The video below explains the differences between research questions, hypotheses, and objectives. This is important to understand because these terms are so commonly used when conducting research.
Tag Archives: research process
Different Views of Research
People have been doing research formally or informally since the beginning of time. We are always trying to figure out how to do this or why something is the way that it is. In this post, we will look at different ways to view and or conduct research. These perspectives are empirical, theoretical, and analytical.
Perhaps the most common form or approach to doing research is the empirical approach. This approach involves observing reality and developing hypotheses and theories based on what was observed. This is an inductive approach to doing research because the researcher starts with their observations to make a theory. In other words, you start with examples and abstract them to theories.
An example of this is found in the work of Charles Darwin and evolution. Darwin collected a lot of examples and observations of birds during his travels. Based on what he saw he inferred that animals evolved over time. This was his conclusion based on his interpretation of the data. Later, other researchers tried to further bolster Darwin’s theory by finding mathematical support for his claims.
The order in which empirical research is conducted is as follows…
- Identify the phenomenon
- Collect data
- Abstraction/model development
You can see that hypotheses and theory are derived from data which is similar to qualitative research. However, steps 4 and 5 are were the equation developing and or statistical tools are used. As such the empirical view of research is valuable when there is a large amount of data available and can include many variables, which is again often common for quantitative methods.
To summarize this, empirical research is focused on what happened, which is one way in which scientific laws are derived.
The theoretical perspective is essentially the same process as empirical but moving in the opposite direction. For theorists, the will start with what they think about the phenomenon and how things should be. This approach starts with a general principle and then the researcher goes and looks for evidence that supports their general principle. Another way of stating this is that the theoretical approach is deductive in nature.
A classic example of this is Einstein’s theory of relativity. Apparently, he deduced this theory through logic and left it to others to determine if the theory was correct. To put it simply, he knew without knowing, if this makes sense. In this approach, the steps are as follows
- model abstraction
- data collection
You collect data to confirm the hypotheses. Common statistical tools can include simulations or any other method that is suitable in situations in which there is little data available. The caveat is that the data must match the phenomenon to have meaning. For example, if I am trying to understand some sort of phenomenon about women I cannot collect data from as this does not match the phenomenon.
In general, theoretical research is focused on why something happens which is the goal of most theories, explaining why.
Analytical research is probably the hardest to explain and understand. Essentially, analytical research is trying to understand how people develop their empirical or theoretical research. How did Darwin make this collection or how did Einstein develop his ideas.
In other words, analytical research is commonly used to judge the research of others. Examples of this can be people who spend a lot of time criticizing the works of others. An analytical approach is looking for the strengths and weaknesses of various research. Therefore, this approach is focused on how research is done and can use tools both from empirical and theoretical research.
The point here was to explain different views om conducting research. The goal was not to state that one is superior to the other. Rather, the goal was to show how different tools can be used in different ways
3 Steps to Successful Research
When students have to conduct a research project they often struggle with determining what to do. There are many decisions that have to be made that can impede a student’s chances of achieving success. However, there are ways to overcome this problem.
This post will essentially reduce the decision-making process for conducting research down to three main questions that need to be addressed. These questions are.
- What do you Want to Know?
- How do You Get the Answer?
- What Does Your Answer Mean?
Answering these three questions makes it much easier to develop a sense of direction and scope in order to complete a project.
What do you Want to Know?
Often, students want to complete a project but it is unclear to them what they are trying to figure out. In other words, the students do not know what it is that they want to know. Therefore, one of the first steps in research is to determine exactly it is you want to know.
Understanding what you want to know will allow you to develop a problem as well as research questions to facilitate your ability to understand exactly what it is that you are looking for. Research always begins with a problem and questions about the problem and this is simply another way of stating what it is that you want to know.
How do You Get the Answer?
Once it is clear what it is that you want to know it is critical that you develop a process for determining how you will obtain the answers. It is often difficult for students to develop a systematic way in which to answer questions. However, in a research paradigm, a scientific way of addressing questions is critical.
When you are determining how to get answers to what you want to know this is essential the development of your methodology section. This section includes such matters as the research design, sample, ethics, data analysis, etc. The purpose here is again to explain the way to get the answer(s).
What Does Your Answer Mean?
After you actually get the answer you have to explain what it means. Many students fall into the trap of doing something without understanding why or determining the relevance of the outcome. However, a research project requires some sort of interpretation or explanation of the results. Just getting the answer is not enough it is the meaning that holds the power.
Often, the answers to the research questions are found in the results section of a paper and the meaning is found in the discussion and conclusion section. In the discussion section, you explain the major findings with interpretation, sare recommendations, and provide a conclusion. This requires thought into the usefulness of what you wanted to know. In other words, you are explaining why someone else should care about your work. This is much harder to do than many realize.
Research is challenging but if you keep in mind these three keys it will help you to see the big picture of research and o focus on the goals of your study and not so much on the tiny details that encompasses the processes.
Writing Discussion & Conclusions in Research
The Discussion & Conclusion section of a research article/thesis/dissertation is probably the trickiest part of a project to write. Unlike the other parts of a paper, the Discussion & Conclusions are hard to plan in advance as it depends on the results. In addition, since this is the end of a paper the writer is often excited and wants to finish it quickly, which can lead to superficial analysis.
This post will discuss common components of the Discussion & Conclusion section of a paper. Not all disciplines have all of these components nor do they use the same terms as the ones mentioned below.
The discussion is often a summary of the findings of a paper. For a thesis/dissertation, you would provide the purpose of the study again but you probably would not need to share this in a short article. In addition, you also provide highlights of what you learn with interpretation. In the results section of a paper, you simply state the statistical results. In the discussion section, you can now explain what those results mean for the average person.
The ordering of the summary matters as well. Some recommend that you go from the most important finding to the least important. Personally, I prefer to share the findings by the order in which the research questions are presented. This maintains a cohesiveness across sections of a paper that a reader can appreciate. However, there is nothing superior to either approach. Just remember to connect the findings with the purpose of the study as this helps to connect the themes of the paper together.
What really makes this a discussion is to compare/contrast your results with the results of other studies and to explain why the results are similar and or different. You also can consider how your results extend the works of other writers. This takes a great deal of critical thinking and familiarity with the relevant literature.
The next component of this final section of the paper is either recommendations or implications but almost never both. Recommendations are practical ways to apply the results of this study through action. For example, if your study finds that sleeping 8 hours a night improves test scores then the recommendation would be that students should sleep 8 hours a night to improve their test scores. This is not an amazing insight but the recommendations must be grounded in the results and not just opinion.
Implications, on the other hand, explain why the results are important. Implications are often more theoretical in nature and lack the application of recommendations. Often implications are used when it is not possible to provide a strong recommendation.
The terms conclusion and implications are often used interchangeably in different disciplines and this is highly confusing. Therefore, keep in mind your own academic background when considering what these terms mean.
There is one type of recommendation that is almost always present in a study and that is recommendations for further study. This is self-explanatory but recommendations for further study are especially important if the results are preliminary in nature. A common way to recommend further studies is to deal with inconclusive results in the current study. In other words, if something weird happened in your current paper or if something surprised you this could be studied in the future. Another term for this is “suggestions for further research.”
Limitations involve discussing some of the weaknesses of your paper. There is always some sort of weakness with a sampling method, statistical analysis, measurement, data collection etc. This section is an opportunity to confess these problems in a transparent matter that further researchers may want to control for.
Finally, the conclusion of the Discussion & Conclusion is where you try to summarize the results in a sentence or two and connect them with the purpose of the study. In other words, trying to shrink the study down to a one-liner. If this sounds repetitive it is and often the conclusion just repeats parts of the discussion.
This post provides an overview of writing the final section of a research paper. The explanation here provides just one view on how to do this. Every discipline and every researcher has there own view on how to construct this section of a paper.
Tips for Writing a Quantitative Review of Literature
Writing a review of literature can be challenging for students. The purpose here is to try and synthesize a huge amount of information and to try and communicate it clearly to someone who has not read what you have read.
From my experience working with students, I have developed several tips that help them to make faster decisions and to develop their writing as well.
Remember the Purpose
Often a student will collect as many articles as possible and try to throw them all together to make a review of the literature. This naturally leads to problems of the paper sounded like a shopping list of various articles. Neither interesting nor coherent.
Instead, when writing a review of literature a student should keep in mind the question
What do my readers need to know in order to understand my study?
This is a foundational principle when writing. Readers don’t need to know everything only what they need to know to appreciate the study they are ready. An extension of this is that different readers need to know different things. As such, there is always a contextual element to framing a review of the literature.
Consider the Format
When working with a student, I always recommend the following format to get there writing started.
For each major variable in your study do the following…
- Define it
- Provide examples or explain theories about it
- Go through relevant studies thematically
There first thing that needs to be done is to provide a definition of the construct. This is important because many constructs are defined many different ways. This can lead to confusion if the reader is thinking one definition and the writer is thinking another.
Examples and Theories
Step 2 is more complex. After a definition is provided the student can either provide an example of what this looks like in the real world and or provide more information in regards to theories related to the construct.
Sometimes examples are useful. For example, if writing a paper on addiction it would be useful to not only define it but also to provide examples of the symptoms of addiction. The examples help the reader to see what used to be an abstract definition in the real world.
Theories are important for providing a deeper explanation of a construct. Theories tend to be highly abstract and often do not help a reader to understand the construct better. One benefit of theories is that they provide a historical background of where the construct came from and can be used to develop the significance of the study as the student tries to find some sort of gap to explore in their own paper.
Often it can be beneficial to include both examples and theories as this demonstrates stronger expertise in the subject matter. In theses and dissertations, both are expected whenever possible. However, for articles space limitations and knowing the audience affects the inclusion of both.
The relevant studies section is similar breaking news on CNN. The relevant studies should generally be newer. In the social sciences, we are often encouraged to look at literature from the last five years, perhaps ten years in some cases. Generally, readers want to know what has happened recently as experience experts are familiar with older papers. This rule does not apply as strictly to theses and dissertations.
Once recent literature has been found the student needs to organize it thematically. The reason for a thematic organization is that the theme serves as the main idea of the section and the studies themselves serve as the supporting details. This structure is surprisingly clear for many readers as the predictable nature allows the reader to focus on content rather than on trying to figure out what the author is tiring to say. Below is an example
There are several challenges with using technology in class(ref, 2003; ref 2010). For example, Doe (2009) found that technology can be unpredictable in the classroom. James (2010) found that like of training can lead some teachers to resent having to use new technology
The main idea here is “challenges with technology.” The supporting details are Doe (2009) and James (2010). This concept of themes is much more complex than this and can include several paragraphs and or pages.
This process really cuts down on the confusion of students writing. For stronger students, they can be free to do what they want. However, many students require structure and guidance when the first begin writing research papers
Common Problems with Research for Students
I have worked with supporting undergrad and graduate students with research projects for several years. This post is what I consider to be the top reasons why students and even the occasional faculty member struggles to conduct research. The reasons are as follows
- They don’t read
- No clue what a problem is
- No questions
- No clue how to measure
- No clue how to analyze
- No clue how to report
Lack of Reading
The first obstacle to conducting research is that students frequently do not read enough to conceptualize how research is done. Reading not just anything bust specifically research allows a student to synthesize the vocabulary and format of research writing. You cannot do research unless you first read research. This axiom applies to all genres of writing.
A common complaint is the difficulty with understanding research articles. For whatever reason, the academic community has chosen to write research articles in an exceedingly dense and unclear manner. This is not going to change because one graduate student cannot understand what the experts are saying. Therefore, the only solution to understand research English is exposure to this form of communication.
Determining the Problem
If a student actually reads they often go to the extreme of trying to conduct Nobel Prize type research. In other words, their expectations are overinflated given what they know. What this means is that the problem they want to study is infeasible given the skillset they currently possess.
The opposite extreme is to find such a minute problem that nobody cares about it. Again, reading will help in avoiding this two pitfalls.
Another problem is not knowing exactly how to articulate a problem. A student will come to me with excellent examples of a problem but they never abstract or take a step away from the examples of the problem to develop a researchable problem. There can be no progress without a clearly defined research problem.
Lack the Ability to Ask Questions about the Problem
If a student actually has a problem they never think of questions that they want to answer about the problem. Another extreme is they ask questions they cannot answer. Without question, you can never better understand your problem. Bad questions or no questions means no answers.
Generally, there are three types of quantitative research questions while qualitative is more flexible. If a student does not know this they have no clue how to even begin to explore their problem.
Issues with Measurement
Let’s say a student does know what their questions are, the next mystery for many is measuring the variables if the study is quantitative. This is were applying statistical knowledge rather than simply taking quizzes and test comes to play. The typical student does not understand often how to operationalize their variables and determine what type of variables they will include in their study. If you don’t know how you will measure your variables you cannot answer any questions about your problem.
Lost at the Analysis Stage
The measurement affects the analysis. I cannot tell you how many times a student or even a colleague wanted me to analyze their data without telling me what the research questions were. How can you find answers without questions? The type of measurement affects the potential ways of analyzing data. How you summary categorical data is different from continuous data. Lacking this knowledge leads to inaction.
No Plan for the Write-Up
If a student makes it to this stage, firstly congratulations are in order, however, many students have no idea what to report or how. This is because students lose track of the purpose of their study which was to answer their research questions about the problem. Therefore, in the write-up, you present the answers systematically. First, you answer question 1, then 2, etc.
If necessary you include visuals of the answers. Again Visuals are determined by the type of variable as well as the type of question. A top reason for article rejection is an unclear write-up. Therefore, great care is needed in order for this process to be successful.
Whenever I deal with research students I often walk through these six concepts. Most students never make it past the second or third concept. Perhaps the results will differ for others.
Successful research writing requires the ability to see the big picture and connection the various section of a paper so that the present a cohesive whole. Too many students focus on the little details and forget the purpose of their study. Losing the main idea makes the details worthless.
If I left out any common problems with research please add them in the comments section.
Academic vs Applied Research
Academic and applied research are perhaps the only two ways that research can be performed. In this post, we will look at the differences between these two perspectives on research.
Academic research falls into two categories. These two categories are
- Research ON your field
- Research FOR your field
Research ON your field is research is research that is searching for best practice. It looks at how your academic area is practiced in the real world. A scholar will examine how well a theory is being applied or used in a real-world setting and make recommendations.
For example, in education, if a scholar does research in reading comprehension, they may want to determine what are some of the most appropriate strategies for teaching reading comprehension. The scholar will look at existing theories and such which one(s) are most appropriate for supporting students.
Research ON your field is focused on existing theories that are tested with the goal of developing recommendations for improving practice.
Research FOR your field is slightly different. This perspective seeks to expand theoretical knowledge about your field. In orders, the scholar develops new theories rather than assess the application of older ones.
An example of this in education would be developing a new theory in reading comprehension. By theory, it is meant explanation. Famous theories in education include Piaget’s stages of development, Kohlberg’s stages of moral development, and more. At their time each of these theories pushes the boundaries of our understanding of something.
The main thing about academic research is that it leads to recommendations but not necessarily to answers that solve problems. Answering problems is something that is done with applied research.
Applied research is also known as research IN your field. This type of research is often performed by practitioners in the field.
- research IN your field
There are several forms of research IN your field and they are as follows
Formative research is for identifying problems. For example, a teacher may notice that students are not performing well or doing their homework. Formative applied research is when the detective hat is put on and the teacher begins to search for the cause of this behavior.
The results of formative research lead to some sort of an action plan to solve the problem. During the implementation of the solution, monitoring applied research is conducted. Monitoring research is conducted during implementation of a solution to see how things are going.
For example, if the teacher discovers that students are struggling with reading because they are struggling with phonological awareness. They may implement a review program of this skill for the students. Monitoring would involve assessing student performance of reading during the program.
Summative applied research is conduct at the end of implementation to see if the objectives of the program were met. Returning to the reading example, if the teacher’s objective was to improve reading comprehension scores 10% the summative research would assess how well the students can now read and whether there was a 10% improvement.
In education, applied research is also known as action research.
Research can serve many different purposes. Academics focus on recommendations, not action while practitioners want to solve problems and perhaps not recommend as much. The point is that understanding what type of research you are trying to conduct can help you in shaping the direction of your study.
Data Science Research Questions
Developing research questions is an absolute necessity in completing any research project. The questions you ask help to shape the type of analysis that you need to conduct.
The type of questions you ask in the context of analytics and data science are similar to those found in traditional quantitative research. Yet data science, like any other field, has its own distinct traits.
In this post, we will look at six different types of questions that are used frequently in the context of the field of data science. The six questions are…
Understanding the types of question that can be asked will help anyone involved in data science to determine what exactly it is that they want to know.
A descriptive question seeks to describe a characteristic of the dataset. For example, if I collect the GPA of 100 university student I may want to what the average GPA of the students is. Seeking the average is one example of a descriptive question.
With descriptive questions, there is no need for a hypothesis as you are not trying to infer, establish a relationship, or generalize to a broader context. You simply want to know a trait of the dataset.
Exploratory questions seek to identify things that may be “interesting” in the dataset. Examples of things that may be interesting include trends, patterns, and or relationships among variables.
Exploratory questions generate hypotheses. This means that they lead to something that may be more formal questioned and tested. For example, if you have GPA and hours of sleep for university students. You may explore the potential that there is a relationship between these two variables.
Inferential questions are an extension of exploratory questions. What this means is that the exploratory question is formally tested by developing an inferential question. Often, the difference between an exploratory and inferential question is the following
- Exploratory questions are usually developed first
- Exploratory questions generate inferential questions
- Inferential questions are tested often on a different dataset from exploratory questions
In our example, if we find a relationship between GPA and sleep in our dataset. We may test this relationship in a different, perhaps larger dataset. If the relationship holds we can then generalize this to the population of the study.
Causal questions address if a change in one variable directly affects another. In analytics, A/B testing is one form of data collection that can be used to develop causal questions. For example, we may develop two version of a website and see which one generates more sales.
In this example, the type of website is the independent variable and sales is the dependent variable. By controlling the type of website people see we can see if this affects sales.
Mechanistic questions deal with how one variable affects another. This is different from causal questions that focus on if one variable affects another. Continuing with the website example, we may take a closer look at the two different websites and see what it was about them that made one more succesful in generating sales. It may be that one had more banners than another or fewer pictures. Perhaps there were different products offered on the home page.
All of these different features, of course, require data that helps to explain what is happening. This leads to an important point that the questions that can be asked are limited by the available data. You can’t answer a question that does not contain data that may answer it.
Answering questions is essential what research is about. In order to do this, you have to know what your questions are. This information will help you to decide on the analysis you wish to conduct. Familiarity with the types of research questions that are common in data science can help you to approach and complete analysis much faster than when this is unclear
Developing a Data Analysis Plan
It is extremely common for beginners and perhaps even experience researchers to lose track of what they are trying to achieve or do when trying to complete a research project. The open nature of research allows for a multitude of equally acceptable ways to complete a project. This leads to an inability to make a decision and or stay on course when doing research.
One way to reduce and eliminate the roadblock to decision making and focus in research is to develop a plan. In this post, we will look at one version of a data analysis plan.
Data Analysis Plan
A data analysis plan includes many features of a research project in it with a particular emphasis on mapping out how research questions will be answered and what is necessary to answer the question. Below is a sample template of the analysis plan.
The majority of this diagram should be familiar to someone who has ever done research. At the top, you state the problem, this is the overall focus of the paper. Next, comes the purpose, the purpose is the over-arching goal of a research project.
After purpose comes the research questions. The research questions are questions about the problem that are answerable. People struggle with developing clear and answerable research questions. It is critical that research questions are written in a way that they can be answered and that the questions are clearly derived from the problem. Poor questions means poor or even no answers.
After the research questions, it is important to know what variables are available for the entire study and specifically what variables can be used to answer each research question. Lastly, you must indicate what analysis or visual you will develop in order to answer your research questions about your problem. This requires you to know how you will answer your research questions
Below is an example of a completed analysis plan for simple undergraduate level research paper
In the example above, the student wants to understand the perceptions of university students about the cafeteria food quality and their satisfaction with the university. There were four research questions, a demographic descriptive question, a descriptive question about the two main variables, a comparison question, and lastly a relationship question.
The variables available for answering the questions are listed off to the left side. Under that, the student indicates the variables needed to answer each question. For example, the demographic variables of sex, class level, and major are needed to answer the question about the demographic profile.
The last section is the analysis. For the demographic profile, the student found the percentage of the population in each sub group of the demographic variables.
A data analysis plan provides an excellent way to determine what needs to be done to complete a study. It also helps a researcher to clearly understand what they are trying to do and provides a visual for those who the research wants to communicate with about the progress of a study.
The research process or scientific method is the default mode for systematically gather information for the purpose of answering questions and solving problems. This process serves the purpose of defining the goals of research, making predictions, gather data, and interpreting results.
In general, there are six steps to the research process as listed below.
- Identify the research problem
- Review the literature
- Specify the purpose of the research or develop research questions
- Collect data
- Analyze and interpret data
- Report and evaluate results
Identify the Problem
The problem can come from personal observation, readings, from others, or any other of a host of ways. Finding a problem also helps in focusing your study. When identifying a problem it is important to make sure that you develop a justification for investigating it as well as the importance of it. People need to know why they should care about what you are studying. This has to do with relevancy.
Reviewing the Literature
Reviewing the literature is about knowing what has been done before your so that you can see how you can build on existing knowledge. Most research tends to add to an existing conversation rather than start a new one. Looking at the literature also helps you to see your contribution to the existing body of knowledge. This is one way in which you can find the “gap” in the knowledge that your study will address.
Purpose of Research or Research Questions
The research purpose is the overall objective of the study. It is a restatement of the research problem. Another term for this is the research questions. The research questions are the questions you are asking about the problem. Many times, you do not solve a problem, instead, you ask questions about a problem. The answers to these questions may help to solve the problem or may not. Many people confuse the research purpose with the research questions when they are one in the same. Your goal at this step is to break a part the aspects of the problem into answerable questions. The answer to each question may contribute to solving the research problem.
This is where the research design begins. Data collection is influenced by the research questions. What you want to know influences what data you will collect. Data collection includes sampling, methods, procedures, and more.
Analysis and Interpretation
Once data is collected it is analyzed. The method of analysis is also influenced by the nature of the research questions. Interpretation is where you answer the research questions. You found a relationship between variables or you didn’t. These answers to your research questions can be used to solve the research problem.
Reporting and Evaluating Research
At this step, the information is complied in a way so that you can communicate with your audience. The format of communication depends on who you are writing for. From journal articles to science fair projects all researchers must know the expected format for communication.
Evaluation is the experience of having your work judge by others based on a certain standard. These standards are not agreed upon. This lack of agreement is another reason to know who you are writing for so you can communicate in a way that is acceptable to them.
The research process serves the purpose of finding answers to questions about problems. A researcher needs to follow the six steps of the research process in order to communicate their findings in a way that is appropriate to their audience.