020.
This lesson will introduce us to the differences between the two editions
In Lesson 74, we have discussed the notable differences between APA 6th and 7th Edition. With these differences, this lesson will take us through how to cite books and journals in our academic work
Every person in academia is expected to publish academic papers in reputable journals. These papers need to be formatted as per the APA 7th Edition guidelines.
This lesson presents the required sections in an academic paper and the optional sections. One thing that the author must bear in mind is that APA 7th Edition guidelines should be applied throughout the paper
Preliminary pages are the pages before the main body of your thesis, project or dissertations. In most institutions, these pages include the title page, declaration, dedication, acknowledgement, Table of Contents, Lists of Tables, List of Figures, Abbreviations & Acronyms and finally the Abstract.
APA 7th Edition has given the guidelines that should be followed when presenting these pages.
This lesson introduces us to the guidelines on the preliminary pages.
The main text of a thesis or dissertation has (in most institutions) Chapter One to Chapter Five; APA 7th Edition style of referencing should be applied in the whole document i.e. there should be consistency of pagination, font size and style throughout the document.
This lesson will discuss the following sections of thesis and dissertations:
Font size & Font Style
Use of bold
Spacing
Hanging headings and white space
Orphans and windows
Numbers and numerals
Margins & Alignments
Lesson 78 has discussed 7 sections of the main body that need to be formatted as per the APA 7th Edition guidelines.
Lesson 79 focuses on:
Lists and Bullets
Tables and Figures
Appendices
Quotation(s)
References
Abbreviations
