The hardest part of research is getting started! Choosing a topic can be challenging, especially in introductory classes, when you don't really know much about the subject. The most important thing to remember is this: you are doing research, so don't make a statement about what you want to prove and then go looking for evidence to support your claim. Instead, start out with an interest, read some articles on the topic and then take a stance on the subject based on what you have learned.
Here are some tips to get you started when choosing a topic:
1. Think about the topics in your class that have interested you so far. Or, if it is the beginning of the semester, think about what you expect the course will cover and what you expect to enjoy about the class. When you added this class, what made you think it might be interesting?
2. Flip through your textbooks and look for chapter titles or subheadings that interest you.
3. Look at a magazine or journal in your subject area and look for interesting articles that might inspire you.
4. Think about controversies or current events in your subject area. Could they lead to a potential research question? If you don't know any controversies or current events for your subject, Google "Controversies in XYZ," "Disagreements in XYZ," or "Current hot topics in XYX" and see if something you find interests you.
5. Think about what you’re studying in other classes. Are there interesting ways in which they might intersect with or relate to this class?
5. Brainstorm with your classmates. Talking to each other is a good way to figure out what interests you.
How long does your paper need to be?
A shorter paper will need a more narrowly focused idea. A longer paper will allow for a more complex exploration of a topic.
How much time do you have?
If you have several weeks, it’s likely your instructor is expecting you to do a lot of research.
Do you need a a particular number or type of references?
Scholarly books and articles take time to write and publish, so topics focused narrowly on a very recent event can be problematic. If you need primary sources, choosing a topic focused on a region whose language you do not speak will be difficult.
When you first begin working on a writing assignment, it is fine to start out with a really broad idea. For example, if you are writing a paper for an introductory computer science class, you might want to focus on cyber security because that is the work field you plan to enter. That is a good starting point - choosing to do more research on an aspect of your future profession is a great idea. But cyber security is too broad of a topic.
Here are some strategies you might use to decide if your topic is too broad:
1. Type the topic (like cyber security) into a library search engine. If you get thousands of results, your topic is probably too broad. Look at some of the titles of those results to get an idea of "sub-topics" you might focus on.
2. If you type the topic into a search engine and you find whole books are written on the topic, it is definitely too broad. But scan the chapter titles of several of those books to get an idea of something more specific to focus on.
3. Sit down and brainstorm all the different angles you might take on your topic (ex. cyber security: encryption methods, types of malware, device security, types a social engineering etc). If you can list lots of different angles, any one of those might be a good way to narrow your topic - but it definitely needs to be narrower.
Finding lots of information may make you feel more comfortable at first, but here are some reasons why its important to make sure you topic is narrow enough:
1. If your topic is too broad you'll have so much information to include in your paper that you won't know how to organize it or even where to start.
2. If your topic is too broad, your reader may expect you to talk about aspects of the topic that you never address.
3. If your topic is too broad, you'll have to write more pages than your instructor assigned to cover everything you need to say. Most instructors won't accept that. Or they may take off points for it. So, you'll end up having to cut material you took time to write in order to make your paper fit the proper length.
4. If your topic is too broad, you will spend a lot of time finding articles or gathering data you will never use because you eventually have to cut material as in #3 above.
5. If your topic is too broad, it will be difficult to identify and apply the proper methods needed to analyze all the information/data you gather.
So,in short, making sure your topic is properly narrow saves you from wasting a lot of time!
We suggest two great ways to narrow your topic:
1. One option is to ask yourself who, what, where, when, why and how questions about your topic. Using cyber security as an example of a "too broad" topic, we can ask who? (what countries are responsible for hacking? who performs hacking for corporate espionage?) and how? (types of malware, types of social engineering) and where? (on networks, computers, phones, smart devices). If we were writing a historical overview of cyber security, we might have narrowed our focus by asking "when". Then our topic might have narrowed like this: A comparison of how hacking has evolved since the dawn of the Internet of Things (ex. smart refrigerators, coffee pots etc).
Below is a video of how this might work using an example from an American history class:
2. A second option is to create a concept map. To create a concept map, write down your broad topic in the middle of a piece of paper. Then brainstorm associated ideas. The terms you write down will likely be good directions to take when narrowing your topic. Here is an example of a concept map:
Here is a video showing how to develop a concept map and use it to create a research statement:
So, returning to our example of cyber security, we might finally decide to write about user education (who? - users) to prevent phishing attacks (what? - phishing attacks)?
Once you have done enough research to narrow your topic to something manageable, you are probably ready to formulate your research question. For college-level research, you will start out with a question, look at all the evidence and then draw a conclusion based on that evidence. Therefore, your research must begin with a research question - a statement that identifies what you are going to study.
To formulate your research question you might:
1. Start with the topic that you have decided upon and then list all the questions that you'd like answered about it yourself. Brainstorm, alone or with another student or with your professor, on all the questions the topic raises in your mind.
2. For beginning researchers, a good way to identify possible research questions is to look at previous studies on the topic. While reading the research studies, look for places where the authors of the studies mention "more research is needed" or "XYZ angle was not included in this study." These statements might indicate gaps in the current research.
3. Another way to use existing studies is to identify a type of study that has been done on one population, but not another. For example, referring again to our computer science research project on which types of user education mitigate social engineering attacks, what if your preliminary research showed there have been many studies on "white collar" workers but none that focused on "blue collar" workers. A study that focused on blue collar workers might offer a new angle for research.
4. A final way to use existing research studies to identify a research question is to look for indications of controversy. If numerous recent studies mention a particular angle of research on the topic is controversial, that indicates there is still a need for study on that angle.
Your individual classes will address in depth the characteristics of a good research question in your discipline. We can make a few generalizations about good research questions at the introductory level here. A good research question:
1. Can be answered objectively, with evidence. It is not solely value-based.
Too subjective: Is social media bad?
"Bad" is a value judgment. It cannot be quantified or measured.
Less subjective: Does excessive use of social media lead to social withdrawal in middle-school students?
"Excessive use" is a term that can be quantifiably defined. "Social withdrawal" can also be defined by a set of named behaviors. This research question is measurable.
2. Can be answered with evidence that already exists or with evidence that can be gathered through experimentation you can design.
Impossible to answer: How can we prevent social engineering?
We will never be able to eradicate social engineering as a means of hacking. Hackers will come up with new approaches constantly and it is impossible to educate every user about every hacking strategy.
Maybe impossible to answer: What impact does computer-based training have on social engineering?
Who will you test? If you want to focus on educating and then testing a population you don't have access to - for example, high school students - this question may be impossible to answer. It needs further definition.
Possible to answer: What impact does computer-based training have on social engineering amongst the student population at Centre College?
You can design an experiment where Centre College students take computer-based training on social engineering methods, expose them to a social engineering attack and measure how they respond. In other words, you have access to an appropriate testing population; you have the necessary skills to design this study; you have the money to conduct the study. you have the time to conduct the study.
3. Is adequately focused.
Too unfocused/broad: What are the effects of user-education on social engineering attacks?
This question is so broad that research methodology would be very difficult to design. If I can't even state the possible "effects" how do I know what I'm testing for?
More focused: Does computer-based training or face-to-face instruction better address the human psychological traits that social engineering hackers exploit?
This question still allows the researcher to study an "effect" of user education to mitigate social engineering - the human psychological traits- but it has a clearer focus for which data should be collected, analyzed, and discussed.
4. Is significant.
Too narrow: What methods are there to mitigate social engineering attacks?
This is too narrow because it can be answered with a simple list of methods. Questions that can be answered with a "yes" or a "no," list or statistics should be avoided.
Too simple: How are security engineers mitigating social engineering attacks?
This question could be answered with a simple online search or with some telephone calls. It provides a little more opportunity for analysis than a simple list, but it does not allow for conclusions to be drawn.
More significant: Which method of social engineering mitigation - computer-based user education, face-to-face user education or tool-based solutions - best prevents social engineering attacks?
This question provides an answer that would benefit many companies and it offers an opportunity to conduct a study and draw conclusions based on evidence gathered.
The type of methodology you will use for your research depends greatly on your field of study. Biologists, economists, historians, literature scholars - they all have vastly different methods of gathering evidence that suit their fields. For now, it would help to understand that in some fields, especially the humanities (literature, history, religion etc), research is often "qualitative." Qualitative research focuses on relationships between people or texts. It seeks to to understand people's beliefs, experiences, attitudes, behavior, and interactions in a non-numeric way. For example, a scholar of literature might exam a wide body of medieval texts to answer the question: How was the LGBTQ+ community portrayed in the writings of a certain author. To answer that question, the scholar will examine a body of texts for all references to LGBTQ+ characters or interactions and how they were portrayed/perceived by other characters. They will then draw a conclusion based on that evidence on the perception of LGBTQ+ characters by that author in that time period.
Physical and social scientists (ex. biologists, psychologists, economists), in contrast, typically conduct quantitative research. Quantitative research emphasizes objective measurements and the statistical, mathematical, or numerical analysis of data collected through direct experiments, polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques. Your goal in conducting quantitative research study is to determine the relationship between one thing [an independent variable] and another [a dependent or outcome variable] within a population. Quantitative research designs are either descriptive [subjects usually measured once] or experimental [subjects measured before and after a treatment]. A descriptive study establishes only associations between variables; an experimental study establishes causality.
You will focus on discipline-appropriate methodologies in your classes, but having at least this introduction will help you understand why certain questions aren't really research questions - they can't be tested and they don't allow for analysis or conclusions.
Babbie, Earl R. The Practice of Social Research. 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods. 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches. 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Quantitative Research Methods. Writing@CSU. Colorado State University; Singh, Kultar. Quantitative Social Research Methods. Los Angeles, CA: Sage, 2007.
Once you have developed your research question and you have done some preliminary reading on your topic, you are ready to form your thesis statement or hypothesis. Depending on your discipline, your thesis or hypothesis will have very specific requirements. You will learn about those requirements in your classes. Here, we will make a general introduction to the thesis or hypothesis statement.
A thesis statement may be seen in quantitative, qualitative, and mixed methods research.
A thesis statement is a short, direct sentence that summarizes the main point or claim of an essay or research paper. It It is developed, supported, and explained in the body of the essay or research report by means of examples and evidence.
A good thesis statement:
The following is an example of a strong thesis statement in the context of the introduction paragraphs of a history paper:
Ritchie, Daniel. “War, Religion and Anti-Slavery Ideology: Isaac Nelson’s Radical Abolitionist Examination of the American Civil War.” Historical Research, vol. 89, no. 246, Nov. 2016, pp. 799–823. EBSCOhost, doi:10.1111/1468-2281.12134.
Hypotheses are typically used in quantitative research.
A hypothesis is a formal statement that predicts a measurable relationship between two or more variables. A well stated, researchable hypothesis:
To properly formulate a hypothesis, it is helpful to understand the different types of variables that it must operationalize:
Dependent variable: the target organism; who or what is affected.
Independent variable: who or what will affect the target organism; the variable the researcher will manipulate to see if it will make the dependent variable change.
Control variable(s): variables that must be held constant to ensure that the independent variable is the only variable affecting the dependent variable.
There are several types of hypotheses that you might formulate:
Simple hypothesis - predicts the relationship between a single independent variable (IV) and a single dependent variable (DV).
For example: Computer-based training (IV) is associated with lower susceptibility to social engineering attacks (DV).
Complex hypothesis - predicts the relationship between two or more independent variables, and two or more dependent variables.
For example: The implementation of a computer-based training program (IV) will result in (DV):
decreased user susceptibility to social engineering attacks;
increased user confidence in the ability to recognize social engineering attacks;
Null hypotheses - the hypothesis that there is no significant correlation or difference between specified populations, any observed difference being due to sampling or experimental error.
For example: Computer-based training will have no significant effect on susceptibility to social engineering attacks.
Directional hypothesis - predicts positive or negative correlation or change.
There is a positive correlation between user education and user confidence in the ability to recognize a social engineering attack.
Users receiving computer-based training will succumb less frequently to phishing attacks than users who do not receive training.
Nondirectional hypothesis - predicts the independent variable will affect the dependent variable, but the direction of the effect is not specified.
For example: There will be a difference in how users trained by computer-based methods and face-to-face training methods respond to social engineering attacks. (As opposed to: Users trained with face-to-face methods will succumb to fewer social engineering attacks than users trained with computer-based methods).