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Starting a PhD in the Pandemic: Challenges and Benefits
27/05/2022
Scholars who embark on their journey towards earning a doctorate know that they are about to undertake a mammoth task. At the best of times, starting a PhD can be quite a demanding and, at times, overwhelming academic commitment. However, when a pandemic is added to the equation, things undeniably get even more difficult.
The experience of starting or pursuing a PhD in the pandemic is largely unprecedented, although it can be safely stated that it affects scholars and their daily lives in many disruptive ways. Apart from causing emotional stress and anxiety, the COVID situation can also throw up other challenges for PhD scholars such as technological and logistical troubles.
In order to deal with these negative effects, one needs to understand them properly first. So, let’s take a look at some of the major challenges faced by research scholars who are starting a PhD during the pandemic.
Challenges of Staring a PhD in the Pandemic
- A sense of isolation
Loneliness has always been one of the most common problems faced by research scholars. Since preparing for a PhD often entails working alone on projects, the situation predictably leads to an overbearing sense of isolation at times. As a result of the COVID situation, the overwhelming task of starting a PhD has been made even more difficult. PhD scholars looking to pursue a doctorate are being made to contend with lockdowns and social isolation, which is invariably leading to fear and confusion.
With almost all educational institutions remaining closed down, isolated scholars are left longing for any form of institutional support. While some universities are better than others at providing academic assistance to PhD scholars, the ongoing pandemic restrictions are not enabling even these universities to offer scholars any relevant form of support. For instance, mentorship programs, workshops or social events for new PhD scholars have become nearly inexistent due to the pandemic. Consequently, a sense of isolation is proving to be a huge detriment for some scholars looking to start a PhD in the pandemic.
- Lack of peer support
Starting a PhD is such a daunting task because research scholars can face many uncertainties and doubts. At a time when many important choices need to be made, peer support is immensely helpful. Friends and family can be immensely supportive when starting a PhD, but the kind of support you can get from fellow PhD scholars just cannot be replicated. The shared commonalities, interests and experiences can help many a PhD aspirant make better sense of their bearings.
The ongoing pandemic has made it difficult to meet and interact with peers and one can often experience a general lack of motivation because of the same. Where once it would be easy to sit down with a peer to share ideas and suggestions, the pandemic has made this day-to-day task very difficult now. With social restrictions in full effect, the only viable recourse for PhD scholars is to maintain their peer network virtually, over the internet. After all, online meetings can go a long way in helping one ascertain what they want from their impending PhD course.
- Stress and Anxiety
The pandemic has caused a considerable spike in the stress and anxiety levels of all kinds of people around the world, and when it comes to PhD scholars, the increase in these levels is even more pronounced. Starting a PhD, even without a pandemic in their midst, is quite a stressful task for most. With COVID wreaking havoc everywhere, the uncertainty of an upcoming lockdown, or a piece of disturbing COVID-related news, can often prove to be even more taxing for scholars.
Furthermore, with the pandemic in full swing, many PhD scholars are also left wondering about the uncertainty that the future holds for them, both in terms of their academic life as well as their distant career prospects. Scholars looking to start a PhD in the pandemic are being burdened by all kinds of COVID-related inconveniences. From uncertain filing dates of PhD applications and deferred entrance examination dates to delayed Research Degree Committee (RDC) meetings for initial interviews – problems are aplenty, and PhD scholars are having to deal with the stress and anxiety involved therein.
Benefits of Starting a PhD in the Pandemic
Now, although some would argue that there cannot be any actual and relevant benefits of starting a PhD in the pandemic, the reality, thankfully, is different. There is always a silver lining present if one looks hard enough. Let’s see how new PhD scholars can make the best of the situation through the following benefits:
- Support groups and community coming together
Research scholars all over the world are gradually, albeit grudgingly, settling down into their altered routines. The internet, as ever, is proving to be an immense boon as individuals are banding together online to form virtual classrooms, support groups and the like. With social distancing becoming the norm everywhere, online communities are coming to the rescue of many individuals seeking academic or social guidance.
When starting a PhD during these uncertain times, scholars should make it a point to harness the power of this virtual community that is available to them. A lot of confusion can be cleared just by talking to like-minded individuals in a supportive environment. For new PhD scholars, speaking to their supervisor often is also highly advisable. Besides reaching out for guidance and feedback, keeping one’s supervisor in the loop and communicating with them freely is always a good idea.
- More time to spare
With social restrictions and lockdowns in place, many PhD aspirants are left with more time on their hands. This time should be used constructively – by reading and researching about one’s field, or maintaining a diary of your academic activities that will come in handy later, or even by pursuing a new hobby or interest. Not only can such activities positively distract a PhD scholar and keep them busy, but also help them make more informed choices during the course of their lives, academic or otherwise.
Conclusion
With the challenges and benefits of starting a PhD in the pandemic out of the way, the next question is, ‘What is the way forward?’ Well, even in such a strange time where very few have an understanding of what the future holds, the most important thing is to stay positive and upbeat.
Starting a PhD during a pandemic is obviously accompanied by a huge set of problems. However, with the right frame of mind, coupled with the right kind of support, even these problems can be overcome one step at a time.
Knowledge, Research Questions and Research Paradigm
29/01/2021
The research question thus posed the objective for exploring and discovering processes that led to knowledge creation. Knowledge by itself is a difficult construct which is viewed from various disciplinary perspectives such as philosophy, cognitive psychology, sociology can pose a myriad and often conflicting variety of definitions. Broadly there are western philosophies which posit separations of reality of physical word from the individual while there are eastern that stress upon knowledge to be occurring to the whole personality and character rather than in separated components of body and mind.
According to the interpretive approach knowledge is personal and constructed through interpretations of meanings. Knowledge is emergent and path dependent. Therefore, by building a linked structure of event pathways the process of accumulation of knowledge and its creation can be constructed. Such study involved collection of naturalistic data and observations and interpretation and validation of meanings. It required creation of a framework for undertaking the research.
The interpretive research paradigm however is relatively new with its traditions yet to be fully established. Only a few works existed to demonstrate the use of methods for data collection analysis and theory building. Apart from principles suggested by Lincoln and Guba (1985) and Klien and Myers (1999) which were yet to be widely applied and agreed upon there were no standards for conduct and evaluation of such research.
Doing Literature Review for PhD, Deriving Research Gap and Setting up Research Objective
15/10/2020
Information about Likert scale in designing survey questionnaire for PhD research
03/09/2020
The Likert Scale( frequently known as agree-disagree scale) was first published by physiologist Rensis Likert in 1932. The technique presents respondents with a series of attitude dimensions ( a battery), for each of which they are asked whether, and how strongly, they agree or disagree, using one of the numbers of the positions on a five-point scale.
With face-to-face interviewer-administered scale batteries, the responses may be shown on a card whilst the interviewer reads out each of the statements in turn. With telephone interviewing, the respondent may sometimes be asked to remember what the response categories are, but preferably be asked to write them down.
The technique is easy for administrators in self-completion questionnaires, either paper or electronic, and may often be given to respondents as a self-completion section in an interviewer-administrator survey.
Responses using a Likert scale can be given scores for each statement, usually from 1 to 5, negative to positive, or -2 to +2. As these are interval data, means and standard deviations can be calculated for each statement.
The full application of the Likert scale is then to sum the scores from each respondent to provide an overall attitudinal score for each individual. Likert’s intention was that the statement would represent different aspects of the same attitude. The overall score, though, is rarely calculated in commercial research (Albaum,1997) where the statement usually covers a range of attitudes. The responses to individual statements are of more interest in determining the specific aspects of attitude that drive behaviour and choice in a market, or summations are made over small groups of items. The data will tend to use in factor analysis, in order to identify the groups of attitudinal dimensions, data are then often used in various forms of cluster or segmentation analyses, in order to segment data into groups of respondents with similar attitudes.
There are four interrelated issues that questionnaires writers must be aware of when using Likert scales :
Order effect
Acquiescence
Central tendency
Pattern answering
A PhD defence Scenario- What happens in the PhD final thesis defence presentation
20/06/2020
What does oral defence look like? Although the format and roles may vary from institution to institution and from advisor to advisor, most follow common procedures.
Here is a scenario that represents a typical oral defence:
1. You arrive about 30 minutes early to arrange the room properly.
2. Your advisor facilitates the meeting, usually opening with introductions. He or she introduces committee members, guests and the outside reader. You then introduce any family or friends who are present.
3. Your advisor explains the purpose of oral defence and procedures to be followed in conducting a defence. Keep in your mind that your advisor is an ally to you and is in your corner at defence.
4. You are asked to provide a brief overview of your study-not more than 5 to 15 minutes. The overview should include the following:
- The purpose of your study and research questions
- What literature did you found particularly helpful
- The methodology used (Include the population and sample, your instruments, and your process for data collection and analysis. Also include the rationale for selecting your sample and method of analysis.)
- Major finding and conclusions from the findings
- Recommendations you would make for action and further research
It’s a good idea to present the summary without numerous notes. If PowerPoint presentations are used, keep the number of slides to a minimum. Just talk to the committee about your study.
Also Read: Why Pilot Questionnaires? Reliability and Validity Testing for PhD Research
5. Who asks the first question is a matter of advisor preference. Members of the committee ask their questions either randomly or systematically chapter by chapter. Committee members should limit their discussion of substance and special concerns rather than those relating to editorial issues. These may be provided at the end of the defence.
6. When committee members have finished with their questions, it is appropriate that visitors are invited to ask questions if they desire. This is a public oral defence. When there are no further questions, you and all visitors exit the room to allow the time for the committee to deliberate and decide if you successfully defended and if your dissertation document is acceptable. A unanimous vote of all committee members is usually required to pass the oral defence.
7. The committee decides among the following:
- Pass with no revisions
- Pass with minor revisions( completed with the advisor’s guidance)
- Pass with major revisions(final approval by the committee)
- Continue with an oral defence
- Fail
What is the difference between minor and major revisions? Minor revisions are those changes that require no substantial rewriting. Examples include updating the bibliography, correcting tables adding more conclusions or recommendations, and correcting typographical and grammatical errors. Most minor revisions can be completed in a weekend, or a week at most. Major revisions are those involving a substantial rewrite of particular sections. Major errors may be incorrect statistics, inconsistency between the research questions and finding, an outdated literature review, poor instrumentation, or lack of adequate data.
8. You and the visitor’s return. If you pass the oral defence, you receive hearty congratulations by all. You will remember that moment of supreme bliss when your advisor shakes your hand and says, ‘Congratulations, Dr.___,” As you reflect on your journey’s experiences, you can probably relate to these words:” Being a graduate student is like becoming all of the seven dwarves.
Why Pilot Questionnaires? Reliability and Validity Testing for PhD Research
27/03/2020
There are two keys tests for a questionnaire: reliability and validity. A questionnaire is reliable if it provides a consistent distribution of responses from the same survey universe. The validity of the questionnaire is whether or not it is measuring what we want it to measure
Testing a questionnaire directly for reliability is very difficult. It can be administered twice to the same of test respondents to determine whether or not they give consistent correct answers.However,the time between the two interviews cannot usually be very long ,both because the respondent’s answer may in fact change over time and because, to be of value to the researcher, the results are usually required fairly quickly. The short period causes further problems in that respondents may have learnt from the first interview and as a result may alter their responses in the second one .Conversely, they may realize that they are being asked the same questions deliberately try to be consistent with their answers. In testing for reliability, we are therefore often asking whether respondents understand the questions and can answer them meaningfully.
Testing a questionnaire for validity requires that we ask whether the questions posed adequately address the objectives of the study. This should include whether or not the manner in which answers are recorded is appropriate.
In addition, questionnaires should be tested to ensure that there are no errors in them. With time scales to produce questionnaires sometimes very tight, there is very often a real danger of errors.
Piloting questionnaires can be thus divided into three areas: reliability., validity, and error testing.
Reliability
- Do the questions sound right? It is surprising how often a question looks acceptable when written on piece of a paper but sounds false, stilted or simply silly when read out.it can be salutary experience for questionnaires elves writers to conduct the interview themselves .They should note how often they want to paraphrase a question that they have written to sound more natural,.
- Do the interviewers understand the questions? Complicated wording in a question can make it incomprehensible even to the interviewers. If they cannot understand it there is a little chance that respondents will.
- Do the respondents understand a question? It is easy for technical technology and jargon to creep into questions, so we need to ensure that it is eliminated.
- Have we included any ambiguous questions, double barreled questions, loaded or leading questions?
- Does the Interview retain the attention and interest of respondents throughout? If attention is lost before it wavers, then the quality of the data may be in doubt. Changes may be required in order to retain the respondent’s interest.
- Can the interviewers or respondents understand the routing instructions in the questionnaire? Particularly with paper questionnaire, we should check the routing instructions can be understood by the interviewers, or if completion, by respondents
- Does the interview flow properly? The questionnaire should be conducting a conversation with the respondent. A questionnaire that unfolds in a logical sequence, with a minimum of jumps between apparently unrelated topics, helps to achieve that.
Validity
- Can respondents answer the questions? We must ensure that we should ask the questions that they are capable of providing answers.
- Are response codes provided sufficient? Missing response codes can lead to answers being forced to fit into the codes provided, or to large numbers of ‘other’ answers.
- Do the response codes provide the sufficient discrimination? If most respondents give the same answer, then the pre-codes provided may need to be reviewed to see how the discrimination can be improved, and if that cannot be achieved, queries should be raised regarding the value of including the question.
- Do questions and responses answer the brief? We should by this time reasonably be certain that the questions we think we are asking meet the brief ,but we need to ensure that the answers which respondents give to those questions are the responses to the questions that we think we are asking.
Error Testing
- Have mistakes been made? Despite all the procedures that most research companies have in place to check questionnaire before they go live, mistakes do occasionally still they get through. It is often the small mistakes that go unnoticed, but these may have a dramatic effect on the meaning of a question or on routing between questions. Imagine the effect of inadvertently omitting the word ‘not’ from a question.
- Does the routing work? Although this should have been comprehensively checked, illogical routing sequences sometimes only become apparent with live interviews.
- Does the technology work? If unusual or untried technology is being used perhaps as an interactive element or for displaying prompts this should be checked in the field. It may work perfectly well in the office, but fields conditions are sometimes different, and a hiatus in the interview caused by slow working or malfunctioning technology can lose respondents.
How long does the interview take? Most Surveys will be budgeted for the interview to take a certain length of time .The number of interviewers allocated to the project will be calculated partly on the length of the interview ,and they will be paid accordingly .Assumptions will also have been made about respondent cooperation based on time taken to complete the interview .The study can run into serious timing and budgetary difficulties , and maybe impossible to complete if the interview is longer than time allowed for. Being shorter than allowed for. Being shorter than allowed for does not usually present such problems but may lead to wasteful use of interviewer resources.
Secondary Research: Know How to Use Existing Information to Conduct a New Study
28/11/2019
Research, aiming to discover solutions to issues/problems in a specific field, includes two major categories: primary and secondary research. While primary research involves data collection via self-conducted approaches, secondary research includes data collected from previous studies.
Primary research is valuable as it fills a gap in the information and provides specific answers to the chosen research question. However, due to its nature, cost involved, and time consumed to perform the study, primary research is not commonly used by the researchers. Instead, they opt secondary research method.
Secondary research ( desk research), involving the use of existing data, summarizes & collates the data to improve the effectiveness of the research. This type of research includes sources published in research reports or other similar documents. The sources for data in secondary research are internal secondary data (websites, public libraries, existing surveys) and external secondary data (government statistics, non-government agencies, media sources).
The purpose of secondary research include:
- Easy clarification of research question
- Ruling out of irrelevant research proposal
- Aligns the objective of the primary research
How to perform secondary research?
Secondary research is easier to perform and includes minimum time-consumption & cost. The steps involved in this process are as mentioned below.
- Identifying the topic of interest – Prior to beginning with the secondary research, identify and define your topic of interest. Next, prepare a list of attributes, purposes and questions that need to be answered at the end of the study. This will help you narrow down the broad topic and determine the key focus of the topic.
- Determining the research sources – After identifying the topic of interest, the next step is to look for sources of relevant & applicable information. In secondary research, information is mostly collected from published and unpublished sources.
Published sources include:
- Journals, periodicals and magazines
- Publication of foreign governments
- Publications and reports of financial institutions, chambers of commerce, trade associations, etc.)
- Census reports and statistical abstracts
- Reports published by state and central government
- Periodic publications of government bodies such as the National Sample Survey Organization (NSSO)
- Reports published by bureaus, economists, research scholars, etc.
Unpublished sources include:
- Reports of business and private sectors
- Data from information sources organizations ( Passport GMID )
- Statistics maintained by corporations, state and central government
- Collecting existing data – On identifying the data sources, narrow them down to gather data that is closely related to your study. For instance, if you want to find the trends in education, then search for suitable data (in the above-mentioned list of sources) using keywords such as trends, education and their synonyms. By doing so, you can collect valuable data and also ensure that none of the vital data is missed out. Also, to ensure that you have collected only the necessary data, consider questions such as: what is the research goal? which questions are outstanding? how precise is the information? and how up-to-date is the collected data?.
- Normalizing data – If the study includes complex and huge data sets, then normalizing the data can ease the process of data analysis. Normalization is the process of comparing the data collected from different sources. For example, information regarding household income is collected from three different sources: US Census Bureau Data (1997), a survey (2000) and a published article (2007). These data can be normalized by shrinking the data into 6 income categories and converting the populations into a percentage.
Normalized data
- Data analysis – Perform the data analysis and determine if any questions are left unanswered. Remember, the analysis technique selected must be capable of producing actionable results. If there is any information gap, repeat the analysis process until you come up with future actions.
What are the advantages of secondary research?
Secondary research includes several advantages over primary research. These include:
- The information is readily available, thereby saving time & cost spent on data collection
- Internal secondary data utilized breakdowns and categories that reflect the way of structuring the data
- Clarifies the research focus
- Presents difficulties faced while conducting the primary research
When should you consider using this form of research?
Secondary research is useful when you want to obtain feedback, clarify primary research objectives or there is no/little budget. However, it is not suitable if situations such as the information available is out-of-date, and it is challenging to evaluate the validity & reliability of the information.
Key takeaways-
1.Verify the credibility of the information gathered
2.Do not just summarize the data. Instead, compare & analyze the information and ensure they are value-adding
Penning Down a Technical Paper: Know How to Structure the Epitome of your Research
30/10/2019
The ability to convey the significant idea of a study is the key to success in the research journey. However, due to reasons such as writers’ block, inadequate knowledge about the writing guidelines, etc. scholars often fail to pour out their thoughts in a technical paper. Although writing a technical paper is a painstaking process, it isn’t too complicated once you are aware of how and what needs to be included in the paper.
A technical paper must reconstruct the investigation process and give an in-depth understanding of the research concept to the reader.
- Typically, a technical paper should be structured as a journal publication and must begin with a read-worthy abstract section. An abstract condenses the critical ideas into a single or a few paragraphs (depending on the length of the paper). This section includes a summary of the investigation and the crucial findings of your study. Explain to your reader the scope of your study and why is it relevant. Lastly, conclude the section by providing a list of index keywords.
- An abstract is followed by an introduction chapter. This section delivers a twofold purpose. That is, it provides the background of your study while establishing its importance and provides an outline & summary of the paper, telling readers as to what they can expect from the paper. While writing the background of your study, ensure to incorporate the latest trends & promising developments in your field of study. If you have included new terminologies, explain them. This chapter also includes a detailed description of the problem statement, solutions and the research approach used. Conclude the section by describing the outline of your paper and the elements in each section.
- The literature review section must follow the introduction chapter. This section has two purposes. First, it provides a list of related works and secondly, gives a critique of the methods in the literature which are required to build the significance of your study. Here, incorporate only those references that are relevant to your study. Also, present how the previous developments form the basis of your study. Providing references shows that you have knowledge pertaining to the topic and your capability to perform the research.
- The fourth section is the system model. Here define the hypothesis and assumption on which the research problem is stated. Remember, the more valid are the assumptions, the more acceptable is your study. Besides assumptions, provide the evidence to support your argument and figures to demonstrate the parameters of the system model.
- Next include the major section of the technical paper, the methodology section or the experimentation/simulation. Here, state the conditions and parameters of the experimental environment or simulations. Additionally, explain the procedure, tools/equipment, algorithms, etc. used to perform the experiment. If you have deviated from standard procedure, explain the changes made. If required, you can include key points to establish the validity of the research method used.
- The first chapter is the result section. As the name suggests, this chapter will include the significant findings of your research. While present the results, round off the numerical value to the nearest significant number. Ensure to eliminate the outliers of the data and results that are of no value. Present the findings using labeled graphs, figures, charts or tables. Represent the set of data points explicitly and draw smooth curves. You can also include scale bars for micrographs to enable the readers to view the details you are explaining.
- In the discussion, section explains the meaning of the results, their reliability & consistency, how the findings back the existing theories and their contribution to your field of study. You can either include this section separately or combine it with the result section.
- In the final chapter briefly explain the summary of your paper and the conclusions of your study. This section should logically follow the result & discussion section and serve two purposes. Firstly, it must elaborate on the impact of using a specific research method, the significance of your study and its limitations.
Besides paying attention to the concepts to be included in each section, focus on non-technical words, acronyms or abbreviations, jargon, sentence structure, and other writing ethics.
Triangulation Technique : A Comprehensive Guide to Enhancing Credibility of Research
28/09/2019
With the increase in issues with the trustworthiness in qualitative research, it has become a necessity for scholars to establish credibility, transferability, dependability, and conformability of their research. Although all the four factors play a vital role, credibility is the foremost factor that builds the trustworthiness of qualitative research. While developing credibility is one side of the story, enhancing the same is other.
Originating in surveying & navigational contexts, triangulation is a practice of utilising multiple data sources & approaches to perform data analysis and improve the credibility of a research. In a word, triangulation is a process of combining several research approaches to study one concept and over the bias & uncertainty in the outcomes of the research.
In research triangulation are of four types:
- Data triangulation – This process involves data collection from various sources
- Theoretical triangulation – This type of triangulation involves borrowing theories from one discipline and using them in another discipline
- Methodological triangulation – Here we use qualitative and quantitative methods to obtain reliable findings
- Triangulation by investigator – This type of triangulation involves more than one investigator. The data is collected individually and then compared on the basis of types of data collected
As said earlier, triangulation assists in minimising different types of bias encountered in your research process.
- Measurement bias – This kind of bias is caused on the basis of the approach used to gather data. Perhaps the most common form of this is the setting/environment is which the research is conducted. For instance, peer pressure on focus group participants. Triangulation lets you combine group and individual research methods to reduce the measurement bias. Consider another example where research subjects tend to explain what they heard. Here triangulation combines observational and self-reported to solve the issue.
- Sampling bias – This type of bias occurs when only few convenient population under study is covered. However, some of the research approaches makes it easier to cover a good amount of population. For example, telephonic interview for interstate research subjects can be a substitute for one-to-one interview with local subjects. Likewise, online survey makes it easier to include geographically distant research participants. Triangulation combines the strength of these approaches to ensure complete coverage of the population.
- Procedural bias – Put simply, procedural bias occurs when the research participants experience the same pressure to provide information. For instance, online exit survey may force the participants to answer the questions quickly to complete the survey. Triangulation combines the short with larger engagements to provide participants sufficient time to answer the questions.
Triangulation, although can be used in various scenarios, it is most commonly used:
- When different sources are used
- Controversial aspect of research which needs critical assessment
- Established research method yields limited & frequent wry picture
- Evaluation of case study of a complex phenomenon
With that said, to achieve triangulation one requires data either from different sources or investigators.
Triangulation can be achieved via:
- Mixing up different techniques: Combine techniques such as qualitative vs quantitative, self-reported vs facilitated, short vs long engagement, individual interview vs focus group, etc. to balance out each other.
- Involvement of two or more individuals on a project – Another kind of triangulation can be achieved by involving two or more than two people to make notes, observation, and perform data analysis. This is so because the investigators will have different perspective giving a theoretical framework to analyse data.
- Layer upon layer – A kind of triangulation can be achieved by conducting research in layers of detail. Begin with broad piece of information, identify major issues, and offer insights to concepts in the next layer. In the second layer focus on narrow area and provide detailed information.
Triangulation is employed for several reasons, of which are:
- To obtain different types of information on a particular issue
- To overcome the weakness of a research method by using the strengths of another method
- To achieve validity and reliability of results
An example for the use of triangulation technique
Consider an example where a research involves studying three crucial concepts. The research problems are (1) access to schooling for women in Pakistan, (2) role of poverty in access to education, and (3) development & implementation of education policies.
For the first research problem, the data was extracted from primary sources such as local leaders, women, & teachers and the data collection tools is interview schedule. For the second research problem, the data was collected from parents, students, and local bodies. For the last research problem, the information was obtained from professors, institutes’ head, and government officers.
Utilisation of various data collection techniques and approaches have led to employ triangulation technique in the research process.
| Research problem | Data sources | Data tools |
| Access to schooling for women in Pakistan | Local leaders, women, teachers | Interview schedule |
| Role of poverty in access to education | Parents, local bodies, students | Open-ended interview |
| Development & implementation of education policies | Government bodies, institutes’ head, professors | Questionnaire |
Research methods have limitations such as bias, irrespective of its type. Triangulation is that one technique which not only lets you capture huge amounts of data but also minimise the impact of bias on your study. Leverage triangulation and ensure balanced research process.
Survey vs Experiment: Know How Two Research Methods Differ from Each Other
29/08/2019
Research methods are procedures that span the steps from nonspecific assumptions to detailed approaches of data collection, analysis, and interpretation. These are essentially well-planned, value-neutral and scientific.
Generally, the research method includes experimental study, focus groups, survey method, numerical schemes, theoretical procedures, etc. However, each study domain demands a specific type of research method.
For instance, for research that requires investigation of characteristics, opinions or behaviours of a group of people, survey method can be used.
Whereas, research that demands explanation based on observations, collected facts, and measurements, the experiment research method is used.
Know more about experiment and survey method
- Experiment method
Derived from Latin word ‘experior’ (meaning – attempt), experiment is a systematic approach that tests the hypothesis by performing a procedure under highly controlled conditions. This approach is based on a comparison between two or more variables and is ideal for studying the primary data. Experiment involves manipulating a certain independent variable and determining its effect on a dependent variable.
For example, you can measure the impact of how water intake on people’s metabolism by letting the experimental group drink 6 glasses of water per day while letting the controlled group to drink only 3 glasses of water. Their metabolism rates can then be compared after a couple of weeks, and statistical tests such as T-test can be used to validate the results.
Typically, an experimental research method consists of three types of designs: pre-experimental, true- experimental, and quasi-experimental design.
- Pre-experimental design – In this approach, a group(s), is kept under observation after factors for cause & effect are considered.
- True-experimental design – Being the most accurate design, this method is used to establish a cause-effect relationship within a group(s).
- Quasi-experimental design – Here, the independent variable will be manipulated, but the members of a population are not randomly assigned.
Experimental research design includes key characteristics such as:
- Manipulating the independent variable
- Determining the factors that cause effects
- Comparison of two or more groups
- Deciding the extent and nature of the treatment
Experiment research method offers several advantages such as – accurate results, control over variables, determination of cause & effect of a study hypothesis, and can be used in collaboration with other research designs.
- Survey method
Derived from Latin word ‘supervidere’ (meaning – to see), survey method, best suited for descriptive research, studies the opinion, behaviours, attributes and feelings of an individual or a group of people. This process collection of numbered data and statistically analysing responses to the questions in order to test the hypothesis about the nature of relationships within a group.
For instance, if you are intended to study the happiness levels among employees’ working in a specific organisation. Here the data will be collected through questionnaires, phone calls, Emails, etc. Upon collecting the data regarding the individuals’ perceived emotional states, statistical tests such as getting the weighted mean can be utilised to assess the responses.
Based on the design, survey research method can be divided into three types of studies: cross-sectional, longitudinal and correlational study.
- Cross-sectional study – Defined as observational research type, this study evaluates data of variables gathered at a given point of time across a sample population.
- Longitudinal study – This method uses repeated or continuous measures to follow certain individuals over an extended period of time ( more often years or decades).
- Correlational study – This non-experimental design studies two different variables and runs a statistical analysis to determine the relation between the variables without the interference of external variables.
The significant features of the survey research method include:
- Involvement in the process of sampling from a population
- Developing instrument for data collection process
- Collecting data via interviews or questionnaires
- Acquiring greater response rate
Survey method offers several benefits of which include – primary data collected is easy to analyse, data can be collected at a faster rate and easily, offers precise information, and is flexible.
Key differences between experiment and survey method
| Features | Experiment method | Survey method |
| Source of information | Information is obtained due to change in behaviour of independent variable | Data is acquired from informants |
| Data handled | Deals with primary data | More often deals with secondary data |
| Sample studied | Studies smaller sample | Studies larger sample |
| Commonly employed in
(research type) |
Utilised in experimental research | Utilised in descriptive research |
| Field of study focused | Used in physical & natural science | Used in social & behavioural science |
| Experiment performed in | Conducted in lab or field study | Conducted in field research |
| Challenges faced | Hardship faced in verifying if the effect is actually caused by the independent variable | Difficulty in identifying the responses are genuine |
| Equipment | Uses software/tool | Doesn’t use any tool |
| Cost of experiment | High | low |
| Manipulation | Involves manipulation of independent variable | Does not involve any manipulation |
| Randomisation | Follows randomisation mandatorily | May or may not follow randomisation |
Choosing the right research method is vital for any research. Hence make sure you understand the requirements of your study and choose the research method accordingly.
