Practical Research 2: Quantitative Research, Variables, and Research Gaps

Academic Context and Course Schedule

• Institution: Our Lady of Fatima University (Senior High School Department, Language Department).
• Course Title: Practical Research $2$
• Academic Period: Academic Year $2026-2027$, $1\text{st}$ Semester.
• Lesson 1 Focus: Types of Quantitative Research, Types of Variables, and Research Gap.

Weekly Academic Calendar (Weeks $1-9$)

• Week $1$ (July $13 - 18$): Subject Orientation, Groupings, Discussion of PR Files.
• Week $2$ (July $20 - 25$): Lesson $1$.
• Week $3$ (July $27 - \text{Aug } 1$): Written Activity.
• Week $4$ (Aug $3 - 8$): Lesson $2$.
• Week $5$ (Aug $10 - 15$): Consultation.
• Week $6$ (Aug $17 - 22$): Consultation.
• Week $7$ (Aug $24 - 29$): Consultation.
• Week $8$ (Aug $31 - \text{Sept } 5$): Title Defense Week.
• Week $9$ (Sept $7 - 12$): Exam Week.

Fundamental Concepts of Research

• Definition of Research: A systematic process of collecting, analyzing, and interpreting information-data in order to increase understanding of a phenomenon about which we are interested or concerned.
• Role: Research is considered an indispensable component of academic and industry practices.

Basic Terminology in Research

• Method: The categorization based on what data will be gathered. Examples include:
  • Historical
  • Descriptive
  • Experimental
• Technique: The specific way data will be gathered. Examples include:
  • Survey
  • Interview
  • Doodling
• Approach: How the data will be processed. Categories include:
  • Quantitative
  • Qualitative
  • Mixed

Understanding Quantitative Research

• Formal Definition: It is the systematic empirical investigation of an observed phenomena through the use of statistical, mathematical or computational methods (Given, $2008$).
• Primary Aim: To find out the relationship between one variable to another, specifically the independent variable (the cause) and the dependent variable (the effect).

Types of Quantitative Research

General Classification

• Experimental Research:
  • Establishes causality.
  • Often used when an intervention is being studied.
  • Involves the manipulation of variables.
• Non-Experimental Research:
  • Establishes the association or connection between variables.
  • Conducted without the manipulation of variables.

Specific Classifications of Non-Experimental Research

• Survey Research: The most common method used for quantitative study; can be in the form of a questionnaire or interview.
• Descriptive Research: A method used to describe the characteristics of a population or phenomenon being studied.
• Correlational Research: Focuses on the connection or relationship between variables.
• Comparative Research: Based on descriptive data; shows that a difference exists between groups but does not imply causation.

Sub-types of Survey Research

• Cross-Sectional Study: Collects data from a population or subset through observation, survey, or interview at a specific point in time.
• Longitudinal Study: Collects data through observation, survey, or interview of the same subjects over a period of time, which can last up to several years.

Sub-types of Experimental Research

• True Experimental:
  • The researcher has total control over the experiment (who, where, when, and how).
  • Involves an experimental group (receives intervention) and a control group (remains unmanipulated).
  • The two groups must have similar qualities.
  • Characterized by three key elements: Manipulation, Randomization, and Control.
• Quasi-Experimental:
  • Depends on how participants were recruited.
  • Participants are NOT randomly assigned.
  • Attempts to establish cause-and-effect relationships using criteria other than randomization.
  • If there is no randomization in the sampling procedure, the study automatically becomes quasi-experimental.

The Nature and Types of Variables

• Definition: Variables are anything that varies or takes on different values, typically numerical values.
• General Examples: Age, gender, height, hair color, health parameters (vital signs), and hobbies.

Major Types of Variables

• Independent Variable:
  • The variable being manipulated by the researcher.
  • It is stable and unaffected by other variables the researcher is trying to measure.
  • Considered "the cause."
• Dependent Variable:
  • The variable that assumes the change brought about by the other variable.
  • This is the variable being measured.
  • Considered "the effect."

Extraneous Variables

• Also referred to as the "unwanted variable."
• Known as confounding variables because their presence influences the outcome of the experiment in an undesirable way, adding error.
• They are factors related to the phenomenon under study but not specifically included in the research design.
• Examples: Weather, participant's motivation, emotional state, age, location, and cultural background.

Case Analysis Examples

• Scenario 1: "The Impact of Classroom Design on Student Learning"
  • Independent Variable: Classroom Design
  • Dependent Variable: Student Learning
• Scenario $2$: "Peer Monitoring and Its Effects on Student Retention"
  • Independent Variable: Peer Monitoring
  • Dependent Variable: Student Retention

The Research Gap

• Definition: A clear, unanswered question or problem in existing research. It is the "missing piece" that a study helps address.
• Identification Logic: Do not ask "What topic has not been studied?" Ask "What is missing, weak, outdated, inconsistent, or underexplored in existing research?"

Categories of Research Gaps

• Empirical Gap: Contradictory findings in existing data.
• Conceptual Gap: Missing variables in current frameworks.
• Methodological Gap: Weak or limited research methods used previously.
• Demographic Gap: Underrepresented populations in previous studies.
• Contextual Gap: Different contexts or industries that haven't been explored.
• Temporal Gap: Outdated studies that no longer reflect current situations.
• Practical Gap: Missing practical implementation of theories.
• Theoretical Gap: Weak theoretical foundations.
• Knowledge Gap: Limited knowledge available on the topic.

Specific Dimensions of Research Gaps

• Location: Most studies were done in other places, but the current setting may have a different situation.
  • Example: Studies in urban schools vs. rural schools.
• Respondents: Past studies focused on one group, but another group needs understanding.
  • Example: College students studied vs. Senior High School learners.
• Method: Past studies used one approach (e.g., surveys), but another approach (e.g., interviews) provides deeper insight.
• Time: Older studies may no longer reflect the current situation, especially with changes like online learning.

Writing and Filling the Research Gap

• Process:
  1. Look at recent studies; do not guess the gap.
  2. Write what studies already say (e.g., "Studies show that students use AI tools…").
  3. Identify what is missing (group, place, method, evidence age).
  4. Justify the gap: Ask "So what?" and explain why the missing part matters.
  5. Connect the gap to your own study to show how it fills the void.
• Example Comparison:
  • Known: AI tools are used in education.
  • Gap: Less is known about SHS students in schools with limited internet.
  • Action: This study examines their specific challenges.

Assessment Notice

• Students must prepare for a $40$-item quiz next meeting covering Lesson $1$: Types of Quantitative Research, Types of Variables, and Research Gap.