A COMPREHENSIVE GUIDE TO DISSERTATION RESEARCH

DISSERTATION RESEARCH

Primary research can seem daunting for many students, even those who are postgraduates or have a good understanding of the dissertation process. However, we're here to ease the tense nerves you might feel if required to conduct research for your dissertation.

Students may be hesitant to do primary research for a variety of reasons. Students' anxiety about conducting primary research for their dissertations is frequently compared to the seeming insurmountable tension they experience before exams. This anxiety can be caused by a variety of factors, such as a lack of familiarity with primary research techniques, a dislike of statistics, or a lack of the necessary skills.

However, doing primary research differs significantly from taking tests. The former is far more interesting, satisfying, diverse, and, dare we say it, even enjoyable. You're in charge and have the power to make inquiries. Additionally, students who do primary research have the chance to contribute in little ways to their subject, which may feel very fulfilling. Many people are experiencing becoming a researcher for the first time rather than just a student.

We'll let you in on a little secret if you're laughing at our unrelenting enthusiasm for primary research as you read this: research isn't truly that difficult. Learning certain practises and understanding when to make precise judgments are required.

This is where this book comes in; providing detailed instructions on these steps and choices, it may help you both before and throughout the research phase of your dissertation.

There are several primary research approaches from which you may pick, as is shown below. Whatever methodology you choose, the first two phases are always the same; the following steps are determined by the methodology.

STEP 1 - DECIDE THE DATA TYPE

Your primary research begins with deciding on the data you will use. You can choose from either primary data or secondary data. This guide is focused on primary research, which means that it only covers primary data. It is helpful to learn a bit about each data approach.

The researcher has collected primary data. This type of data is most often used for primary research in your undergraduate and graduate programs. Primary data can be described as "real-time" data. This means that the data was collected during the research project. The researcher is responsible for data collection.

SECONDARY DATA: Secondary Data was already gathered by another source. It is frequently available from previous researchers or official sources. This information is referred to as "past data" because it has already been gathered. Since you don't need to gather the secondary data yourself, you can use it quickly. Due to the fact that secondary data was gathered with another research question in mind, it might not be pertinent to your project. Secondary information's veracity may also be questioned.

BIG DATA: The most complicated type of data is what is used in graduate and undergraduate studies. Three Vs are the hallmarks of big data: large amounts of data, variety in the data type and speed with which it is processed. Because big data is complex, traditional data processing methods are not applicable and you will need to be trained to understand how to process it.

STEP 2: SELECT A PRIMARY RESEARCH METHOD

You can conduct primary research using qualitative, quantitative, and mixed methods. We will discuss each one separately and then look at the steps you should follow depending on the method.

QUALITATIVE RESEARCH: This is exploratory. When quantitative studies on a topic are unavailable, qualitative research is used to try and discover the topic. This is accomplished by looking at the perspectives and experiences of specific individuals. Because they reflect a dynamic reality, rather than a static one, their particular meanings are crucial. Interviewing people can reveal a lot about their perceptions of reality.

QUANTITATIVE RESEARCH: The essence of quantitative research is confirmation. The basic goal of quantitative research is to use statistical studies to support or refute theories. Numerical data that is predictable and stable will be the main focus of quantitative research rather than dynamic data. By utilising large samples and trustworthy tools, you are attempting to make your findings more universal.

MIXED RESEARCH: Methodologies from both qualitative and quantitative research are combined. It allows you to learn more about a subject than if you employed just one approach. Typically, a mixed technique will start with qualitative research and go on to quantitative research.

A small-scale study is the first thing you do while researching a phenomenon. You then formulate a hypothesis that will be tested with larger samples. There are further mixed approaches available as well, which we shall cover later.

WHAT SHOULD YOU DO IF YOU HAVE CHOSEN A QUALITATIVE METHOD?

STEP 3: BE AWARE OF YOUR STRENGTHS AND LIMITATIONS

Qualitative research has the advantage of allowing you to explore a topic in great detail. You can focus your magnifying glasses on specific people and events. This in-depth view will help you understand the meanings, occurrences, and behaviours of your research topic. Qualitative research provides more detail than quantitative research. Qualitative research can still achieve many things. Because you're only able to study a small group of people, your findings cannot be generalised to the wider population. Qualitative research is more difficult to judge. Your ability to accurately interpret results without bias is a key factor in qualitative research quality. It might be challenging to come to an agreement or determine a "bottom line" when qualitative research combines diverse viewpoints.

STEP 4: SELECT A QUALITATIVE METHOD

You have many options when it comes to qualitative research methods. The most popular qualitative research methods are observation, focus groups, and interviews. Let's look at each one separately.

ONE OBSERVATION: As the name suggests, it's the act of observing people in their environment. Your role as a researcher is to observe the environment and become immersed in it. You can either be part of the behaviour of your participants or just observe from a distance. You will need an observation checklist. This checklist will enable you to track the behaviour of your participants.

Interviews are the most popular qualitative method. Interviews are based on predetermined questions. These questions seek to understand participants' understanding, opinions, and attitudes. You may choose to change the question structure depending on your research topic. Understanding participants' subjective perspectives are the main goal.

Focus groups work in the same way as interviews, except they involve more than one person. Focus groups are made up of several people, usually from diverse backgrounds. Your role is to engage them and to help them understand the topic.

You should record and then transcribe your interviews and focus group sessions.

Case studies are centred on a single individual or group that is pertinent to your study subject. These people or groups were picked because they present amusing, unexpected, or highly illuminating circumstances. Determine how the case study educates you as part of your task.

STEP 5-SELECT PARTICIPANTS

Before choosing your volunteers, you must first decide who they will be. Interviews and focus groups require a variety of people, but only one person or organization is required for a case study.

You must first provide an answer to your research question in order to identify these individuals or groups. Additionally, you must decide on the participant count (which is typically small in qualitative research) and whether participants should have comparable backgrounds. You should reflect on the following issues: What ought they to compare and what ought they to distinguish?

You must decide how to recruit your participants before you can select them. A predetermined environment is required for observation studies. This makes it easier to recruit your participants, since you already know their locations. For a case study, you don't need to recruit people because the subject of your investigation is already set.

Because participants in focus groups and interviews must come from a certain target audience, more complicated recruiting strategies are needed. The snowball method is a common way to recruit participants. You will need to find the common threads between your participants in order to recruit them to the same location.

Remember that all participants must sign an informed consent form before they are allowed to participate in research.

STEP 6: MEASURES TO BE TAKEN

Measures are used in qualitative research. These metrics, however, are less complex than those used in quantitative research.

A checklist is frequently included in observation studies so that you may record your findings. Focus groups, interviews, and the majority of case studies all make use of semi- or formal interviews. The questions used in semi-structured interviews are preset. However, structured interviews enable the examination of answers and predetermined queries.

Semi-structured interviews are best because you can get more specific responses in most cases.

You will need to create your own observation checklist when you use observations. You must prepare your interview questions before using them. Checklists for observation are often simple to create since they are preset. Participants' names (or ID numbers, if they choose to remain anonymous) and any other details you require might be included.

When creating interview questions, you must make reference to both your research topic and the pertinent literature. Ask generic questions that are pertinent to your research issue, such as "What drives you the most to play computer games," if the focus of your interview is on the reasons for computer gaming.

You might find out that people play games to feel competent. If so, you can ask your subjects, "Does playing games satisfy my need for competence?"

Always get advice from your supervisor before developing an observation checklist or interview questions.

STEP 7: CHOOSE ANALYSES

When analysing the findings of qualitative research, complex statistics are not necessary. This is achievable since you won't have utilised any numerical data. You must determine the participants' average age, as well as the proportions of each gender, educational level, and ethnicity.

Data analysis for qualitative research is focused on coding and identifying common themes.

Coding should not be difficult. Just look over your interview transcripts or your list of things to observe and underline any interesting answers or observations.

By organising coded responses and observations into patterns, you might uncover themes in your data. Even though it's a simple process, it's frequently incredibly fascinating. When it comes to coding your data and identifying themes, you have several possibilities. There are numerous options for data analysis. These include discourse analysis, interpretative and interpretative phenomenology as well as constant comparative, narrative, and thematic analysis. Let's take a look at each one.

The most common method is thematic analysis. This method is used to analyse the data, review the codes and find the themes. The interpretative phenomenological analysis is similar to thematic analyses. It aims to discover how an individual in a particular setting interprets a phenomenon.

To detect patterns or inconsistencies, one item of data (a statement, a subject) is constantly compared to all other items of data. For this comparison, the goal is to see how the data is related to each other. Characters' descriptions of their experiences are more important in narrative analysis, which also seeks motifs. The goal of discourse analysis, which also looks at language, is to comprehend how language affects people's attitudes and actions.

STEP 8: UNDERSTANDING THE PROCEDURE

It is simple to carry out qualitative research. You must decide where and when you will observe your participants (for observations) or conduct interviews with them after you have recruited your subjects (for interviews, focus groups, case studies, and interviews).

Through observations and interviews, you gain information. Interviews must always be recorded, followed by transcription. During observations, only observation checklists should be filled out.

You can analyse your data once it has been gathered, and then you can begin drafting your final report.

WHAT SHOULD I DO IF I HAVE CHOSEN A QUANTITATIVE APPROACH?

STEP 3: RECOGNIZE YOUR ADVANTAGES AND DISADVANTAGES

The benefits of quantitative research are numerous. You may pick a representative sample of the population using carefully thought-out participant selection procedures. As a consequence, you may generalise your findings to the entire population. Establishing causation and testing hypotheses are two purposes of quantitative research. You may establish causation and control factors (confounders) in quantitative research. Your quantitative research can be replicated if you use standardised procedures. Quantitative research has its limitations.

This research is, for instance, less effective at understanding deep perceptions of people as it averages their responses to obtain a "bottom line". Because research is often based upon self-reported measures, it is difficult to ensure that participants are truthful. Sometimes quantitative research is not sufficient to enable interpretation. Your results might not be as general or accurate if you don't choose the right measures and participants.

STEP 4: SELECT A CERTAIN QUANTITATIVE APPROACH

Your decision among the many quantitative methodologies will rely on the nature of your research problem. You can choose to do descriptive, correlational, experimental, or quasi-experimental research, in general.

Consider each of these independently.

When you wish to characterise the features of a population or a phenomenon, you conduct the descriptive study. When it comes to determining how many college students take drugs, descriptive research may be performed.

You are not attempting to determine the link between variables; rather, you are only describing the phenomena in the issue. Consequently, descriptive research is never employed to demonstrate causality.

When exploring the link between two or more variables, correlational research is conducted. In correlational research, the distinction between independent and dependent variables is crucial.

An independent variable is considered controlled if its effects on the dependent variable are investigated. When examining the link between critical thinking and IQ, for example, critical thinking is the dependent variable.

In terms of science, correlation examines the connection between the levels of an independent variable and a dependent variable (s). Remember that correlation only looks at the relationship between variables; it never establishes causality.

Additionally, you can take into account the impact of a third variable, also referred to as a covariate or confounder. After accounting for abstract reasoning, you might want to look at the connection between intelligence and critical thinking, for instance.

Critical thinking and intellect go hand in hand with abstract reasoning. You might wish to take this into account. By eliminating the intermediate component, you can explain how intellect, critical thinking, and other factors are directly related.

Experiments seek to determine causality. This distinguishes them from descriptive and correlational studies. Experiments change the independent variable to establish the cause.

As an alternative, investigations might look at how several independent factors affect the dependent variable. Here's an illustration: An innovative supplement may improve people's focus (an independent variable) (dependent variable). You must contrast its results. You'll give some of your participant’s sugar tablets to compare the effects of a supplement to a placebo.

The type of therapy is now the independent variable. This applies to both supplements and placebos. We may determine if the supplement improved concentration by contrasting the concentration levels of those who took the supplement with those who got the placebo (independent variable).

Between-subjects and within-subjects experimental designs are the two different types. Since the concentration levels of those who received a supplement and those who received a placebo were compared in the previous example, a between-subjects design was used.

However, you can also make comparisons within a single topic. For instance, you might want to find out whether taking a supplement before or after eating has a different impact on focus. The length of supplement administration is here the independent variable (with two conditions: before and after the meal). The same group of volunteers are then told to take the supplement both before and after meals on Days 1 and 2.

You are conducting a comparison within subjects because both conditions are applicable to every participant in your study. When allocating participants to a condition, you must guarantee that the assignment is random regardless of the research methodology employed.

A "quasi-experiment" is not a legitimate research study. Due to the lack of randomization, this is not a true experiment. You would employ a quasi-experiment if you classified your volunteers into distinct conditions based on a present trait.

For instance, you may like to determine whether youngsters are less prone to cheat on an exam than teenagers. You cannot utilise random assignment since you have divided your participants into age groups. As a result, it is sometimes claimed that quasi-experiments cannot demonstrate causation.

Nonetheless, they are a valuable instrument for examining variations between preset participant groups.

STEP 5: CHOOSE PARTICIPANTS

In comparison to qualitative research, the sample size in quantitative research is frequently much bigger. Large sample size in quantitative research, as previously mentioned, enables you to generalise your findings to a larger population.

To increase the precision of your results, it is strongly advised to use a G-Power analysis to determine the sample size required. You can find a tool for G-Power analysis online, which is based on the effect sizes, significance levels, and power of prior research.

In order to enter these values into a G-Power analysis, you must first identify studies that looked into a similar effect, then find out about their reported effect size, significance level, and power. There is a tonne of how-to manuals online.

You must ensure that the participants you choose for your quantitative study are representative of the sample population you intend to use. To do this, specify your inclusion and exclusion criteria.

If you're trying to reach depressed young moms, for example, you'll only include women who are under 35, have given birth, and have been diagnosed with depression. This means you'll exclude ladies who don't meet these requirements.

Keep in mind that you need the informed consent of your subjects, demonstrating that they have chosen to participate, just as you would in qualitative research.

STEP 6: SELECT MEASURES

Utilizing measuring instruments is a part of quantitative research. As a result, all variables employed in your research will be "operationalized" using certain metrics. These metrics are based on surveys that have previously been utilised in legitimate and trustworthy ways.

When a questionnaire has consistently produced consistent results in studies, it is considered reliable. It is also valid if it measures the things it was supposed to measure. A questionnaire can be considered valid and reliable if it has been shown to be valid and reliable in other studies.

Using a statistical tool like SPSS to determine a questionnaire's Cronbach's alpha value is another way to assess a questionnaire's dependability. Acceptable dependability is indicated by a value of 0.7 or above. High dependability is indicated by values over 0.8, while excellent reliability is indicated by values over 0.9. A score below 0.7 indicates unreliability.

You may always ask your supervisor for advice on which surveys would work best for your study. You can also look at earlier studies to see what kinds of questionnaires were used.

Each questionnaire you employ will need to have final results. Previous studies that made use of the same questionnaire can be consulted for instructions on how to calculate the final scores. A statistical software will be used to finish this computation.

Some of the components in this computation may be scored in reverse. A "5" response indicates agreement when a question like "Are you feeling well today?" is asked. Another question that could be asked is, "Are you feeling bad today?" Again, a 5-response rate means "completely agree." You will need to score the second question if your questionnaire measures how good a person feels. Higher scores indicate that a person is feeling more (rather than less) good. You can also use a statistical programme to do this.

STEP 7: CHOOSE ANALYSES

Students often have a hard time with statistical analysis.

There is no reason to, as the entire process of performing statistical analyses isn't difficult. You just need to know what analysis you should use and how to perform it. Let's look at some examples.

When you do descriptive research, you will need to use frequency and descriptive statistics for your analyses.

Calculating the means and standard deviations of continuous variables may be done using descriptive statistics. Frequency statistics can be used to calculate the frequency and percentage of responses to categorical variables.        

Continuous variables refer to variables whose final scores are wide-ranging. Because final scores might range from one year to one hundred, the age of participants, for example, is a continuous variable. If your participants had an average age of 37.7 years, for instance, this would be a good illustration.

Another illustration is a continuous variable. To determine a final score, you must use the questionnaire responses. Each respondent will get a final score of between 10 and 50 depending on the number of questions in your survey and how satisfied they are with the medical care they received. The mean and standard deviation of the whole sample may be calculated using this continuous variable.

Participants are divided into specific categories by a categorical variable, which does not result in final scores. Gender is one instance of a categorical variable. Your participants can be divided into male and female groups. In your final report, you'll mention that the participants were split equally between men and women.

For all forms of quantitative research, descriptive and frequency statistics must be used. Even if you are not conducting descriptive research, this is still true. You require these figures when discussing the demographics of your sample, such as age, gender, educational attainment, etc.

A correlation analysis, also known as regression analysis, is performed while doing correlational research. In order to answer the question, "Is intelligence connected to critical thinking?", correlation analysis is used to examine the relationship between two variables.

Verifying that your data is delivered normally is crucial. Indicating that the data's summary histogram exhibits a bell-shaped curve. A histogram may be generated with the help of a statistical tool. The regulations are available on the internet. A Pearson correlation study will be carried out if you establish that your data is consistently distributed. A Spearman analysis may be performed if your data is not distributed consistently. After accounting for covariates, you may include a covariate, such as people's ability to think abstractly, to assess whether there is a relationship between the variables.

The level of an independent variable may be used to predict the level of a dependent variable using regression analysis. Is there a connection between, say, IQ and the ability to think critically? The ability to concurrently account for a multitude of confounding variables is one of the most valuable features of regression analysis. If abstract reasoning, gender, educational attainment, and age of participants are controlled for, you may determine if intelligence predicts critical thinking. Resources on interpreting regression analysis can be found online.

You can use t-tests or ANOVA for experiments and quasi-experiments (analysis of variance). Unbiased samples When there is one independent variable, two conditions (such as administering a placebo or a supplement to participants), and one dependent variable, t-tests are utilised (e.g., concentration levels). This test is referred to as an "independent sample" since there are two distinct conditions.

This is an intersubject design, as noted above. With an independent sample t-test, you want to determine if the concentration levels of participants who received a supplement versus those who were administered a placebo are different. A paired sample t-test will be used if you have a within-subjects design. Because you compare two groups of participants under the same conditions (e.g., taking a supplement before or after eating), this test is called "paired".

A paired sample t-test can be used to determine whether there are any variations in concentrations (the dependent variable) between Time 1 (when eating a meal supplement) and Time 2 (while taking a meal supplement following the meal supplement).

ANOVA analysis comes in two basic flavours. When an independent variable has more than two conditions, one-way ANOVA is utilised.

Use a one-way ANOVA in a between-subjects design to investigate the effects of therapy type (independent variable) on concentration levels (dependent variable) using three treatments for the independent variable, such as a supplement (condition 1), a placebo (condition 2), and concentration training (condition 3).

When there are multiple independent factors, however, two-way ANOVA is used.

To check whether the kind of treatment (an independent variable with three conditions: supplement, placebo, and concentration training) and gender (an independent variable with two conditions: male and female) have any effect on the participants' capacity to focus, they may be explored (dependent variable).

Last but not least, MANCOVA is employed when there are one or more independent factors but also several dependent variables.

The MANCOVA method is used to investigate the impact of treatment type on two dependent variables (independent variable with three conditions: supplement, placebo, and attention training) (such as concentration and an ability to remember information correctly).

STEP 8: UNDERSTANDING THE PROCEDURE

It is very easy to conduct quantitative research.

When performing an experiment, you must randomly allocate people to conditions once you have gathered volunteers. You'll need a procedure to choose which participant will be exposed to which condition if you're conducting quasi-experimental research. For instance, when comparing them, you'll put kids and teens in the same category based on their ages. Participants in descriptive and correlational studies do not need to be categorised.

Additionally, you need to explain the research process to the participants and obtain their informed consent. After that, you will let them know about the specific safety precautions you are taking.

Sometimes it makes sense to balance the questionnaires' order. As a result, some participants will receive Questionnaire 1 first, while others will receive Questionnaire 2.

To eliminate the "order effects," whereby the order in which questionnaires are presented influences the results, counterbalancing is essential.

You will "debrief" participants at the end of your research. This means that you will tell them what the purpose of their study was. You will need to create a final report after you have completed the statistical analysis.

WHAT SHOULD YOU DO IF YOU'VE CHOSEN A MIXED APPROACH?

STEP 3 - BE AWARE OF YOUR STRENGTHS AND LIMITATIONS

Mixed research has the advantage of overcoming both quantitative and qualitative limitations. Qualitative research, for example, is constrained by its tendency to make biases in interpreting results. Also, results can't be generalized to a larger population. This is what quantitative research overcomes.

Quantitative research is, however, limited in that it doesn't provide a deep understanding of specific meanings or contexts. Qualitative research does. The strengths and weaknesses of each method can be balanced by the use of the mixed approach. This allows you to get more information than if you only used one method.

However, mixed research comes with its limitations. Research design can be very complex, which is one of the main drawbacks of mixed research. Planning mixed research can take more time than planning qualitative or quantitative research.

When combining results from qualitative and quantitative research, you might have trouble connecting your findings. Any discrepancies in your results may be challenging to explain.

Mixed research is essential and must be carried out carefully.

STEP 4: CHOOSE A SPECIFIC MIXED METHOD

Mixed methods come in many different forms. Mixed techniques come in many different forms. Depending on how and when the qualitative research components were carried out, they diverge. These techniques go by the names sequential exploratory, sequential explanatory, concurrent triangulation, concurrent nested, and concurrent triangulation.

Let's take a look at each one separately.

Sequential exploratory design:  A method that combines quantitative and qualitative research is called Sequential exploratory Design. This allows you to first investigate a topic and then add numerical data. This is useful if you are trying to test theories that were based on qualitative research, or if your group wants to share findings from qualitative research.

Sequential explanation design: This refers to the order in which qualitative and quantitative research is done. Quantitative data is given priority. A subsequent collection of qualitative data is required to help you understand the quantitative information.

This design can be used to explain, interpret, and contextualise quantitative findings in depth. It can also be used when quantitative research gives you unexpected results that you want to explain with qualitative data.

Data may be gathered simultaneously using a concurrent triangulation design. We can analyse both forms of data in parallel since both approaches are given equal weight.

This design may be used to cross-validate your findings or to get more in-depth information about a subject. Cross-validation is a statistical technique for determining how well a theoretical model predicts the future. Your research could take advantage of concurrent triangulation. Cross-validation is not necessary, despite the fact that this is a difficult task.

A concurrent nested design collects both qualitative and quantitative data at the same time, but the dominant methodology (qualitative or quantitative) nests or embeds the less prominent method (for example, if the dominant method is quantitative, the less dominant would be qualitative).

This layering implies that your primary technique and less prominent method both focus on a different area of inquiry. The final work output then combines the outcomes of the two different types of procedures. In your undergraduate or graduate classes, you are not required to employ concurrent nested design, the most difficult type of mixed design, unless expressly asked to.

STEP 5: CHOOSE PARTICIPANTS

When doing mixed research, two sets of participants are generally involved: one for qualitative research and the other for quantitative research. Please refer to the sections above for information on how to choose participants based on whether the research is qualitative or quantitative.

In conclusion, a number of relevant participants in your research project will take part in the investigation's qualitative component. In contrast, a larger sample of participants who were chosen to be representative of your target population will be included in the study's quantitative component.

When deciding which people to select for qualitative vs. quantitative research, you will also need to use a variety of recruiting strategies.

STEP 6: SELECT MEASURES

Mixed research is a combination of qualitative and quantitative methods. Therefore, you need to use both qualitative and quantitative measures.

In the sections about quantitative and qualitative research, these measures are talked about in more depth.

Qualitative research is based on observation or interviews. This is usually done by you. Quantitative research is based on questionnaires from past research that have been proven to be valid and reliable.

Depending on the outcomes of your qualitative study, you might occasionally need to develop a questionnaire when using mixed techniques. This is especially true if you employ the sequential exploratory technique, which enables you to compare the findings of your qualitative research to those of your quantitative study in order to verify their accuracy.

In any event, a mixed methods strategy necessitates that you coordinate your quantitative and qualitative measures so that they both focus on the same issue. You can get assistance with this from your boss. 

STEP 7: CHOOSE ANALYSES

You must analyse both qualitative and quantitative data while using a mixed technique. Please refer to the aforementioned website for further details on the precise analyses that are applied in these procedures.

You must typically analyse the data thematically for qualitative research. The participants' replies or your observations are coded in order to do this, and the themes are then discovered within the codes. You can analyse your data using a constant comparative, narrative, or interpretive phenomenological method.

You will need to conduct statistical analyses for quantitative investigations. The type of quantitative design that you use will determine which one you choose. If you're doing descriptive research, then you'll use regression if it is correlational research. If your experiment or quasi-experiment involves statistical analysis, choose A t-test, ANOVA, or MANCOVA.

STEP 8: UNDERSTANDING THE PROCEDURE

The type of mixed design you use will determine how your mixed research is conducted. If you use a sequential exploratory design, then you will start with the qualitative and then move on to the quantitative.

The opposite is true if you employ sequential explanatory designs. You must conduct both the qualitative and quantitative phases of the research simultaneously when using concurrent triangulation or concurrent nested design. The way you prioritise one (qualitative or quantitative) as the primary technique distinguishes them.

Whatever the hybrid designs, you must employ certain techniques for both quantitative and qualitative research.

ADDITIONAL STEPS YOU SHOULD CONSIDER

STEP 9: THINK ABOUT ETHICS

You must ensure that your primary research, whether it is qualitative, quantitative, or mixed, is ethical. Some studies are focused on sensitive topics or vulnerable populations. Your participants should not be hurt. Your research proposal must be submitted to an ethics committee before you can begin your primary research. This is where you will outline how you will handle any ethical concerns that might arise during your research. Even if your primary research has been deemed ethical, you must still follow certain rules of conduct in order to meet the ethical requirements. These include getting participants' informed consent, protecting them, making sure their privacy is protected, and giving them a debriefing. Participation in research requires informed consent. Participants must have read the terms and agreed to participate. No matter what type of research you're doing, informed consent will be sought. You can ask participants to sign a consent form online or in print. You can tell your participants that they will be participating in the research even if they cannot sign an online consent form. Individuals over 18 must sign informed consent. If your participants are under 18, you will need their parents' permission. It may occasionally be challenging to obtain informed permission from your participants for a variety of reasons. You can get the opinions of others who are similar to them about taking part in your study. You have "presumptive permission" if they agree.

All data will be kept anonymous to ensure the confidentiality of participants. You won't ask for the participants' names. Instead, you will assign a participant number to each participant. You should not refer to participants by their names, even if you're reporting interviews with multiple people.

Also, it is important to protect your data so that third parties cannot access it. You must also ensure that your participants are not subject to any mental or physical consequences. They shouldn't be embarrassed, scared, or offended. Your participants should not be from vulnerable groups such as children, the elderly, or the disabled. You must provide special care for them during research.

It is important that your participants are informed at all times that they have the right to withdraw from the research. In situations like an interview or survey, you may do this both during and after your participation. In this situation, participants should be able to contact you and ask for the erasure of their personal data.

After the research is over, participants must always be debriefed. This is crucial if you "deceived," or omitted to disclose to your volunteers up front, the genuine goal of your study. You have two options for debriefing your participants: in-person or in writing.

STEP 10: CONSIDER YOUR LEVEL OF STUDY AND DISCIPLINE

Research for undergraduate studies is less complicated than that for graduate studies.

For undergraduate students, the primary research you do will be based on either qualitative or quantitative methods. You will need to employ interviews more frequently for qualitative research than you will observation, focus groups, or case studies. You might be able to get assistance from your boss with your interview questions.

When performing quantitative research, you may employ a range of approaches (descriptive and correlational, experimental and quasi-experimental), but your study will be basic and easy. There will be no need to predetermine your sample size, no big sample size, just a few measurements will be utilised, and statistical analyses will be simplified. The primary goal of your undergraduate research project is to teach you the fundamentals of research.

Research projects are more significant for graduate students. Graduate students must possess the capacity for critical thought and choose the most appropriate strategy to address their research topics. Consequently, you should consider all of the primary research methods that were discussed in this manual. A mixed, qualitative, or quantitative approach is an option.

It's crucial to pick the right approach and design your measurements before beginning any qualitative study. You also need to be well-versed in techniques like theme analysis. In order to do quantitative research, you must carefully design your study, choose the sample size, find a big number of participants, test several hypotheses, and utilise more intricate statistical analysis. Your graduate research project should teach you more sophisticated research techniques.

Additionally, you should be aware that some fields use particular research methodologies more frequently than others.

In the social sciences, qualitative research is most commonly employed. It is used less often in scientific and mathematical sciences. Because they rely significantly on qualitative research, social sciences are frequently referred to as "soft sciences." This is not to say that they are easy disciplines!

Sociology, psychology, education, ethnology, and cultural anthropology are all fields that involve observation. In all domains that emphasise qualitative research, interviews are employed. Focus groups are used in research in usability, business studies, and library and information sciences. Administrative science, social work, and clinical science all employ case studies.

Quantitative research is popular in the social sciences, with the exception of geography and anthropology. It serves as the foundation for all natural and formal sciences (hence the term "hard sciences"). However, this does not imply that they are more challenging disciplines. It is critical to be familiar with all of the fundamental quantitative approaches, regardless of specialty (descriptive and correlational, experimental and quasi-experimental). These procedures are regarded as scientific pillars, particularly when attempting to prove causality

In the social sciences, mixed research is a popular form of investigation. It can, however, be utilised in natural and formal sciences.

SUMMARY

This manual describes the key techniques for doing primary research for your undergraduate or graduate project. The steps are as follows:

• Choose the data type

• Decide on methodology

• Take note of the strengths and weaknesses of your method

• Choose a primary research method

• Participating Participants

• Take specific measures

• Choose from these analyses

• Learn the procedure

• Ethics: Think about it

• Take into account your level of study.