Reading Academic Research

Amanda Williams; Emma Duke

3 Reading Academic Research

Learning Objectives for Chapter

Identify and explain the five key features of a good research question.
Differentiate between strong and weak research questions.
Identify the main sections contained in scholarly journal articles.
Evaluate key questions to be asked when analysing published academic research.

Introduction

One of the keyways we begin to understand reading research methods is via academic articles. They can and are often avoided by students. However, it is hoped that with some additional guidance around how to formulate good research questions, how to identify the parts of a research paper and read it more critically, these documents can become more accessible and hopefully something you want to incorporate into your professional practice instead of avoiding them!

Research Questions

All good research projects start with a strong research question. But what makes a good research question? There are at least five components to a good research question worth considering.

Firstly, while it may seem obvious that a well-formed research question takes the shape of an inquiry. To elaborate, it should be framed as a question that explicitly conveys the essence of the research’s focus.

For instance, a research question should not merely present a statement like “explore the concept of being a child-free adult.” Instead, it should transform this into an interrogative format such as: “What are the lived experiences of adults who choose a child-free lifestyle?” or “How does the media construct experiences of adults who choose a child-free lifestyle?” The formulation of an effective research question necessitates clarity and precision. Another example might be that instead of trying to “investigate students’ knowledge about current events or movies, a strong research question should be restructured to distinctly specify the research intention and might be: “How does exposure to current events through news media impact students’ critical thinking skills?” or “What are the factors influencing students’ preferences of movies from different genres?” In essence, crafting a research question involves transforming a topic of interest into a succinct and probing inquiry.

Secondly, a good research question is one that is well-focused. A well-focused research question is essential for guiding a study in a clear and purposeful direction. It narrows the scope of investigation to a specific and manageable topic, ensuring that the research remains targeted and efficient. This focus helps researchers avoid becoming overwhelmed by a broad or vague subject area and enables them to delve deeper into the particular aspects that matter most.

For instance, consider a research question about the effects of technology on children’s learning. While this is a broad topic, a well-focused question could be: “How does the use of educational apps impact the vocabulary acquisition of preschool children?” This focused question narrows down the study to a specific technology (educational apps), a specific age group (preschool children), and a specific outcome (vocabulary acquisition). Imagine a researcher is interested in studying the relationship between diet and heart health. A broad question might be: “How do diets influence cardiovascular health?” However, a well-focused research question could be: “What is the effect of a Mediterranean diet on reducing cholesterol levels in adults with high blood pressure?” This focused question specifies the type of diet (Mediterranean), the target population (adults with high blood pressure), and the outcome of interest (reducing cholesterol levels). In essence, a well-focused research question illuminates a particular angle of inquiry within a broader subject.

Thirdly, a good research question is one that cannot be answered with a simple yes or no. Imagine you’re trying to figure out something interesting about how people think about gender norms. At first, you might think of a question like, “Does gender affect how much someone shaves?” If you just get a “yes” or “no” answer, you might not have much else to say. This kind of question limits what you can learn from an investigation. Once you know the answer is “yes” or “no,” the investigation kind of stops. There’s not much more to discuss. Now, think about a different way to ask the question: “How does gender influence how someone feels about body hair?” This new question goes beyond just “yes” or “no.” It challenges researchers to dig deeper, explore more, and really understand all the different parts of the topic.

Fourthly, a good research question should be open to different possible answers. For example, here are two questions:

“What year was the first telegraph message sent?”
“How did different cultures use the telegraph to disrupt existing forms of communication?”

Which one makes a better research question? You likely answered two, but do you know why?

The second question is open-ended, inviting diverse interpretations and possible answers. This stimulates critical thinking, encourages researchers to uncover lesser-known historical facts, and enables them to draw connections that could contribute to a broader understanding of communication history. The question prompts research into intricate interactions between technology and culture. By exploring how the telegraph disrupted existing communication methods, researchers can uncover multifaceted narratives that involve not only technological aspects but also societal norms, economic factors, and cultural values. In contrast, while historically notable, the question concerning the first telegraph message’s year confines itself to a single answer. It lacks the intricate layers of analysis, critical thought, and multi-dimensional exploration.

Finally, a strong research question should consider the relationship among multiple concepts. For example, let’s say you are interested in how to be an effective public speaker. You might ask: “How does body language affect public speaking effectiveness?” However, why not open this up to a more sophisticated analysis by exploring the following question instead: “How does body language, vocal tone, and choice of words influence the overall effectiveness of public speaking in diverse cultural contexts?” This second question does not just focus on body language. In this case public speaking is not just about verbal delivery but also about nonverbal cues, cultural and social contexts associated with language choices, and interpersonal and intercultural dynamics. By thinking about these different dimensions, the researcher can draw on insights from complementary academic traditions to situate their findings including linguistics, communication studies, psychology, and cultural studies. This allows for a more well-rounded answer to emerge.

In sum, a good research question generally has the following features:

It is written in the form of a question.
It is clearly focused.
It is not a yes/no question (i.e. or is open ended).
It has more than one plausible answer.
It considers relationships among multiple concepts.

These criteria provide a great benchmark to begin evaluating research studies and consider how they might be used in the knowledge translation process.

Reading About Research Methods

Beyond just a research question, most research papers generally consist of several core parts that serve specific purposes in presenting and communicating the research findings. Here are the key components commonly found in research papers:

Title: The title serves as a concise and informative representation of the paper’s content, offering readers an initial glimpse into the subject matter and the extent of the research investigation. An effective title encapsulates the essence of the study, guiding readers’ expectations and piquing their interest in delving further into the paper’s contents.
Abstract: The abstract is typically about 150-250 words and summarises the paper’s contents by outlining the research question, methodological approach, and key findings. This compact snapshot provides readers with a rapid overview of the central components of the study helping a reader quickly assess its relevance,
Introduction: This section initiates the exploration by introducing the research’s subject matter, underlining its importance, and furnishing historical context. It typically should end with a research question or hypothesis, laying the groundwork for the paper’s content and objectives.
Literature Review: A comprehensive literature review delves into existing scholarly contributions related to the research’s focus. This section contextualises the study, identifies gaps within the current knowledge framework, and establishes a rationale for pursuing new insights through the present investigation. It does not provide new data but summarises what has been done so far.
Methodology: The methodology outlines the research design, detailing the procedures, techniques, and tools employed for data collection and analysis. By providing a transparent review, this section allows fellow researchers to replicate the study, assess its methodological soundness, and ultimately verifies the findings credibility.
Results: The results section presents the empirical findings emanating from data analysis. Tables, figures, and descriptive explanations are ways that the research data is often presented.
Discussion: The discussion offers an interpretation of the results within the context of the research question. It illuminates the implications of the findings, examines their broader significance, and contrasts them against prior studies, aiming for connections and to further future scholarly outputs.
Conclusion: In the conclusion, the principal findings are typically succinctly summarised, and their overarching implications highlighted. Study limitations and future research projects are usually offered.
References: The references section assembles an exhaustive list of all cited sources, providing readers with the means to follow up regarding specific areas of interest. It enhances the paper’s credibility.
Appendices: The appendices provide supplementary information (for example the survey instrument or interview protocol followed), or additional data that complement the main body of the paper. While not integral to the central narrative, these materials may enrich the reader’s understanding or allow for greater transparency.

These core parts collectively guide readers through the research process, from understanding the context and rationale to interpreting the findings and implications. Researchers use this structure to present their work systematically and coherently, ensuring that their findings are accessible and credible to the academic community and beyond.

Unpacking Tables

As noted in the previous section, tables are often used in the discussion section. They are like a quick, summarised way of showing the most important parts of the research. Tables help to put lots of information in one place so you can understand it more easily.

How Tables Work

Some tables present descriptive information about a researcher’s sample. For example, if gender was an important variable for a researcher’s analysis, they might include how many men vs. women were participants in the study. “How many” or a frequency will usually be listed as the initial N, whereas the percent symbol (%) would be used to indicate percentages.

In a research study, a variable refers to any characteristic, attribute, or quantity that can be measured, observed, or controlled. Variables are essential to a study as they allow researchers to investigate and understand relationships, patterns, and effects within a research question.

In a research study, the terms “independent variable” and “dependent variable” describe two key components of the experiment or investigation. They play a crucial role in understanding cause-and-effect relationships between different factors under study.

The independent variable (IV) is the factor or condition the researcher deliberately manipulates or controls in an experiment. It is the variable thought to impact the dependent variable. The independent variable represents the cause or input in the study. Researchers change or vary the independent variable to observe its impact on the dependent variable.

For instance, in a study investigating the effect of different study techniques on exam scores, the independent variable would be the study technique being used. The researcher may use various study methods, such as reading, summarising, or practising with flashcards.

It is important to note that the term “independent variable” is commonly used in quantitative research, particularly in experimental and quasi-experimental studies, where researchers aim to establish cause-and-effect relationships between variables. In contrast, in qualitative research, the concept of independent variables is less commonly used, as the focus is often on exploring complex phenomena and understanding the context rather than on manipulation and control.

Alternatively, the dependent variable (DV) is the outcome or response measured or observed in the experiment. It is the variable that is expected to change as a result of variations in the independent variable. The dependent variable represents the effect or outcome of the study.

As an example, in the study mentioned earlier, the dependent variable would be the exam scores of the participants. The researcher would measure how well the participants perform in the exam based on their different study techniques.

Demographics are typically considered independent variables in a research study. Demographics refer to characteristics or attributes of a population or sample, such as age, gender, ethnicity, income, education level, and so on. These characteristics are inherent to the individuals being studied and are not subject to manipulation by the researcher during the course of the study.

Demographics are treated as independent variables because they are used to categorise or describe the participants in a study based on certain characteristics. Researchers often use demographic variables to analyse and compare data across different groups. These variables are not influenced or affected by the study’s manipulation or intervention, which is why they are independent.

In contrast, the dependent variable is the outcome or response that the researcher measures or observes to see if it is influenced by changes in the independent variable. The dependent variable is the focus of the study, and researchers aim to understand how it varies in response to different conditions or levels of the independent variable.

To illustrate the difference, a study on the relationship between age (a demographic independent variable) and smartphone usage (the dependent variable) among a sample of participants.

In this example, the researchers would categorise the participants into different age groups based on their demographics (e.g., 18-25, 26-35, 36-45, etc.). The researchers do not manipulate the participants’ age groups; they already exist as inherent characteristics of the participants. The researchers would then measure and analyse smartphone usage (dependent variable) across these age groups to determine any patterns or relationships between age and smartphone usage.

In summary, demographics are independent variables because they are not manipulated during the study and are used to categorise participants or describe the characteristics of the sample, whereas the dependent variable is the outcome or response that is measured or observed to assess its relationship with the independent variables.

The goal of manipulating and measuring the independent and dependent variables is to establish a cause-and-effect relationship between them. By controlling all other variables (known as extraneous variables) and focusing solely on the independent and dependent variables, researchers can draw meaningful conclusions about the impact of the independent variable on the dependent variable.

It’s important to note that in some research designs, there may be more than one independent variable or more than one dependent variable. Additionally, the distinction between the two types of variables may not always be straightforward, depending on the complexity of the study. However, understanding the concept of independent and dependent variables is fundamental to designing and interpreting research findings accurately.

If a table presents a causal relationship (where the dependent variable changes based on the independent variable), independent variables are typically located in the table’s columns, and dependent variables can be found in the rows.

You can scan the rows to see how the values on the dependent variables change as the independent variable changes. In tables presenting quantitative data, you can usually find some information regarding the strength and statistical significance of the analysis. Statistical significance refers to a statistical concept that helps researchers determine whether an observed result is likely to be a real effect or if it could have occurred by chance. In other words, it helps researchers assess whether the relationship or difference they observe in their data is meaningful and not just random.

When a finding is said to be statistically significant, the results are unlikely to have occurred due to random fluctuations in the data. Instead, they suggest that there is a genuine relationship or difference between the variables being studied.

Statistical significance is typically determined through hypothesis testing. Researchers formulate a null hypothesis, which assumes that there is no true effect or relationship, and an alternative hypothesis, which posits that there is a real effect. They then analyse the data to see if the observed results are so extreme that they would rarely occur if the null hypothesis were true.

If the p-value (probability value) associated with the statistical test is below a predetermined threshold (often 0.05), researchers may conclude that the result is statistically significant. This means that the observed effect is unlikely to have occurred purely by chance, and there is evidence to support the alternative hypothesis.

The null hypothesis is the assumption that no relationship exists between the variables. For example, if the p value is 0.039%, it means that there is a 3.9% that the null hypothesis is correct. If the p value is less than 0.05, we would say that this is not statistically significant, and we can reject the null hypothesis. We would fail to reject the null hypothesis if the p value is 0.05 or greater.

To illustrate, imagine you come across a p value of 0.039%. This signifies a mere 3.9% chance that the null hypothesis holds true – a small indication that a relationship might indeed be present. When the p value dips below the critical threshold of 0.05, it signals a lack of statistical significance. In this scenario, you’re inclined to reject the null hypothesis, indicating that the variables likely share a meaningful connection.

Conversely, when the p value reaches or exceeds 0.05, it ushers in a different outcome. Here, you would refrain from dismissing the null hypothesis. Instead, you acknowledge that the data doesn’t provide enough substantial evidence to sway you in favour of rejecting the initial assumption.

By understanding the nuances of the p value, you equip yourself with a powerful tool to decipher the significance – or lack thereof – of research findings. However, it is important to note that statistical significance does not necessarily imply practical or meaningful significance. A finding can be statistically significant but have a very small or negligible effect in real-world terms. Researchers need to interpret statistical significance within the context of their study and consider the practical implications of the results.

Questions Worth Asking While Reading Research Articles

Media professionals play a crucial role in interpreting and communicating academic research to the public. When evaluating an academic research article for journalistic purposes, there are several key questions they should consider:

What is the Research Question or Hypothesis?

Media professionals should start by understanding the central inquiry the researchers aimed to address. This sets the stage for the entire study and helps readers grasp the article’s focus. Some great rules about what makes research good were given at the start of this chapter.

Who Conducted the Research?

Investigating the authors’ credentials and affiliations is essential. It is important to verify if they are experts in the field and affiliated with respected institutions or organisations. This can impact the credibility of the research.

What is Methodology?

Understanding the research methods used is crucial for assessing the study’s validity. Media professionals should investigate whether the methods align with the research question and are widely accepted in the academic community. Some additional tips about this will come in the chapters that follow.

What is the Sample Size and Composition?

Evaluating the size and characteristics of the sample helps readers determine if the findings can be generalised to a broader population. A small or unrepresentative sample may limit the study’s significance.

What were the Findings?

Readers should extract the main outcomes and results of the research. This involves identifying key data points, trends, or correlations that emerged from the study.

What are the Limitations?

Recognizing the study’s limitations provides a balanced perspective. Factors such as potential biases, flaws in methodology, or aspects that could impact the accuracy of the findings are all things to consider.

Has the Study Been Peer-Reviewed?

As noted previously, a peer-reviewed study has undergone scrutiny by experts in the field, enhancing its credibility. Asking whether a research article has been through this rigorous evaluation process is key.

Is the Article Published in a Reputable Journal?

The reputation of the journal matters. Whether the publication has a high impact factor, rigorous review process, and is respected within the academic community are all worth exploring.

Is the Article Accessible to the Public?

Accessibility is essential t for effective dissemination. Is the article behind a paywall or freely available, which impacts how widely the research can be shared and understood, may be important.

Are There Conflicts of Interest?

Scrutinising potential conflicts of interest is essential. Whether the authors have financial or personal interests that could influence the study’s outcomes is always worth considering.

Are the Findings Put in Context?

The work should contextualise the research within the broader body of knowledge. Highlighting how the findings contribute to or challenge existing understanding provides a more nuanced perspective.

Has the Research Been Replicated?

Replication enhances the reliability of research. Whether other researchers have attempted to replicate the study’s results and whether they achieved similar outcomes is often a great question.

Are There Practical Takeaways?

Translating complex findings into practical insights is valuable for the audience. Media professionals should explore whether the research has implications for everyday life, policy-making, or specific actions.

Additional considerations can be found in the table below.

Figure 3.1

Questions on Report Sections

By addressing these questions, media professionals can effectively analyse, interpret, and communicate academic research to the public in a comprehensive, accurate, and informative manner.

Reflection Question

How can using well-crafted research questions and understanding the structure of academic articles improve your ability to read, understand, and apply research in your future career? Document your thoughts in a 200–300 word post.

Key Chapter Takeaways

There are at least five components to a good research question worth considering which include: containing a question format, having a proper focus, not confined to a yes or no answer, allowing for unexpected answers to emerge, and including multiple concepts to be measured.
Tables provide important information about a paper and can often include p values that determine the findings’ strength in statistical terms.
Media professionals play an important role in explaining and sharing academic research with the public. They should be critical when looking at a research article to use in their news work.

Key Terms

Research question: A way of framing a researcher’s particular area of interest. Good research questions have five key features: written in the form of a question, focused, not a yes/no question, has more than one plausible answer, and considers relationships among concepts.

Abstract: An abstract is a concise summary of a research paper or article that provides a brief overview of the study’s main objectives, methods, results, and conclusions. It serves as a snapshot of the entire work, allowing readers to quickly understand the essential aspects without having to read the full document.

Literature Review: A literature review is a critical and comprehensive analysis of existing research and scholarly writings on a specific topic or subject. It involves reviewing, summarising, and synthesising relevant studies, theories, and findings to provide context, identify gaps, and establish the theoretical foundation for a new research study. The literature review helps researchers understand the current state of knowledge in their field and positions their own work within the broader academic discussion.

Variables: In a research study, a variable refers to any characteristic, attribute, or quantity that can be measured, observed, or controlled.

Independent Variable: The independent variable is the factor or condition in an experiment or study that is intentionally manipulated or changed by the researcher. It is used to observe its effect on the dependent variable. In cause-and-effect relationships, the independent variable is considered the potential cause that influences the study’s outcome.

Dependent Variable: The dependent variable is the outcome or response being measured or observed in an experiment or study. It is the variable that researchers are interested in understanding or explaining, and its changes are thought to be influenced by the independent variable. The dependent variable is the effect or result that researchers analyse to draw conclusions about the impact of the independent variable.

Demographic Variables: Demographic variables are characteristics of a population or sample that provide information about its composition, such as age, gender, ethnicity, income, education, and marital status. These variables help researchers categorise and understand the individuals or groups being studied, allowing for the analysis of patterns and trends within different segments of the population.

Extraneous Variables: Extraneous variables are factors or conditions that are not the main focus of a research study but can affect the study’s outcome if not controlled for. They are external influences that may unintentionally influence the relationship between the independent and dependent variables, potentially leading to misleading or inaccurate results.

Statistical significance: A statistical concept that assists researchers in figuring out if a seen outcome is a genuine effect or if it might have happened randomly.

Null hypothesis: Posits no significant difference or effect between variables under investigation, serving as a baseline for comparison in hypothesis testing.

P Value: A statistical measure used in hypothesis testing to determine the likelihood of obtaining results as extreme as, or more extreme than, the observed data, assuming that the null hypothesis is true. It helps researchers assess the strength of evidence against the null hypothesis and make informed decisions about its rejection or acceptance. A lower p value indicates stronger evidence against the null hypothesis, suggesting that the observed results are less likely to occur by chance. Typically, a p value threshold (often 0.05 or 0.01) is used to determine whether the results are statistically significant, leading to the acceptance or rejection of the null hypothesis.

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Navigating Communication Research: A Practical Guide for Media Practitioners Copyright © 2025 by Amanda Williams and Emma Duke is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, except where otherwise noted.