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Quasi-Experimental Design: A Sneak Peek to Research Technique that Tests a Causal Hypothesis

Quasi-Experimental Design: A Sneak Peek to Research Technique that Tests a Causal Hypothesis

Experimental research design is widely used by the research community to manipulate one or more variables (independent) and determine their effect on the other variables (dependent). This type of research design is often used in two cases: (1) When time priority exists in a causal relationship and (2) there exists a consistency in a causal relationship. 

Experimental research design is classified into a pre-experimental, true experimental and quasi-experimental research design. Although true experimental design is regarded as the most accurate design, it is a quasi-experimental design that is widely used in the research in social science, psychology, etc. as it doesn’t involve random assignment of participants to orders of condition. 

A quasi-experimental research design, also known as ex-post-facto design involves the selection of groups without a random pre-selection process. This type of research design doesn’t allow the research scholar to control the assignment of participants to groups or conditions. It identifies a comparison group that is similar to the intervention group in terms of baseline features. 

Types of quasi-experimental research designs 

Quasi-experimental research designs are of various types and have a variety of applications in a specific framework. 

  • Non-equivalent group, posttest only design – This type of research design includes administration of outcomes measures to treatment group or two groups and a comparison. For instance,  a group of students might receive coding instruction using the latest programming language whereas another group of students might receive writing instruction using standard programming language. After a week, a writing comprehension test is administered to determine which programming language is more effective. However, the major setback of this design is that the two selected groups may differ in important ways that impact the writing process. For example, if a group of students who code using standard programming language, then we cannot determine if the students are well-prepared or if it’s the result of utilization of standard programming language.
  • Non-equivalent control group design – Here we compare the control group and the experimental group. The groups are selected & assigned through convenience rather than choosing via randomization. But the problem arises when the results of the control and experimental group are to be compared. For instance, a researcher wants to determine the impact of online training on the average grade point of class 11 students. Here the researcher cannot randomly collect the participants as the institution will not permit to regroup the classes. Therefore, the researcher chose two sections of class11 from the same institution. Since the participants were not randomly allocated, the researcher cannot conclude that two groups were equivalent before the manipulation. Also, it cannot be determined if the difference in the grade point is only due to the impact of online training as other variables such as intelligence, motivation, etc. can bring about the difference in learning.
  • Separate pretest-posttest sample design – The main idea of this research design is that the individual selected for the pretest is not the same as that of the posttest. For example, assume that the two companies are similar. You can use one company to implement your study and second company as a control. A customer satisfaction program is developed. Initially, the customer satisfaction is measured without implementing the program. This is followed by the implementation of program and measuring the client satisfaction. Here the clients for each company will be different for pretest and posttest. The response of the client from the pretest and posttest cannot be compared. As a result, nonequivalence exists not just between companies but also between the pre and post groups.
  •  Double pretest design – This type of quasi-experimental research design is regarded as the strongest design with respect to internal validity. This is because, in the pre-post nonequivalent research design, the nonequivalent groups may differ from one another. Pretest does not tell us if the changing at the same rates prior to the program. But with a double pretest design, we can determine the rate of change through pretest1 and pretest2. Therefore, this research is explicitly used to control the selection of maturation threat. 
  • Repeated treatment design – Here the treatment is withdrawn and then presented for the second time. Simply said, treatment is presented more than once. The response of the participant is measured prior to and after the implementation of treatment. The treatment program is withdrawn and then the process is performed again. Consider an example where the government has banned the consumption of alcohol. To analyze the impact of this policy, problems pertaining to alcohol consumption were assessed. The outcome of the policy was the health of individuals improved as a result of the ban. 

A quasi-experimental design is widely used to produce results for general trends. The added advantage of this design is that it doesn’t require randomization, prescreening and minimizes the threat to internal validity. 

Although this type of research design is easy to implement, one should take care to address the internal validity threat and utilization of additional data.

Phenomenology: Explore the unexplored concepts of non-positivism research method

Phenomenology: Explore the unexplored concepts of non-positivism research method

Qualitative research involves an interpretive, naturalistic approach which is conducted through critical, self-reflexive enquiry where the researcher should be constantly asking questions about his role in the research process. Qualitative research design includes interviews, case studies, participant observation, action research, historical research, philosophical research, of which phenomenological research, an approach to collect qualitative data. 

This research method distinguishes itself from other research designs as it aims to provide a live experience despite quantifying the research. Phenomenology study inherits the experience from the participant’s perspective, as a result, no formulation of the hypothesis is required to carry on the process of data collection. The phenomenological method used in epistemology, where data and information can be obtained only by emphasising personal experiences and comprehension. 

Phenomenology uses multi-methods such as focus group meetings, participant observation, interviews, conversations, analysis of diaries and other personal texts. To solve the purpose, the questionnaire used is more unstructured and open-ended to explore the experiences of the respondents. Simply put, phenomenology emphasises subjectivity aiming to collect the data in detail using more unstructured questions.

Generally, such research methodology is used in finding out an individual’s experiences, perceptions from their perspectives and in the research studies related to psychology & medical. 

Few research examples employing phenomenological research are as follows:

  • Experiences of Higher Education Students with Disabilities
  • Studying the green flash that sometimes happens just after sunset or just before sunrise
  • Experiences of parents of young children suffering from autism receiving special education services
  • A phenomenological study on the resilience of  old age people from chronic disease

Phenomenology does not focus on measurements or explanations but searches for the meaning or essence of an experience. Phenomenology research is different in that the researcher is often participatory and the other participants are co-researchers in many cases. This research emphasises the study as a holistic approach rather than considering into parts.

Typically, a phenomenological research study follows the four steps, of which includes: 

  1. Bracketing – It is the process to keep a check on any preconceived beliefs or opinions about the phenomenon being researched.  
  2. Intuition – In this step the researcher gets fully involved in the study but simultaneously considers the phenomenon conceived by others.
  3. Analysis – Here the researcher uses processes such as coding and categorising to organise the data.  
  4. Description – This process involves utilisation of cognition regarding data collection and after understanding the phenomenon communicates it to others.

Talking about the strengths of phenomenological research, it provides an in-depth understanding of the themes and meanings of experience that emerge from the data and provides sensible meaning to lived experience. Such type of study contributes to the development of changes in policies or development of new theories. But many a time, researcher may not be able to express the experiences to its full context due to different barriers such as age, language, cognition, motivation, embarrassment and other factors. 

Sometimes the researcher may be biased which is difficult to determine. Also, the results may not be statistically reliable even if the large sample size is taken and may not produce results which may be generalised over the whole population. 

The darker side of this research is that the policymakers do not provide much credibility to it as the subjectivity of the data may lead to difficulty in establishing reliability and validity.

A supervisor’s account of reviewing literature review by candidates from different cultural backgrounds

A supervisor’s account of reviewing literature review by candidates from different cultural backgrounds

There is a whole lot of dilemma linked with being a supervisor to students from different cultures. It is understandable that these students must be feeling perplexed, lonely and confused in their Ph.D. journey. As a supervisor, with a humane touch one would want to do everything that is reasonable enough to help, but then there is always some ambiguity about the best way to help, and with so many responsibilities attached, a supervisor is always short of time and energy, both.

With varied experience in my kitty, and all that I have seen around, I feel that prospective supervisors should be given a choice to accept or not a student who belongs to a diverse cultural background. This holds all the more weight when one talks about semantic barriers, such as the scholar and supervisor not being comfortable on the grounds of language. In universities and institutes who have big monetary motives often don’t say  no to  applying scholars as they don’t consider these challenges significant in front of the money that is coming to them.

As a supervisor you much check in prior to accepting that whether you are in a position to offer support that needs to be given to the scholar. Sometimes, I have also had to face rudeness from the scholar who belonged to another culture. To be explained better, because of cultural differences, certain behaviour of the scholar seems unacceptable in our culture. For example, getting late for appointments, or looking into the eyes and talking. All these may be signs of normal behaviour in some culture but at the same time signalling rudeness or impoliteness in some.  If you are facing anything such, you must do what I did. Explain to the scholar in a tactful manner the changes in the culture that need to be adopted certainly.

Yet another dilemma faced during handling cross cultural scholars is the correction of work and telling them their mistakes. The usage of appropriate words and vocabulary matching the standards of the culture are certain challenges that are difficult to comprehend by the scholar. One needs to devote a lot of time and energy on perpetual basis, trying to do this. This may sometimes make scholars believe it is actually a part of the supervisor’s job but that is not possible, and then further conflicts or differences may arise, which sometimes may get out of control.

Does Every PhD Research Require a Conceptual Framework?

Does Every PhD Research Require a Conceptual Framework?

A majority of reports indicates that over 89% of research candidates find it difficult to decide if their research requires a conceptual framework or not.

Are you fighting the same battle?
If yes, then this article will surely help you out!

The conceptual framework is an essential ingredient for your research. It provides a glance on researcher’s synthesis of literature on how to explain a phenomenon.

The requirement of a ‘Conceptual Framework’ depends on the type of research. But before explaining which research requires a conceptual framework, let me first tell you what purpose a conceptual framework fulfils:

  1. It generates proper links from the literature to the questions and research goals.
  2. It serves as a medium to keep research on track.
  3. It provides a clear insight on the variable of a study.
  4. It explains the concepts and proposes the relationships among the concepts.
  5. It provides an organized structure for the research design and methods.
  6. It guides the development & testing.
  7. It represents the relationship of the developed hypothesis with central factors or key concepts.

Now, moving towards the purpose of this article, let’s see, which research requires a conceptual frame:

A conceptual framework is understood as an explanation of how a research candidate sees the different concepts and outcome of the study and its relation with each other. It can be an adoption used in a previous study with modification to suit the inquiry.

framework

A research can be categorised into two types mentioned below:

  • Exploratory Research: It is also known as formative research, its objective is to gather preliminary information that will help define problems and suggest hypothesis. It is conducted for a problem that has not been clearly defined. Exploratory research helps determine the research design, methods of data collection and conceptual framework.
  • Explanatory / Casual Research: Casual research is quantitative in nature. It is pre-planned and structured in design that’s why it is also known as conclusive research. It is different from exploratory research in terms of explaining cause and effect relationship between variables. Explanatory research shows the cause and effect relationship in terms of experiments and doesn’t require a conceptual framework.

There are two research methods for exploring the cause and effect relationship between variables:

  1. Experimentation
  2. Simulation

What if your research requires a conceptual framework?

Well, don’t worry; we have got your back.

But, what all do we require for developing a conceptual framework?

Below are the ingredients required for developing a conceptual framework:

  1. Literature Review
  2. Knowledge of specific research domain
  3. Research Background
  4. Personal Experience
  5. Data

We understand that the conceptual framework is a prominent document for your research. Let’s discuss how to develop a conceptual framework.

Developing a Conceptual Framework:

concepual-framework

  • Identify Concepts:

Identify concepts from the literature review and provide a categorization among them. The concepts can be categorised as abstract or concrete.

An abstract concept is broad and may not be readily observable while the concrete or specific concepts are amenable to measurement.’

  • Define Variable:

Defining variable is the main function of a conceptual framework in a descriptive research. A variable is something that changes. The change in variable depends upon the various factors; some of the variables are like constant only (name of someone) while other change frequently (Value of Stock Exchange)

  • Operationalize Variables:

The operationalization of variables involves strictly defining variables into measurable elements. It defines fuzzy concept and allows them for empirical and quantitative measurement. To improve the robustness of research design and to increase the quality of the result, operationalization of variables sets down the exact definition of each variable.

  • Develop Propositions:

Develop the relational statement or propositions among the concepts. This helps in providing an idea for hypothesis development and testing.

  • Explore the relationship between variables:

Exploring the relationship among variable is an important part of developing a conceptual framework. Some research abstracts contain the variable of research and thus may serve the purpose.

Even though conceptual framework is the heart of a research, not every research requires a conceptual framework.

Do you require assistance in developing a conceptual framework? Then drop a mail at info@phdthesiswriters.com!

Writing a HYPOTHESIS of the Research

Writing a HYPOTHESIS of the Research

Being a PhD thesis writer, creating a hypothesis for your research study could be a bit tricky part. The hypothesis of the research can also be considered as a statement of predicting the results of the study.

Thus, when you frame a hypothesis always bear in mind that the statement should be

  • Objective
  • Testable
  • Linked with the variables of the study

Here, you should also remember that when you frame a hypothesis there are two statements which are framed simultaneously, in terms of Null hypothesis (symbolized as H0) and Alternate hypothesis (symbolized as H1).

In general terms, the Null hypothesis is a statement which is supposed to be ACCEPTED by the researcher and which is deemed to be the cause of the research. Whereas, the alternate hypothesis is the antithesis of the Null hypothesis (i.e. supposed to be REJECTED)!

For an instance, your study focuses on the subject of employee retention in an organization. In this study you are focusing on various factors which are responsible for retaining the employees in an organization. Thus, when you try to frame the hypothesis statement, you need to concretely define the variables of the study first.

By variables we mean that the variables have various categories such as: dependent variables; independent variables and control variables. The independent variable is the one which influences the dependent variable. The control variables are the ones which determine the conditions in which the dependent and independent variables interact with each other.

Continuing with the example mentioned above, here the independent variables would be the factors which influence the employee retention. Let’s say in your study, you chose these variables as:

  • Source of recruitment
  • Skills and job profile match and
  • Experience of the employee

Note of caution: Now understand that the variable Source of recruitment is also broadly defined. There could be numerous ways of recruiting the employee. Hence, you need to focus on this part as well because the influence of each source of recruitment in retention of employee may vary.

Sources of recruitment could be

  • campus placement;
  • online job portal;
  • recruitment agencies, and
  • advertisement in newspapers

framework

Figure: Framework of Variables of the Research

Note of caution: Categorisi ng the broad variables into specific variables is crucial as the impact of distinct sources of recruitment could vary on the employee retention. If these sources would not be categorized then the research seems generalized and would loose on providing specific insights to the academicians and industry people.

After identifying and categorising the variables you can easily define the hypothesis statement which can be tested as well. The hypothesis statement would follow as:

Ha0: Sources of recruitment impact the retention of employee in an organisation

Ha1: Sources of recruitment does not impact the retention of employee in an organisation

The sub-hypothesis of the main hypothesis are:

Hb0: Employees chosen through campus placement tend to stay for long duration in an organisation

Hb1: Employees chosen through campus placement do not stay for long durations in an organisation

Hc0: Employees chosen through online portals tend to stay for long duration in an organisation

Hc1: Employees chosen through online portals do not stay for long duration in an organisation

Similarly you can frame the hypothesis for the other two variables in the similar manner…

Framing a hypothesis for your dissertation would become a cakewalk if you would follow these steps. Just like the other chapters and sections of your dissertation, the hypothesis statement acts as pillars for drawing conclusion.

Note of caution: If you would make incorrect assumptions (i.e. the predicting statement) then the aims, objectives and all your efforts being invested would go in vain.

Follow these steps to form an appropriate hypothesis for your dear dissertation.

Emerging Research Areas in Energy Economics

Emerging Research Areas in Energy Economics

Emerging Research Areas in Energy EconomicsIf the areas in the domain of applied economics are being looked at, then it can be experienced that out of all the areas, energy economics is the area, which is the most coveted of them all, owing to its multidisciplinary nature. The importance of this area lies in its scope, as this area focuses on the aspects of economic growth and development, linked with the problems regarding natural resources and energy pricing. Given its multidisciplinary nature and mounting amount of importance in the word of business and society, several research areas are emerging out of this particular domain of applied economics.

Within the scope of energy economics, there are several research areas, which are gradually turning out to be popular and significant among the researchers across the world. Signal ProcessingYou can also take help of scholarly writers to choose a good topic to begin your research study. Some of those areas are as per the following:

  • Rebound analysis: With the growth in industrialization across nations, demand of energy is on the rise, and due to several factors, usage of energy is not able to attain its optimum level. The association between expected usage of energy and the actual usage of energy is being tested by researchers by means of rebound analysis. This area is gradually turning out to be popular since last two to three years.
  • Efficiency analysis: Apart from the rebound analysis, efficiency analysis of energy generated from various sources are carried out based on several parameters, like energy price, energy demand, energy supply, number of transmission channels etc.
  • Environmental analysis: During the course of energy generation and consumption, several types of fossil fuels are used, and as a consequence of that, several kinds of environmental degradations, in terms of air, water, soil pollution etc. take place. Analysis of environmental impacts of the energy generation and consumption processes is gradually gaining importance among researchers.

For more information about the emerging and popular research areas in energy economics, kindly browse through the pages of www.phdthesiswriters.com.

Design of Research Questions

Design of Research Questions

Devoid of coming up with concrete research question(s), any research based study can never be started. Based on observational phenomenology, a broad research objective is formed, and then through epistemology and construct building, the research objective is boiled down to concrete research question(s). Unless those research questions are not specific and measurable, the research work can never be effective in all aspects. Specificity of the research question is required in order to keep the study focused. There are several organizations, which assist researchers in designing research questions for their studies. For more information about designing research questions, kindly go through the pages of www.phdthesiswriters.com.

The right reasons for getting a doctorate

The right reasons for getting a doctorate

Doing a PhD is hard work. It is not easy spending hours and hours thinking about a single topic. It is not easy devoting days, months and even years to the study of a subject and trying to find answers to difficult questions. It is often not financially rewarding. It can also be a lonely job. The researcher might find himself studying when others his age are out there in the world earning money. It is not easy to withstand the temptations of partying and having a good time that is invariably a part of social life in a college and spend all that time trying to comprehend the intricacies of big data. There are many students who are not able to withstand the rigours of doing a doctorate and often quit in the middle. Only the single minded and the strong willed are able to see the job through and get to a stage where they can proudly call themselves a doctor. That is why before enrolling in such a course, it is essential that the student look inward and examine the reasons why he wants to be a doctor of philosophy. It is only these reasons that would subsequently seem him through the hard days of completing a PhD.

There are many students who enrol in such courses under the misconception that if they were to get a PhD they would be able to earn fame and fortune. There are others who enrol in these programs under pressure from family and society. Then there are others who think that the only natural thing to do after a Masters is a PhD. All these students are heading down the wrong path. If they were to enrol for these reasons, the chances of them failing are a lot higher than the chances of them succeeding.

One of the best and purest reasons for doing a PhD is for the intense love of a subject. There are students who love a subject so much that they want to examine every aspect of it. Their quest for knowledge is what drives them to put in all the hard work for collecting large volumes of data and then analysing it. If students are intensely passionate about a particular topic or have a deep desire to make a difference to society then they should ideally try their hand at writing a dissertation and becoming a doctor of philosophy.

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