Practical Research 2 Lesson 1: Quantitative Research and Variables

Overview and Learning Objectives

Quantitative research is a critical methodology involving the collection and analysis of numerical data to identify patterns, relationships, and trends. This instructional material, part of the Senior High School curriculum at Philippine Christian University – Dasmarias City (S.Y. $2026-2027$), focus on Practical Research $2$ for Grade $12$. The primary goal is to provide students with the foundations to solve real-life problems through evidence-based decision-making and the proposal of feasible research topics aligned with their specific academic strands.

Learning Objectives

By the end of the lesson, students are expected to:

• Describe the characteristics, strengths, and weaknesses of quantitative research.
• Differentiate the various kinds of quantitative research: descriptive, correlational, quasi-experimental, and experimental.
• Illustrate the importance and application of quantitative research across different academic and professional fields.
• Differentiate types of variables and understand their specific uses in study designs.
• Propose a simple quantitative research topic aligned to a specific academic strand and justify its research type.
• Value the roles of collaboration and critical thinking in the selection of research topics.

Essential Questions

• How can quantitative research help address real-life problems in a chosen academic strand?
• What specific variables contribute to making a study effective?

Characteristics of Quantitative Research

Quantitative research is defined as a systematic methodology for gathering and analyzing numerical data. It is preferred in many scientific and social disciplines because it yields objective and reliable results that can be measured and generalized to larger populations.

• Foundational Priming Question: What makes research study ‘quantitative’ rather than qualitative?
• Core Components: Use of numerical data and rigorous statistical analysis.
• Key Attributes: The process must be objective, replicable, and generalizable.

Strengths

• Provides precise measurements.
• Facilitates hypothesis testing.
• Allows for the use of large sample sizes to represent populations.

Weaknesses

• May overlook specific contexts, personal feelings, or nuanced human experiences.
• Requires a high level of statistical knowledge for accurate data interpretation.

Kinds of Quantitative Research

Research designs are selected based on whether the goal is to describe a situation, examine relationships, or test for cause-and-effect.

• Descriptive Research: Describes characteristics or the current status of a subject. An example is studying the "Level of Stress Among Senior High School Students."
• Correlational Research: Examines relationships between two or more variables without identifying causation. An example is analyzing "Sleep Hours and $GPA$ of Grade $12$ Students."
• Quasi-Experimental Research: Tests cause-and-effect relationships but lacks the random assignment of participants. An example is investigating the "Effect of Online Modules on Test Scores."
• Experimental Research: Involves strict control and manipulation of variables, including random assignment, to determine impact. An example is measuring the "Impact of Different Study Techniques on Retention."

Importance of Quantitative Research Across Fields

Quantitative research converts everyday problems into measurable data, allowing for practical, evidence-based solutions in various domains:

• STEM (Science, Technology, Engineering, Mathematics): Example: Testing the effect of different fertilizers on the growth rate of plants to identify effective and sustainable farming methods.
• ABM (Accountancy, Business, and Management): Example: Analyzing how social media advertisements affect the buying behavior of teenagers to guide marketing strategies.
• HUMSS (Humanities and Social Sciences): Example: Surveying the level of political awareness among Senior High School students to improve civic education programs.
• ICT (Information and Communication Technology): Example: Measuring user response times to evaluate the usability of mobile applications for developing faster software.
• Home Economics (HE): Example: Studying the impact of proper nutrition on athletic performance to support health and wellness programs.
• Sports: Example: Studying the relationship between sleep duration and athletic performance among student-athletes to improve training and recovery protocols.

Research Variables

Variables are the measurable characteristics or factors that researchers observe and analyze. They are the foundation of any quantitative study.

Types and Roles in Study

• Independent Variable ($IV$): The variable that is manipulated or changed by the researcher. It serves as the Cause or Input. (Example: Study Hours changed to see an effect).
• Dependent Variable ($DV$): The variable that is measured or observed. It represents the Effect or Outcome. (Example: Academic Performance measured through $GPA$ or test scores).
• Control Variables: Factors that are held constant to avoid interference and ensure fairness in the study. (Examples: Age, Gender, School Schedule).
• Intervening/Mediating Variable: A variable that explains the ‘how’ or ‘why’ of the relationship between the $IV$ and the $DV$. (Example: Motivation Level, which explains why increased study hours lead to better $GPA$).

Example Scenario

In a study titled "Effect of Study Hours ($IV$) on Academic Performance ($DV$) among Grade $12$ Students," the researcher assumes that the input (hours spent studying) will result in a measurable change in the output (grades).

Learning Resources

• Barrot, J.S. ($2017$). Practical Research $2$. C&E Publishing.
• Mendoza, D.J. et al. ($2023$). PADAYON-Applied Research.
• Cabading, J.P.F., & Brawner, F.G. ($2022$). Practical Research $2$ (New ed., Reprinted $2024$). ISBN $978-621-04-2932-9$.
• Abante, M.V. et al. ($2024$). Advanced Research Methods.
• Orleans, A.V. ($2018$). Research in Daily Life $2$.

Supplemental Readings and Resources

• Creswell, J. W., & Creswell, J. D. ($2023$). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches ($6^{th}$ ed.). SAGE Publications.
• Field, A. ($2024$). Discovering Statistics Using IBM SPSS Statistics ($6^{th}$ ed.). SAGE Publications.
• Polit, D. F., & Beck, C. T. ($2021$). Nursing Research: Generating and Assessing Evidence for Nursing Practice ($11^{th}$ ed.). Wolters Kluwer.
• Khan Academy (n.d.). Statistics and probability: Variables and quantitative methods.
• TED-Ed ($2024$). The power of quantitative research [Video].

Administrative Details

• Prepared by: Ardin A. Susana, LPT. (Subject Teacher)
• Checked by: Justine Mar F. Mina, LPT. (Subject Lead Teacher, Research $12$)
• Approved by: Maria Beatriz B. Sico, MM. (Principal)

Disclaimer: This module is an exclusive property of Philippine Christian University-Dasmarias Senior High School. It is provided for free to enrolled students for academic use. Reproduction without official permission is strictly prohibited.