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What is it that researchers do? They ask and answer questions. This process entails two logical correlates:\u00a01) a question must be asked in a way that can be measured; 2) a method must be devised that answers the question as asked. Writing like a psych researcher begins with asking questions the way a psychologist would.<\/p>\n
Before diving into devising research questions, spend a moment delving into where your research interests spring from. Start at the most general level by asking yourself what aspects of the human experience capture your attention\u00a0— what makes your eyes shine in wonder or face-palm in fury? What makes you want to fist bump the human race for its sheer coolness factor or rage from an interstellar podium for its boundless stupidity? Finishing a research projects hinges on motivation, and one of the first things to figure out about yourself is whether you get staying power from things that make you happy or things that make you mad. In my experience, it’s about a 3:1 ratio — approximately 75% of researchers follow the things that make them smile while the other 25% find more motivation in things that make them mad. Eventually, as you get into a research topic, curiosity is enough of a driver, but to get started, a little emotional investment goes a long way.<\/p>\n
(from Trochim, Research Methods Knowledge Base<\/a>, Type of Questions<\/a>)<\/p>\n There are three basic types of questions that research projects can address:<\/small> \u00a0\u00a0 2. Relational<\/strong>. \u00a0When a study is designed to look at the relationships between two or more variables. A public opinion poll that compares what proportion of males and females say they would vote for a Democratic or a Republican candidate in the next presidential election is essentially studying the relationship between gender and voting preference.<\/small><\/p>\n \u00a0\u00a0 3. Causal.<\/strong> \u00a0When a study is designed to determine whether one or more variables (e.g., a program or treatment variable) causes or affects one or more outcome variables. If we did a public opinion poll to try to determine whether a recent political advertising campaign changed voter preferences, we would essentially be studying whether the campaign (cause) changed the proportion of voters who would vote Democratic or Republican (effect).<\/small><\/p>\n The three question types can be viewed as cumulative. That is, a relational study assumes that you can first describe (by measuring or observing) each of the variables you are trying to relate. And, a causal study assumes that you can describe both the cause and effect variables and that you can show that they are related to each other. Causal studies are probably the most demanding of the three.<\/small><\/p>\n A good Research Question (RQ) is specific enough to be answered, broad enough to be discussed, and significant enough to be of interest to the field. Below are some tips to help you formulate a RQ that is both personally meaningful and researchable, meaning that the RQ is asked in a way that can be measured. Measurability results from generating data that can be analyzed in component parts, whether the parts are units of meaning (e.g., thematic analysis<\/a>) or numbers\/statistics.<\/p>\n Research questions have two parts: a topic and something asked about that topic. The topic comes from your interests as a researcher\/thinker (with consideration eventually given to the current interests of your field). The “what about the topic” also comes from your interests but is formulated using the “wh-question words”: who, what, why, when, where, how, how much\/often\/many. Often, those two steps don\u2019t result in a good RQ\u2014remember, that a successful RQ is one that is answerable and researchable. So, after determining the topic and some idea of “what about” the topic, do the following: define and operationalize the major terms as well as\u00a0qualities or relationships (“qualities” are pieces of language that describe something). Operationalizing a term means to define it so that it can be measured; this often means matching ideas\/concepts to behaviors.<\/p>\n The example below is a “think aloud” model, distilled from real-life encounters which social-behavioral science types are hard-wired (or “doomed” :-)) to turn into research questions.<\/p>\n At this point, general curiosity evolves into real questions: what exactly is the relationship student have to their mobile devices? Why can’t they turn them off? What about using devices creates such a powerful relationship that some cannot even bear to be more than an arm’s length away? Is this a generational difference, a personality difference, some blend thereof? How does this start? When does the device become problematic? If not problematic, per se, then what are the characteristics of a “healthy” relationship to devices? Do Ss even see their devices as pieces of machinery? If so, under what conditions, and when does it change to something else, assuming that this happens?<\/p>\n And so on and so on!\u00a0A couple of observations yields a nearly infinite number of questions.<\/p>\n Some of these questions have answers in the literature, but many do not. Thus, the researcher must narrow in on a single question or highly-related set of questions. In this scenario, the researcher might grow particularly interested in the intersection of two questions: the relationship to devices as something other than machines and generational differences in perceptions of devices. In psychology, the concept of “developmental path” captures the idea that there is a regular, systematic way in which some skill, behavior, ability, phenomena, etc changes from a beginning state to an end state. Developmental paths can be mediated by age, with learning language being the prime example; however, it’s equally common for learned behaviors and states of being to follow\u00a0a predictable sequence. Eventually, a larger RQ may emerge:\u00a0perhaps, “is there a developmental path that mobile device users progress along?”<\/p>\n This question entails a beginning state and an end state, neither of which are defined in this context. To investigate this question, research must necessarily be exploratory, asking many different kinds of questions to get at both behavior and perceptions. \u00a0Broadly speaking, let’s say the researcher wants to know both how people obtain and use mobile devices (across different age groups), when device use starts, and what relationship device users have to the functions of their machines. The researcher decides to ask counting questions for behavioral stuff (how often, how much, etc) and open-ended questions about perceptions and feelings. From the morass of data, a development pattern may emerge. A cross-sectional design is chosen to get a picture of results across multiple generations. This is critical because in another 50 years, there won’t be a generation who grew up without mobile devices.<\/p>\n The research scenario above results in 2 kinds of data: quantitative (results that can be counted) and qualitative (results that are analyzed thematically, according to patterns of meaning). In the Social and Behavioral Sciences, these are the two main methodologies represented in published\u00a0research reports: the quantitative report<\/strong> and the qualitative report<\/strong>. They are distinguished by the kind of research design used to gather information, which is reflected in the way the research report gets written.<\/p>\n In quantitative studies, the research question is tested using methods that will produce numerical results, usually manipulated by statistical tests. We are very familiar with this kind of research and it is the hallmark of the scientific method. In social and behavioral science, such methods include surveys, some kinds of interviews, and experimental manipulation. The resulting paper uses functional subheadings to move the reader through the text: Introduction, Method, Results, Discussion.<\/p>\n Qualitative research relies on\u00a0meanings\u00a0and good thinking. The results are not usually numerical, but represented as text with analysis and explanation. Qualitative research\u00a0generates data through words (open-ended surveys or interviews) or observation (video). Whatever the nature of the data, patterns are elicited through coding techniques that identify repeating elements. Ideas or behavioral instances that repeat in multiple contexts or across multiple participants form the basis of the results. The resulting paper employs both functional subheadings (Introduction, Discussion) and topical subheadings indicating thematic categories (the Results of the investigation).<\/p>\n <\/p>\n What do you expect when you sit down to read a scientific article? You want to know \u201cwhat happened?\u201d and “why should I care?\u201d. These are the two main questions that any research report has to answer. Historically, scientists themselves created a standardized format through which to answer these questions \u2192 this is the \u201cresearch report\u201d, and while each discipline has a slightly different take on how to write one, all science publication on experimental data is composed of 4 parts, each answering some part of \u201cwhat happened?\u201d and \u201cwhy does it matter?\u201d. The Introduction tackles motivation, providing part of the answer to why the reader should care. \u00a0It does so in 5 steps; that is, 5 informational moves that both inform and persuade.<\/span><\/p>\n How are these goals accomplished? The writer provides a brief review of the literature in the correct order (given below!). The content of the introduction informs; the organization of the introduction persuades.<\/p>\n 1) Establish Topic — quick, concise (what is being studied) Let’s take a look at an example!<\/p>\n Example (Quantitative) ||\u00a0A Psychological Exploration of Engagement in Geek Culture<\/a><\/p>\n A geek is traditionally defined as an enthusiast who develops expertise on a topic through exceptional determination and devotion [1]. The word \u201cgeek\u201d is used to describe not only enthusiasts in science, technology, and engineering but also especially devoted fans of media (i.e., \u201cfandom geeks\u201d). Here, we refer to geek culture<\/strong> as a subculture of enthusiasts that is traditionally associated with obscure media (Japanese animation, science fiction, video games, etc.).<\/span> However, geek culture is becoming an increasingly mainstream influence<\/strong> on contemporary culture.<\/span> Geek culture includes a range of activities such as role-playing games (e.g., Dungeons and Dragons), science fiction (e.g., Star Trek), comic books, and dressing in costumes (i.e., cosplay). Although geek interests were once marginalized [2], comic book movie adaptations (e.g., Iron Man, Thor) [3] are now major box office draws. Likewise, science-fiction (sci-fi) and fantasy themed video games (e.g., World of Warcraft) have become multi-billion dollar industries. There has also been enormous growth in geek conventions such as Comic-con and Dragon*Con. In the past year alone, New York Comic-Con, one of the premier geek conventions in the United States, attracted over 130,000 attendees [4] and Dragon*Con in Atlanta has grown from 2,400 fans in 1989 to 57,000 fans in 2013 [5].<\/span><\/small><\/p>\n Despite the popularity of geek culture, it has received little attention from the social sciences<\/strong>. Yet this increasing tendency of individuals to engage in a culture with heroic and magical themes may be linked to important trends in our wider culture, such as increasing narcissism[6], thwarted belongingness [7], and the interface between technology and entertainment media.<\/span> In the present paper, we have two primary goals. First, we develop and validate the construct of geek engagement as participation in specific activities represented at major geek conventions. Second, we describe and examine three new theoretical accounts of geek culture related to the cultural trends above, which we refer to as the great fantasy migration hypothesis, the belongingness hypothesis, and the desire for engagement hypothesis<\/strong>. These theoretical accounts are not considered to be mutually exclusive\u2014participation in geek culture is almost certainly determined by multiple factors and several of these hypotheses share predictions. This research is designed to be the first rather than last word on these hypotheses.<\/span><\/small><\/p>\n To these ends, we present results from 7 studies (N = 2354). These include construct operationalization and scale development (Studies 1\u20132), and examination of personality, self-concept, intelligence and other individual differences variables associated with geek engagement as well as a social network analysis of geek culture (Studies 2\u20137). Before we begin, however, we (a) define geek culture, and (b) describe three theoretical accounts.<\/small><\/p>\n Analysis: In terms of color, each of the 5 steps works as follows: 1) Topic: Blue<\/span>; 2) Significance: Orange<\/span>; 3) Lit Review: Green<\/span>; 4) Gap: Brown<\/span>; 5) RQ: Purple.<\/span> The bolded items emphasize the central information in each section. Let’s examine each briefly.<\/p>\n The final paragraph of this Introduction presents a roadmap of where the paper is going after the Introduction. This is not a common step, but makes sense in this paper because it is part of a larger investigation and also includes a separate lit review following the Intro\u00a0which covers\u00a0the topic and theoretical literature in more depth. Not all psych research reports require this step, but a longer literature review is common when the research question itself is complex and\/or exploratory.<\/p>\n Example (Qualitative) ||\u00a0Socio-Psychological Factors Driving Adult Vaccination: A Qualitative Study<\/a><\/p>\n
\n1. Descriptive<\/strong>. \u00a0When a study is designed primarily to describe what is going on or what exists. Public opinion polls that seek only to describe the proportion of people who hold various opinions are primarily descriptive in nature. For instance, if we want to know what percent of the population would vote for a Democratic or a Republican in the next presidential election, we are simply interested in describing something.<\/small><\/p>\nA Process for Formulating Questions<\/h5>\n
Research Question Scenario<\/h5>\n
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\/end RQ Scenario\/<\/h5>\n
RQ + Method = Research Report<\/h4>\n
Contents<\/h3>\n
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Writing Introductions<\/h2>\n
…Next comes the most important paragraph of the whole paper: the first one. Even if it is a work of expositional genius, few among a broad audience are likely to read beyond it. So it is vital that this paragraph tells the central story of the paper, and makes clear why this story deserves to be told. Elements of Style<\/a>, Nature Physics<\/small><\/p><\/blockquote>\n5 steps to Writing the Introduction<\/h4>\n
\n2) Provide significance — research, practical, clinical (why it is generally important)
\n3) Review the relevant literature — what the expert literature reveals (what we know already)
\n4) Point out the gap — what’s missing in the research literature (what we don’t know — motivation for study)
\n5) Reveal the research question (and sometimes, hypotheses) — the specifics of this research<\/p>\n\n
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