Reliability_Validity_Intervention_Data-Gathering

Lesson 1: Validity and Reliability

1.1 Concept of Validity

  • Definition: Validity pertains to how well a research instrument measures what it intends to measure.

  • Example: A questionnaire that incorrectly measures grammar rather than discourse management is not valid.

  • Importance: Ensures that results are accurately reflecting the intended measure.

1.2 Concept of Reliability

  • Definition: Reliability refers to the consistency of results when a research instrument is administered multiple times.

  • Example: If the same test yields the same scores upon repeated administration, it is considered reliable.

  • Analogy: A reliable weighing scale gives consistent readings; being accurate to actual weight ensures validity.

1.3 Types of Validity

  • Face Validity: Subjective assessment of whether the instrument appears to measure what it intends to measure.

  • Content Validity: Instrument meets study objectives; involves expert assessment for relevant items to be measured.

  • Construct Validity: Alignment of the measurement method with the concept being measured; requires careful parameter development.

  • Concurrent Validity: Comparing new instrument results with existing validated instruments to check correlation.

1.4 Establishing Reliability

  • Homogeneity/Internal Consistency: Measures how well all aspects of the study are captured. High consistency indicates good reliability.

    • Techniques: Split-Half reliability, Kuder-Richardson, Cronbach's alpha.

  • Stability: Reflects repeatability; instruments should yield similar scores over time.

    • Techniques: Test-Retest and Parallel-form reliability.

  • Equivalence: Consistency among different users or forms of the instrument.

    • Example: Randomly splitting questions to maintain similar means and variances in responses.

Lesson 2: Describing Intervention

2.1 Overview of Experimental Research Design

  • Definition: In experimental research, variables can be manipulated through interventions.

  • Purpose: To measure the effects of a treatment or intervention on a population.

2.2 Components of Describing Intervention

  1. Background Information: Explanation of the intervention’s origins, relevance, context, and duration.

  2. Differences and Similarities: Outline the expectations for experimental vs. control groups.

  3. Procedures: Detailed description of how the intervention will be implemented with the experimental group.

  4. Basis of Procedures: Justification for the choice of intervention whether derived from past research or theoretical frameworks.

2.3 Example of Research Intervention

  • Research Framework: Task-based language teaching aimed at enhancing oral competence among Automotive Service students.

  • Module Details: Based on variances in learning styles (kinesthetic) and structured by Ellis’s task-based framework with pre, during, and post tasks.

  • Implementation Timeline: Proposed for use in the second quarter of the academic year after pre-testing and concluded with post-testing.

Lesson 3: Planning Data Collection Procedure

3.1 Importance of Data Collection

  • Essential for testing hypotheses and gathering information-rich data.

  • Data should be reliable and valid for effective statistical analysis.

3.2 Phases of Data Collection

  1. Before Data Collection:

    • Adapt or construct the research instrument.

    • Identify necessary authorities for permission.

    • Determine sample size and select respondents.

    • Obtain consent from participants (or parents for minors).

    • Validate the research instrument through expert feedback; Pilot testing if needed.

  2. During Data Collection:

    • Administer the instrument or implement interventions.

    • Collect and record responses accurately.

  3. After Data Collection:

    • Summarize data in tabular format for clarity.

    • Analyze the collected data to evaluate hypotheses.