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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