Content from Welcome to Pre-seeds (Research 101)!


Last updated on 2025-06-25 | Edit this page

Overview

Questions

  • What is this course about?
  • Who is it for?
  • How can I get the most out of it?

Objectives

  • Get oriented with the course’s tone and approach.
  • Understand who this course is designed for.
  • Feel excited and supported as you begin your learning journey.

Introduction


Welcome! 🎉

We’re so glad you’re here. This course—Pre-seeds (Research 101)—is not your typical introduction to research. It’s built for you: the curious, the hopeful, the hands-on learners who may not always see themselves in traditional research spaces but know they have something to contribute.

Whether you’re stepping into research for the first time or circling back with fresh eyes, you’re in the right place.

This isn’t about throwing jargon at you or expecting you to “catch up.” We’ll take things step by step, building confidence and skills in a way that’s practical, inclusive, and deeply human. Expect check-ins, relatable examples, and thoughtful pauses—not just facts.

We believe research is for everyone, and that includes you!

Challenge 1:

Who is this course designed for?

  1. Only people with a science degree

  2. Researchers at elite institutions

  3. Anyone curious about research, no matter their background

  4. People who already know everything

Answer: C

This course was built for anyone who’s curious about research, especially folks who may not come from traditional academic paths.

Challenge 2:

What kind of experience can you expect from this course?

  1. Lots of memorisation and final exams

  2. Strict grading and formal lectures

  3. A practical, inclusive, step-by-step journey

  4. Pure chaos, honestly

Answer: C

We’re keeping things practical and human—this is a supportive space to explore and grow.

Challenge 3:

Which of the following might already make you a budding researcher?

  1. Asking good questions

  2. Looking for patterns

  3. Being curious about the world

  4. All of the above

Answer: D

Yep—if you’ve done any of these, you’ve already started thinking like a researcher!

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You don’t need to be an expert

This course is designed assuming you have little to no formal research training. If you’ve ever asked good questions, looked for patterns, or been curious about the world—congrats, you already have the beginnings of a researcher’s mind.

Just a heads-up


Throughout this course, you’ll find short challenges, real-world scenarios, and opportunities to apply what you’ve learned. There’s no grading—just growth.

Each module builds on the one before it, but you can always circle back or skip ahead if something calls to you.

So take a breath, settle in, and get ready to stretch your brain gently.

You belong here. đź’›

Key Points

  • This course is beginner-friendly and community-rooted.
  • You don’t need a research background to get started.
  • Learning is nonlinear, and that’s okay.

Content from Episode 1.1: Introduction to research: What is research?


Last updated on 2025-06-17 | Edit this page

Overview

Questions

  1. What makes research different from everyday opinions?
  2. What does it mean for research to be “replicable”?
  3. Why is critical thinking important in research?

Objectives

Learners will be able to:

  • Define research in their own words, and how it stands apart from other ways of knowing (e.g. opinion, belief, or anecdote)
  • Identify the defining features (characteristics) of credible research.
  • List reasons for conducting research, and the importance of research in various contexts.
  • Identify real-world examples of research in action.

Think Like a Researcher


Imagine you’re sitting in a university lecture hall. Every time you glance around, more students seem to be glued to their phones. Some are scrolling through social media, others texting, and a few seem genuinely disengaged from the class.

You start to wonder: Why is this happening? Is it boredom, habit, or maybe something deeper about how students are taught today?

Now pause—what if you wanted to understand this behavior, not just guess at it? How would you systematically investigate this problem in a way that produces useful insights?

Hold on to that question. By the end of this lesson, you’ll know how a researcher would approach it.

A Wise Researcher Once Said…


“Research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. It involves inductive and deductive methods.” — Earl Robert Babbie, American Sociologist

Let’s break that down. “Systematic inquiry” means we don’t just ask questions and hope for the best. We follow a method, apply logic, and rely on evidence.

What Is Research, Really?


Research is the engine behind most of the advancements we see in medicine, technology, social policy, and even the arts.

At its core, research is a structured way of asking and answering questions about the world. It’s how we move from guessing to knowing.

Unlike casual observations or personal beliefs, research depends on: - Gathering data - Organising and analysing it - Interpreting it logically - Drawing conclusions that others can test or build upon

Key Characteristics of Research


Let’s look at what separates research from, say, a viral tweet or a hunch you have about something:

  1. Systematic Approach Research follows a clear plan or methodology. You don’t jump from question to conclusion—you walk through the steps carefully.

  2. Objective and Unbiased Good research minimises personal opinions or preferences. It focuses on what the data says, not what we want it to say.

  3. Empirical Evidence It uses real-world observations—things we can see, measure, or document—not just ideas or feelings.

  4. Replicability Someone else, following the same steps, should be able to reproduce your results (or at least understand how you got them).

  5. Critical Thinking Researchers must ask tough questions of their own work and be open to alternative interpretations.

Why Do We Do Research?


Not all research is done for the same reason. Depending on your goal, you might approach the same topic very differently.

Purpose Goal
Exploratory To investigate new or poorly understood phenomena.
Descriptive To paint a detailed picture of a population or situation.
Explanatory To figure out why something happens—cause and effect.
Applied To solve a practical, real-world problem.

Think of these like different lenses you can look through—each one helps you focus on a particular aspect of your research question.

Why Does Research Matter?


Research isn’t just for scientists or academics. It affects all of us.

  • In healthcare: It helps us understand disease and develop treatments.
  • In education: It helps improve how we teach and learn.
  • In policy-making: It ensures decisions are backed by facts, not just opinions.
  • In everyday life: It sharpens our critical thinking and helps us avoid misinformation.

Simply put: without research, we’re just guessing.

Illustrative Example: When Clean Water Becomes a Crisis


Let’s say a rural community starts experiencing a rise in cases of waterborne diseases. Some people think the cause is the local river, others blame poor hygiene, and some say it’s just a coincidence.

What would a researcher do?

  1. Start by clearly defining the problem: When and where are cases happening?

  2. Collect data: Water samples, health records, sanitation practices.

  3. Analyse patterns: Are certain water sources contaminated? Are specific villages more affected?

  4. Draw conclusions and make recommendations: Maybe the source is an open well near a farm using chemical fertilizers.

This kind of systematic, evidence-based process transforms a community crisis into an opportunity for real, impactful change.

Wrap-Up: Research as a Way of Seeing the World


To do research is to say: “I want to understand, not assume.”

Whether you’re investigating disease outbreaks, classroom dynamics, or the impact of climate change, the tools of research help you navigate uncertainty with clarity.

Test Your Knowledge!


Challenge 1:

A key characteristic of research is that it follows a systematic and structured process. (True/False)

True.

Challenge 2:

All research must include an experiment in order to be valid. (True/False)

False.

Challenge 3:

Which of the following is NOT a reason for conducting research?

  1. To satisfy personal curiosity.
  2. To improve decision-making.
  3. To confirm pre-existing biases.
  4. To solve real-world problems.

Answer: C.

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Callout

đź’ˇ Not all knowledge is created equal.

What sets research apart from everyday opinions or anecdotes is its structured, objective, and evidence-based approach. If you can’t explain how you arrived at a conclusion, it probably isn’t research.

Key Points

  • Research is a systematic, logical, and evidence-based process for asking and answering questions about the world.
  • It differs from opinion or belief because it relies on data, critical thinking, and clear methodology.
  • Good research is replicable, objective, and empirical—others should be able to follow your steps and understand your conclusions.
  • Research serves various purposes: it can explore new topics, describe conditions, explain relationships, or solve real-world problems.

Content from Episode 1.2: The research process: Steps involved in conducting research


Last updated on 2025-06-20 | Edit this page

Overview

Questions

  • What is the research process, and why is it important?

  • What are the key phases of the research process?

  • How do the phases of the research process connect to each other?

  • Why is the research process iterative rather than strictly linear?

Objectives

Learners will be able to:

  • Outline the major phases of the research process

  • Match research activities to their corresponding phases.

  • Describe the iterative nature of research

  • Develop a conceptual foundation for the rest of the course

A Wise Researcher Once Said…


“Experienced researchers loop back and forth, move forward a step or two before going back in order to move ahead again, change directions, all the while anticipating stages not yet begun. And no matter how carefully you plan, research follows a crooked path, taking unexpected turns, sometimes up blind alleys, even looping back on itself.” — Wayne C. Booth (The Craft of Research)

What is the Research Process?


The research process is a systematic journey of asking questions, gathering evidence, analysing information, and sharing insights. Whether you’re investigating a public health challenge or evaluating the impact of a new product, or even assessing how frequently you drink water, the research process provides a structured path to ensure that your conclusions are credible, relevant, and reproducible. But don’t be fooled by neat diagrams that suggest a rigid step-by-step path. In practice, the research process is more like a loop than a ladder. Ideas evolve, questions sharpen, methods shift, and results can take us back to the drawing board. And that’s not a failure—that’s research done right!.

Why Learn the Research Process?


Imagine starting a long journey without a map or GPS. You might wander around and eventually find your way—but it’ll take longer, cost more, and you might end up somewhere you didn’t intend.

The research process is your map. It helps you:

  • Stay organised
  • Ask sharper questions
  • Design stronger studies
  • Avoid common pitfalls
  • Work ethically and transparently

It also builds your credibility as a researcher, whether you’re publishing in a journal, advising decision-makers, or giving yourself a pat on the back for staying hydrated.

An Overview of the Key Stages


We’ll cover each of these in detail in later modules of the course, but for now, here’s the big picture:

An infographic titled "The Research Process" showing 10 stages in a flowchart format. The stages are: 1) Problem Identification – What do I want to know?, 2) Literature Review – What’s already known?, 3) Objectives/Hypothesis – What do I predict?, 4) Research Design – How will I find out?, 5) Data Collection – Go get the facts!, 6) Data Analysis – What do the numbers say?, 7) Result Interpretation – What does it mean?, 8) Conclusion – So what?, 9) Share – Share the story, 10) Evaluation – What worked? What next? Each stage is accompanied by an icon and arranged left to right as a horizontal arrow.
An infographic summarising the research process.

Aisha, a market woman and community volunteer in a rural town, begins to notice that many children in her area frequently miss school due to malaria. Concerned about the possible link between environmental factors and malaria cases, she decides to investigate whether improper waste disposal and stagnant water around homes contribute to the high incidence of malaria among school-aged children.

Identifying a Problem or Question

Define and articulate the research question or problem that you want to investigate. What issue do you want to explore? This step often emerges from curiosity, observations, literature reviews, or real-world challenges.

  • Aisha defines her research problem: “Does poor environmental sanitation contribute to the frequency of malaria infections among school-aged children in her community?” Her goal is to uncover patterns that could inform local health actions.

Reviewing the Literature

Conduct a thorough review of existing literature to understand what has already been studied and published on your topic. What have others already discovered? What gaps remain? Reviewing existing research ensures you’re building on a solid foundation and not reinventing the wheel.

  • She asks a local teacher to help her access some online articles and health brochures. From these, she learns that malaria is linked to stagnant water, uncovered containers, and poor drainage. She also speaks with a health worker to understand how similar studies have been done elsewhere.

Formulating Objectives or Hypotheses

Develop a clear and testable hypothesis or hypotheses based on your research question and literature review. These are your study’s compass. Objectives guide the focus; hypotheses offer testable predictions.

  • Aisha’s hypothesises: “Children living in households with poor environmental sanitation are more likely to suffer repeated episodes of malaria than those in cleaner environments.” This simple, clear hypothesis helps her structure her inquiry.

Choosing a Research Design

Determine the research design and methodology, including selecting participants (sampling), data collection methods (e.g., surveys, experiments), and procedures. Will you conduct experiments, surveys, case studies, or secondary data analysis? This step aligns your tools with your goals.

  • She chooses a simple observational survey. She plans to assess environmental conditions around households and collect information on malaria history from parents of school-aged children. She creates a basic checklist with help from a local nurse, including signs of poor sanitation like stagnant water, open drains, and exposed refuse.

Data Collection

Time to gather information! Collect empirical data based on your chosen methodology. This could be through interviews, questionnaires, sensors, or even scraping online data. How you collect data must be ethical, accurate, and purposeful.

  • Over two weeks, Aisha visits 50 homes. She observes the environment and asks parents how often their children have had malaria in the past 6 months. She records her findings using her notebook and a checklist, with permission from participants.

Data Analysis

Use appropriate statistical or qualitative analysis techniques to analyse the collected data and test your hypotheses. This is where your raw data becomes meaningful. You’ll look for patterns, test hypotheses, and answer your research questions.

  • With help from her nephew, who is good with Excel, Aisha organises the data. They create simple charts comparing the number of malaria episodes with the sanitation scores. The results suggest that children in homes with poor sanitation had significantly more malaria episodes.

Interpreting Results

Interpret the results of your data analysis in the context of your research question and hypotheses. Consider implications, limitations, and future research directions. What do your findings actually mean? Are they consistent with previous research? Do they raise new questions?

  • Aisha interprets the findings: in her community, poor sanitation practices appear strongly linked to repeated malaria infections. She notes that many families lack access to covered bins, drainage systems, or insecticide-treated nets.

Draw Conclusions

Draw conclusions based on your findings and discuss how they contribute to the field of study or address the research problem.

  • She concludes that community-wide sanitation improvements could reduce malaria infections. She emphasises the need for proper waste disposal, draining of stagnant water, and health education on malaria prevention.

Sharing Findings

Your research isn’t complete until it’s communicated. This could be through papers, presentations, infographics, or conversations with stakeholders.

  • Aisha presents her findings at the monthly community meeting. She uses simple language and posters to explain the link between the environment and health. The town chief and local health workers are impressed and agree to help with a community clean-up drive.

Evaluate and Reflect

Reflect on the entire research process, evaluate its strengths and weaknesses, and consider areas for improvement or further exploration.

  • Aisha reflects that although she is not a professional researcher, her local knowledge and passion made the study meaningful. She notes that involving others from the beginning would have improved data accuracy and plans to train some youth to help with future community surveys.

The Process is Connected, Not Compartmentalised


Each stage flows into the next, and each decision you make affects those that follow. For example:

  • Poorly defined objectives can lead to unclear analysis.

  • Weak data collection methods can ruin great research designs.

That’s why this course doesn’t just teach techniques. We’ll emphasise how everything connects—because research isn’t just about what you do, but why and how you do it.

Research is Iterative (And That’s a Good Thing!)


You might design a perfect study on paper… only to find that your participants misunderstood your survey, or your data has gaps, or your findings raise a brand-new (and even more exciting) question.

That’s not a problem—it’s progress.

Research often involves:

  • Revisiting your question after early data collection

  • Refining your analysis plan mid-study

  • Updating your literature review when new studies emerge

In short: you don’t have to get it all right on the first try. But you do need a process that helps you notice when something needs to change—and gives you the tools to adjust.

Reflection


Think on a real-world problem that interests you. Which of the 10 research stages do you think would be the most challenging for you, and why?

What’s Next?


In the rest of the course, we’ll take a closer look at each of the stages you’ve just seen. And for the rest of this introductory module, you’ll learn:

  • The various types of Research and their applications

  • The strengths and limitations of each type

But for now, remember this: The research process is your ally, not your obstacle. It’s flexible, responsive, and deeply logical—once you understand how it works. Let’s explore it together.

Test Your Knowledge!


Challenge 1:

A researcher begins with a well-defined problem and conducts a literature review. During the review, they realise their initial research question has already been thoroughly studied. What should the researcher do next?

  • A. Skip to the data collection phase
  • B. Abandon the research entirely
  • C. Refine the research problem and continue
  • D. Go ahead with the original question anyway

Challenge 2:

Which of the following best reflects an activity in the “Design the Research” phase?

  • A. Searching for articles in a database
  • B. Choosing a sample size and deciding on survey instruments
  • C. Comparing your findings to those of previous studies
  • D. Writing the introduction of your research report

Challenge 3:

You are analysing data from interviews and discover a new theme that you hadn’t anticipated in your original hypothesis. What is the most appropriate next step?

  • A. Ignore the theme to stick to your hypothesis
  • B. Revise your research framework to include the new theme
  • C. Change your research design retroactively
  • D. Restart the research process from the beginning

Challenge 4:

A student decides to examine the effects of social media use on sleep patterns among university students. Which phase of the research process is the student currently in?

  • A. Formulating a hypothesis
  • B. Communicating findings
  • C. Identifying the research problem
  • D. Analysing data

Challenge 5:

A researcher presents findings at a public health conference, receives critical feedback, and decides to re-analyse their data using a different method. This illustrates:

  • A. A failure to conduct proper data analysis
  • B. The final phase of the research process
  • C. The iterative nature of research
  • D. Poor planning in the research design phase

Challenge 6:

Which of the following best describes the primary goal of the “Evaluate and Reflect” stage in research?

  • A. To formulate a hypothesis for the next study
  • B. To interpret statistical results
  • C. To identify strengths, weaknesses, and opportunities for improvement
  • D. To compare your results with those of others

Challenge 7:

The research process is always linear and should not be revisited once a phase is complete. (True/False)

False

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Content from Episode 1.3: How is Research Classified?


Last updated on 2025-06-20 | Edit this page

Overview

Questions

  1. Why do researchers use different classification systems to describe their studies?
  2. Can a single study belong to more than one research category?

Objectives

Learners will be able to:

  • List at least four common criteria used to classify research (e.g. purpose, methodology, design, timeframe).
  • Explain how each criterion influences study design and interpretation.
  • Match a brief study description to two appropriate classification labels.

Why Classify Research at All?


Imagine you and your classmates are each investigating students’ phone use during lectures.
One of you runs an experiment, another conducts interviews, and a third mines university log-data.
Even though you share a topic, you are not doing the same kind of research.

Giving studies the right labels helps us:

  • choose methods that fit our goals,
  • communicate findings precisely, and
  • compare work across disciplines.

In this episode, we step back to see the whole classification map before zooming in on specific types in later lessons.


The Big Picture: Common Ways to Classify Research


Classification Criterion Typical Labels (examples) Key Question Answered
Purpose Basic / Applied Why is the study being done?
Methodology Quantitative / Qualitative / Mixed What kind of data will be collected?
Research Design Descriptive / Correlational / Experimental How will the data be gathered and analysed?
Goal (Depth of Study) Exploratory / Descriptive / Explanatory / Evaluative To what end will the findings be used?
Focus Theoretical / Empirical Does the work build concepts or test them in the real world?
Timeframe Cross-sectional / Longitudinal When and how long will observations occur?
Data Source Primary / Secondary Are you collecting new data or analysing existing material?

Note: A single project can legitimately wear several labels.
For instance, a longitudinal applied mixed-methods evaluative study is perfectly possible.


A Closer Look at Our Categories


1. Purpose

  • Basic research asks fundamental “how or why” questions (e.g. How does attention work?).
  • Applied research seeks direct solutions (e.g. Will locking phone pouches improve grades?).

2. Methodology

  • Quantitative: counts phone glances per lecture.
  • Qualitative: interviews students about distraction.
  • Mixed: does both to get numbers and narratives.

3. Design

  • Descriptive: records what happens.
  • Correlational: checks if phone use relates to low marks.
  • Experimental: randomly assigns half the class to “no-phone” rules.

(We will unpack each design in Episodes 1.4 and 1.5.)

4. Goal

  • Exploratory work might map new distraction patterns.
  • Explanatory work tests whether boredom causes phone use.

5. Focus

  • A theoretical paper could model digital distraction behaviour;
  • while an empirical study would test that model in real lectures.

6. Timeframe

  • Cross-sectional: a one-off survey this semester.
  • Longitudinal: tracking the same cohort for four years.

7. Data Source

  • Primary: your own classroom observations.
  • Secondary: institutional attendance records from past years.

Test Your Knowledge!


Challenge 1

A research team videotapes every lecture of a single course for one term and counts phone-checking events each week.
Which two classification labels (from different criteria) fit best?

Possible answer: Applied (purpose) and Longitudinal (timeframe).
Another reasonable combination is Quantitative and Descriptive.

Challenge 2

True | False: A study can never be both basic and applied.

False. A project can develop basic theory in its early phase and apply that knowledge in a later phase—or run both threads in parallel.

Key Points

  • Research can be classified by purpose, methodology, design, goal, focus, timeframe, and data source.
  • These labels guide methodological choices and clarify how findings should be interpreted.
  • Most real studies blend several categories; classifications are tools, not rigid boxes.
  • Recognising the map of research types prepares you to plan and communicate your own projects.

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Content from Episode 1.4: Types of Research I: Basic, Applied; Quantitative, Qualitative


Last updated on 2025-06-17 | Edit this page

Overview

Questions

  1. What is the difference between basic and applied research?
  2. When would you use qualitative instead of quantitative research?
  3. Can a study be both qualitative and quantitative?
  4. What are descriptive and experimental research, and when are they used?
  5. How do different research types affect the kind of data you collect?

Objectives

Learners will be able to:

  • Distinguish between basic and applied research.
  • Compare and contrast quantitative, qualitative, descriptive, and experimental research.
  • Identify when and why each type is used.
  • Connect each research type to real-world examples and questions.

Think Like a Researcher


Let’s go back to our earlier curiosity:
Why are so many students distracted by their phones during lectures?

Now imagine five different researchers trying to answer this question, each with their own method and mindset:

  • One carefully observes students and documents their behavior.
  • Another hands out a questionnaire to hundreds of students.
  • A third digs into journal articles to find trends across universities.
  • Another conducts interviews to understand students’ perspectives.
  • And yet another runs an experiment to see if a new teaching method reduces phone use.

Are all of these research? Yes.
Are they all the same type of research? Not quite.

This episode explores several popular pathways of research, each tailored to a particular kind of question, context, or goal. While not an exhaustive list, these are among the most commonly used types. You’ll learn how different kinds of research give us different kinds of answers.

How do we categorise research?


There’s more than one way to slice the research pie. But most research falls into one or more of the broad categories below:

1. Basic vs. Applied Research

Basic (or Pure) Research

This is aimed at expanding our general knowledge, without necessarily needing immediate application. That is, we don’t intend to solve a problem today.

Instead, basic research asks: How does the world work?

So, it is common in theoretical disciplines or foundational sciences.

  • Example: Studying how memory works in the brain, even if no product or intervention is being developed.

Applied Research

Unlike basic research, this is focused on solving a specific, real-world problem.

Applied research asks: How can we use knowledge to improve something?

It is common in public health, education, engineering, and business.

  • Example: Investigating how mobile phone use during lectures affects exam performance and then designing strategies to reduce it.

These two types, they often work together. Basic research builds the foundation, applied research builds the bridge to real-life solutions.

2. Quantitative vs. Qualitative Research

Quantitative Research

This involves numbers, statistics, and measurable variables.

Good for answering: How much? How many? How often? Is there a correlation?

(Task: Define correlation in a call out)

This type of research uses tools like surveys, experiments, statistical analysis.

  • Example: Measuring how many students use phones during lectures, how long they spend on them, and whether this correlates with their grades.

Qualitative Research

This focuses on experiences, meanings, stories, and context.

Good for answering: Why? How? What was the experience like?

Qualitative research tools include interviews, focus groups, observations, and content analysis.

  • Example: Interviewing students to understand why they check their phones, what they feel during lectures, and what might help them focus more.

3. Descriptive vs. Experimental Research

Descriptive Research

This is about observing, recording, and describing a phenomenon without manipulating any variables. It answers: What is happening? Who is involved? How widespread is it?

Descriptive research helps to build a picture of a situation as it naturally occurs. - Example: Surveying how many students report being distracted by phones and tracking differences across age groups or courses.

Experimental Research

This involves actively manipulating one variable to observe its effect on another. It answers: Does this cause that? What happens if we intervene? Experimental research is key when you want to establish cause and effect.

  • Example: Introducing a no-phone policy in some classes and comparing exam scores with classes that kept phones.

Illustrative example


Imagine you want to study vaccine hesitancy in your community:

  • Quantitative: How many people are hesitant? Which demographics?
  • Qualitative: Why are they hesitant? What fears or beliefs do they have?
  • Descriptive: What are the most common concerns expressed in public forums or media?
  • Experimental: What happens when people are shown targeted educational videos — does their willingness to vaccinate increase?

All offer important insights. Some give you patterns, others give you meaning or causal relationships.

Test Your Knowledge!


Challenge 1:

Which type of research is most likely to involve large data sets and statistical analysis?

  1. Applied
  2. Basic
  3. Quantitative
  4. Qualitative

Answer: c) Quantitative

Challenge 2:

True or False:
Applied research has no value unless it’s immediately applied to a problem, policy or practice.

False. Applied research still builds knowledge, even if implementation is delayed.

Key Points

  • Basic research builds theory; applied research solves problems.
  • Quantitative research answers “how much” with numbers.
  • Qualitative research answers “why” with stories and context.
  • Mixed methods combine the strengths of both.
  • Descriptive research tells you what’s happening without changing anything.
  • Experimental research tests cause and effect by manipulating variables.

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đź’ˇ Note: Some research combines both approaches. This is called Mixed Methods Research.

Content from Episode 1.5: Strengths, Limitations, and Applications of Research Types


Last updated on 2025-06-17 | Edit this page

Overview

Questions

  1. What are the strengths and limitations of the different types of research?
  2. How can understanding these differences guide the design of better studies?
  3. In what ways are these research types applied in real-world contexts?

Objectives

Learners will be able to:

  • Identify at least two strengths and limitations for each of the types of research.
  • Match each type of research to a practical example or disciplinary use case.
  • Decide which research type(s) may be most appropriate for a given research question or real-world scenario.

Think Like a Researcher


Imagine your university is considering launching a mental health app for students. You’re part of the team evaluating its impact. What’s the best way to approach the task?

Would you: - Measure students’ stress levels before and after using the app? - Interview students to understand how they feel about using it? - Compare the app to others in use at different schools? - Or do a little bit of everything?

The way you choose to investigate the problem depends on the kind of research you conduct—and each type brings its own strengths and tradeoffs. In this lesson, we’ll explore those strengths, limitations, and the contexts where each approach thrives.

A Quick Recap


In the previous episode, we introduced four common types of research, often grouped by purpose:

Type Goal
Baic Expand fundamental knowledge without immediate use
Applied Address real-world problems directly
Descriptive Document or quantify what is happening
Experimental Test cause-and-effect relationships
Qualitative Understand experiences, meanings, context
Quantitative Measure variables using numerical data

These types can work independently or in combination, depending on the research question.

Let’s now take a deeper look at each research type and how it plays out in practice.

Basic Research


Used when: You want to understand how things work at a fundamental level.

Strengths

  • Builds foundational knowledge and theories.
  • Often leads to future innovation and discovery.

Limitations

  • May not have immediate application.
  • Hard to justify in applied or results-driven environments.
  • Results tend to be tentative and may not lead to actionable conclusions on their own.

Real-World Applications

  • Studying how memory is encoded in the brain.
  • Investigating the basic principles of quantum computing.

Common Methods: Literature reviews, theoretical modeling, laboratory experiments.


Applied Research


Used when: The goal is to solve a specific, practical problem.

Strengths

  • Results are actionable and directly relevant to practice or policy.
  • Often interdisciplinary, integrating knowledge from different fields.
  • Supports innovation and impact.

Limitations

  • May be constrained by political, commercial, or time pressures.
  • Can prioritize short-term fixes over long-term understanding.
  • Results may not always be published or widely disseminated.

Real-World Applications

  • A hospital testing a new nurse scheduling algorithm to reduce staff burnout.
  • A city evaluating traffic sensors to improve road safety.

Common Methods: Case studies, evaluations, needs assessments, feasibility studies.


Descriptive Research


Used when: You want to document or quantify what is currently happening.

Strengths

  • Helps build a foundational understanding of populations or phenomena.
  • Supports policy-making and planning with concrete data.
  • Often large-scale and generalizable.

Limitations

  • Does not explore causes or explanations.
  • Can be misleading if poorly designed or biased in data collection.

Real-World Applications

  • A national census on employment trends across industries.
  • A school district tracking student attendance and engagement.

Common Methods: Observational studies, cross-sectional surveys, routine data audits.


Experimental (Causal) Research


Used when: You want to test cause-and-effect relationships by manipulating variables.

Strengths

  • Provides strong evidence for causality
  • Often highly systematic and replicable

Limitations

  • Can be complex and time-intensive.
  • May require ethical safeguards, especially in experiments.
  • Difficult to fully control variables in real-life settings.

Real-World Applications

  • A clinical trial testing whether a new vaccine reduces infection rates.
  • A randomized controlled study on whether gamified lessons improve student retention.

Common Methods: Experiments, longitudinal studies, regression modeling.


Quantitative Research


Used when: You want to measure variables and test hypotheses using numbers.

Strengths

  • Enables statistical analysis and generalization.
  • Suits large-scale studies and trend analysis

Limitations

  • May overlook context or nuance.
  • Can miss “why” behind the numbers

Real-World Applications

  • Measuring the number of app logins and correlating with mood scores.
  • Calculating percentage change in academic performance

Common Methods: Surveys, experiments, correlational studies


Qualitative Research


Used when: You want to understand how people make sense of their experiences.

Strengths

  • Offers rich, contextual, in-depth insights.
  • Flexible and adaptive to new findings.

Limitations

  • Findings are harder to generalize.
  • Can be time-intensive to collect and analyze

Real-World Applications

  • Interviewing students about mental health stigma.
  • Analyzing social media posts related to stress

Common Methods: Interviews, focus groups, ethnography, content analysis


When One Type Isn’t Enough


In the real world, many studies span multiple research types. Consider the case of the university’s mental health app:

  • Basic: Understanding psychological mechanisms behind stress
  • Applied: Designing and implementing the app
  • Descriptive: Tracking usage rates and stress reports
  • Experimental: Testing impact on mental health through a controlled study
  • Quantitative: Measuring shifts in mood using survey scales
  • Qualitative: Interviewing users about their experiences

This is where mixed methods come in—combining qualitative depth with quantitative breadth for a fuller picture.


Cross-Disciplinary Lens


Different academic and professional fields tend to favor different types of research based on their goals:

Discipline Typical Research Type Sample Topic
Public Health Applied, Qualitative, Descriptive Are health interventions reaching target populations?
Education Descriptive, Qualitative What do students report as barriers to learning?
Engineering Applied, Experimental How efficient is a new solar energy prototype?
Psychology Basic, Experimental, Quantitative What are the cognitive effects of screen time?
Sociology Qualitative How do young people define identity in online spaces?

Understanding the types of research favored in a field can help you collaborate more effectively, apply for grants, and interpret findings with nuance.

Test Your Knowledge!


Challenge: Match the Type

Scenario: A local government wants to understand whether its free school meal program improves student performance.

Which research types could apply?

  • Experimental: Randomly assign some schools to receive the meal program and others not to, then compare performance outcomes between the two groups.
  • Applied: Evaluate the effectiveness of the current program and offer policy recommendations on whether it should be expanded or revised.
  • Descriptive: Collect data on how many students are receiving meals.
  • Quantitative: Conduct interviews or focus groups with students, parents, and teachers to explore how the meal program affects learning, focus, and well-being.
  • Qualitative: Evaluate whether the program should be expanded based on findings.

Key Points

  • Each type of research—basic, applied, descriptive, experimental, qualitative, and quantitative—has unique strengths and limitations.
  • Complex problems benefit from mixed methods that draw on multiple types.
  • Being intentional about research type improves clarity, coherence, and usefulness of findings.
  • Different disciplines apply research types in different ways, tailored to their questions and practices.

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