Reading 1

The Craft of Research
by Wayne Booth, Gregory Colomb, et al.

Read chapters 3–6 from Part II: Asking Questions, Finding Answers.

Use the tag “R1” when you post your assessment of the text’s message and the questions it raises.

Chapter 3 and 4 explain the initiating phase of a research project: how to find a topic within a certain subject matter, and formulate a precise research question. After having selected a substance to asses, the book’s recommended process of formulating the research question follows the three-step formula of: 1) a topic, 2) an analyzable question around the topic, and 3) the significance of this (motivation of its relevance). Chapter 6 provides ideas on how to make the research more interesting. When narrowing down the research question, “creative disagreement” stood out to me as an approach that lends itself well to data visualization-fueled projects. Data that is visualized in a new or original way, can debunk prevailing ideas, expectations or urban myths - exactly because it is visualized. Based on the reading, do you think that the proposed research question should be fairly clear to the audience of a data visualization project? Or do you find it more interesting if the data visualization does not communicate a question, but leaves it up for the audience to discover its own questions?

Chs. 3-6 in Asking Questions, Finding Answers outline overall approaches to research with specific, focused, practical approaches to planning and starting to execute projects. The thing that struck me most about the reading is the emphasis on the reader. Not what research are you interested but turning the perspective around to look outwards: what is the reader interested in, what questions does the reader want me to answer? This questions my perspective, I’d thought of data visualization more as displaying factual statistics, but this reading asks me to consider showing data from a different standpoint. The topic is important but is a starting place to go from: to get to the place of both thinking of the reader’s reaction and answering follow-up questions.
I like the note that a topic is too broad if it can be summarized in 4 or 5 words. I thought that the 3 question framework to developing the topic into research questions is a useful process to explore: step 1, name your topic -> step 2, add an indirect question (I am studying this because I want to find out..) -> step 3, add the answer (in order to help my reader understand). This approach with step 3 - significance - goes further than I’d perceived as a research data visualization outlook.

Question – any recommendations for an online platform to use for compiling quotes, references, citations, research ideas?

The ‘planning your project’ section of The Craft of Research was insightful and calming, providing useful frameworks and suggestions for a research beginner – and did so in a surprisingly readable manner. What was especially useful given our current stage of research (where we all have started thinking about topics and what the appropriate scope of those topics should be for our thesis) was the structure of topic to question, specifically defining the steps in-between. Some of my recent thinking around what I might want to pursue for this thesis has be overwhelming, as I’m considering a number of broad topics that seem interesting but have a lack of refinement that leads me to feeling like I’m ‘drinking from a firehose.’ The structure of finding a topic, refining it, whittling that down to a specific question (and answering the so what about that question), then finally establishing the research problem addressed by that question (with definitions of each of these concepts along the way) feels like a cheat sheet on how to formulate an accurate and meaningful scope for our thesis project.

I particularly enjoyed the framework the authors present for formulating a thesis question: “(1) Topic: I am studying ___ (2) Question: because I want to find out what/why/how ___, (3) Significance: in order to help my reader understand ___”. This provides a formula of sorts to guide refinement of research, helping to direct general interests into reasonably refined research. I also found their tips for active reading particularly helpful – in seeing the examples of notes taken on an index card, I started envisioning and planning how I could replicate this process in Evernote to maintain an organized paper trail of my research and thinking that will help immensely in helping me reach the 10k word threshold of our research paper and keep me on track to formulating and answering a significant question in my research and data collection process.

I would be curious to know if my classmates found this reading as useful as I did, as I envision this chapter being an almost constant reference for me as I go through the initial literature review required for this week and my entire research process. A lot of what I read seemed like intuitive common sense, but I'm not sure I'd have approached my research in such a productively structured way without reading it from an expert first. It helped calm my nerves as I thought about starting my literature review by offering a playbook for this review– the “Evaluating Sources for Relevance and Reliability” section on page 76 was exactly what I needed. Did we all feel the same, or did this feel like common knowledge to the class? Do we all agree on the approaches and perspectives laid out in these chapters?

I found the reading (chapters 3–6 from The Craft of Research in the section “Asking Questions, Finding Answers”) incredibly helpful as we face the daunting task of starting our thesis. The reading provided a process of how to tackle possible topics for research, determine critical questions, glean problems those topics, and how to distinguish, understand, find, and learn to work with problems.

For somebody like myself, who is new to this sort of research, this sort of best practices in approaching research provided strong guidance and direction for how to best proceed, think critically, and make the best use of the limited time.

I found it particularly helpful: when they broke down the approach down to answering the questions: “What will be lost if you don’t answer your question? How will not answering it keep us from understanding something else better than we do? Start by asking So what? at first of yourself:
1. what you are writing about—I am working on the topic of . . .
2. what you don’t know about it—because I want to find out . . .
3. why you want your reader to know and care about it—in order to help my reader understand better . . .”

The reading acknowledges that too many research often make the mistake of writing to answer a problem that only interests alone and encourages researchers to aim to go after problems that he/she thinks the community would like to see solved. Though I agree this is what makes a thesis compelling, I find this to be no easy task that involves a lot of critical thinking and practice.

The last two chapters dealt with sources. Distinguishing between the three (primary, secondary, and tertiary), it broke down how to locate them, evaluate them, find unexpected sources, and how to use people at primary sources. The reading gave guidance on what kind of evidence to look for, tips for recording complete bibliographical data, engaging sources actively, and how to use secondary sources to find a problem and plan an argument.

Most of this made common sense, but it helped to have this sort of check list approach. However, I am finding that it is not so easy for me to distinguish between Primary, secondary, and Tertiary sources and am hoping this will get easier as I do the work.

These chapters in The Craft of Research went over the basics of how to frame your interest in a way that allow successful transitions from questions that you are personally interested in answering, to problems that are worth solving both for you and a greater audience, to identifying and utilizing sources that will help you assemble necessary information to address these problems. It clearly spelled out each step of the process of forming a proposal and conducting research. Often times, even if we have experience with research, it is difficult to figure out the most relevant question regarding the topic we are interested in, and these chapters give great guidelines on how to pursue this.

In scientific research, we are often already placed in a situation that narrows the scope of what we could pursue (ie. you've already chosen a specific lab, you are part of a team that focuses on one area of a broader problem, you are already fixated on an issue, you are given suggestions by your PI). This differs from our project, where we have been given free reign to choose our topic. Admittedly I've been having trouble narrowing the scope of my topic(s), and finding questions to answer that are unique (ie. the broad topics I'm considering are history of techno and its evolvement into the future, sexual violence in various countries, and some topic in neuroscience).

Also in science, the path from question to research is almost second nature. We have a question; we do a literature search on related topics and what researchers in the field have published; we come up with a series of experiments to answer the question. When it comes to research that depends more on secondary sources such as books rather than raw data that is collected by oneself, it becomes necessary to select sources wisely. I think going over the guideline questions raised in these chapters will assist significantly in the process of honing in on our topic.

This is a nice book about how to unlock assumptions to dig deeper for underlying questions for a particular topic.  Chapter 3 really boils down to learning to ask the right questions about a topic.  Asking questions and inquiring about events can lead to further research if these same questions are not already research in itself.  Chapter 4 focuses on transforming questions into problems or hypotheses.  The book references a topic->question->significance model to help unlock problems of significance to a field.  Page 67 references a beginners mistake to tackle a problem which is too large.  Instead, it is recommended to understanding key components to the bigger problem and perhaps work on significant problems related with the key components.  The book author notes that it is perfectly acceptable to disagree or question assumptions made by other research sources.  Chapter 5 focuses on how to find data or sources related to research problems.    The author notes the three tiers of traditional research: primary sources, secondary sources, and tertiary sources.  Primary sources are directly witnessed.  Secondary sources are research reports which cite primary sources.  And, tertiary sources are books articles written about secondary sources.  The author recommends some ways to test the validity of the source including place of publication, peer review, author, and timing.  The author notes (p. 78) that even well respected medical journals have found that there are errors made even when the articles are peer reviewed.  Finally, the chapter ends with venues where sources can be found.

The book has a nice flow and organization.  One new technique to find sources was developed by Google last year.  Their new search tool helps users find data: https://toolbox.google.com/datasetsearch.  Another useful read is "Talking to Humans" https://www.talkingtohumans.com/

When deciding on a topic to research, I like to think if people would debate my question or problem at a bar. If the topic instigates that kind of casual but passionate debate, I usually believe a visualization exploring it is justified as the exploration may lead to some sort of conclusion to that debate, or promote even more conversation. Where I work, we say this more fancily: A topic is promising if it represents an idea debated in culture.

I always struggle with finding a topic that isn’t water is wet—one with an obvious answer just simply backed by data. I liked when the reading spoke about “silly” questions. I think there’s a lot of truth in this. Two of my co-workers were interested in the size of women’s pockets as opposed to men’s pockets. The idea started with a jovial tone, but they actually followed through with it, collected the data, and produced a visualization that won an Information is Beautiful award. I’ve ran down some “silly” paths—during an internship last summer, I started pulling every transcript from the TV show The Office, analyzed the text data, and produced a visualization with my co-worker that people still ask me about to this day. One last example, for my thesis in college, I created a visual essay about one of my favorite bands. Many were confused when I told them the topic of my thesis, but I was incredibly happy with the results, as were people I showed in the music industry.

I found it incredibly helpful when the book broke down the different levels of a topic, question, and significance. One of my personal goals for 2019 is to get better at thoroughly understanding a topic deeply before I start researching it—I often jump into data before I actually know what I'm looking for. I was eventually taught to go into a dataset with a cultural question in mind. Diving head first into a dataset makes the possibility of falling down a rabbit hole much more eminent because you're aimlessly searching through data without a clear goal. I've seen this work occasionally, but not often. This excerpt from Chapter 5 encapsulates this well to me:

"To do that efficiently, you need to have a plan. If you plunge unto any and all sources on your topic, you risk losing yourself in an endless trail of books and articles."

Chapter 3 -- From Topics to Questions

“Research topic” → Something that interests me enough that I could potentially become some level of expert on it

A topic is probably too broad if it is stated in five words or less. Narrowing a topic is key. Do this by rephrasing a topic area into a full sentence (per Tolstoy example.) But don’t narrow a topic so much so that there ceases to be enough / any data available related to it!

Once I have a focused topic, it’s time to start asking questions …

• About the history of the topic
• About how this topic fits into a larger structure of something, or is it a function in a larger system/
• Can it be grouped up into different kinds, or compared and contrasted with similar topics?
• Is it subject to positive questions as well as negative ones?
• How can what if? questions be applied to it
• What questions are the sources I’m consulting with interrogating about the topic? Are they in agreement or disagreement?

Looking at all these questions, which are the good ones? And how are they significant? (the so what? aspect of the answer.)

Consider questions in the three part structure:

1. Name of the topic (I am working on/studying…..)  
2. Add a question that points to what I don’t understand about the topic (because I want to know…)
3. Name the significance of the answer (in order to ….)  

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• How to think about research topics in terms of what could make a compelling argument or research paper, but also specifically for a project rooted in data visualization? What additional questions should be attached to the three-part structure?  

Chapter 4:  From Questions to a Problem

Research roles:

Topic (I’m studying) → Data collector

Question (because…) → Researcher

Significance (in order…) → Searching for meaning!

Note: finding significance of a problem is hard.

Practical problems vs Research problems:

• A practical problem has meaningful cost/consequence in terms of time, money, physical wellness, etc
• A research problem is conceptual in nature and the answer will be meaningful because it will help build understanding of the research problem

A practical problem has a cost (ie. if we don’t answer this, this is what is going to happen!) : a research problem has a consequence (ie. if we don’t understand this, then..?)

It will be key to make clear to the reading audience that no matter what the problem, the answer will have some impact on them / their interests (either practically or conceptually)

I need to focus on forming a question that I believe to be worth answering, which will lead to finding a problem that other people will think is worth solving --- and thus determining cost/consequence for readers.

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• What problems have I identified that might be smaller parts of bigger problems?

Chapter 5 -- From Problems to Sources

There are three types of sources:

• Primary sources:  providing the raw data
• Secondary sources: research reports that incorporate primary data to solve research problems, written for journals and professional audiences
• Tertiary sources: Books and articles that synthesize secondary sources for general readers and mass-circulated publications

Note: Thorough protocols on methods of evaluating the reliability of sources, and of exploring the reference chain as means of discovering new angles on a question or new topics altogether

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• As we prepare to interview subject matter experts about our research problem, what are some guides that should be consulted surrounding the “complexities of interviewing” as referenced at the end of this chapter?

Chapter 6 -- Engaging Sources

A general rule of thumb: “Take notes more carefully than I think I need to!”

It’s important to understand what particular types of evidence (data) my audience will expect.

Other key pieces of advice on using sources:

• Record all (and full) bibliographic material
• Re-read the most important sources, at least twice
• Don’t accept claims tacitly without further interrogation

Note: creative agreement vs disagreement -- in a secondary source, what claims can I extend or interrogate with forms of contradictions?

Note: when to summarize vs paraphrase vs quote --- photocopy often! -- and make sure to always capture the context correctly

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Is this it too late to learn to speed-read?