Practical Research 2 Review

Practical Research 2 Review

• Theoretical Framework: Provides the foundation and building blocks for a study. It strengthens the study.
• Conceptual Framework:
  • Guides the researcher by providing clear directions.
  • Shows the relationship and connections between variables in the study.
  • It is a diagram illustrating the expected findings.
• EXAMPLE (Peer Tutoring Study):
  • Problem Statement: The effect of peer tutoring on reading fluency of senior high school students.
  • Variables:
    • Independent Variable: Peer tutoring
    • Dependent Variable: Reading fluency
  • Conceptual Framework Diagram: Shows the relationship between peer tutoring and reading fluency as an independent and dependent variable.

Research Components

• Hypothesis: Predictions about the research findings.
• Review of Related Literature: A detailed examination of existing literature related to the research topic.
• Research Design: The overall strategy to implement the research study; incorporating all research components.

Types of Quantitative Research Designs

• Descriptive Research: Exploratory research used when little is known about the problem. Focuses on answering who, what, when, where, and how much. Objective is to observe and report on a phenomenon.
• Correlational Research: Aims to determine if variables increase or decrease together. It does not establish cause-and-effect. Focuses on association and prediction of variables.
• Ex Post Facto Research: Measures a cause from a pre-existing effect. The researcher has no control over variables in the study.
• Quasi-Experimental Research: Attempts to measure causal relationships. Groups are not randomly assigned (e.g., by age, education).
• Experimental Research: Uses the scientific method, including controlled environments and manipulation. Typically involves random assignment of subjects into treatment and control groups.

Sampling

• Population: All objects, elements, persons, and characteristics under study.
• Sample: A representative subset of the population used for research analysis.
• Sampling Techniques (Probability):
  • Simple Random Sampling: All members have an equal chance of selection.
  • Stratified Random Sampling: Population is divided into strata or groups before sample selection.
  • Cluster Sampling: Used in large-scale studies with geographical spread-out populations. Useful when direct sampling would be too difficult.
  • Systematic Sampling: Choose every nth member of the population.

Research Instruments

• Characteristics of a Good Instrument: Concise, sequential, valid, and easily tabulated.
• Common Scales: Likert Scale (used to rank statements).
• Types of Validity: Face validity, content validity, construct validity, concurrent validity (detailed review of existing literature related to thesis topic).
• Research Intervention Steps: Write background information, and describe differences and similarities between experimental/control groups; describe procedures; explain the basis of procedures.

Data Analysis

• Data: Pieces of information or facts.
• Techniques in Collecting Quantitative Data: Observation using senses or equipment, and Surveys (questionnaires or interviews).
• Data Analysis: Summarizes information to answer research questions. Statistical methods are used (e.g., descriptive statistics: frequency distribution, measures of central tendency, standard deviation).
• Types of Statistical Analysis:
  • Univariate analysis: Analysis of one variable.
  • Bivariate analysis: Analysis of two variables (e.g., independent and dependent variables).
  • Multivariate analysis: Analysis of multiple variables.