RDL

• Research design


  The overall strategy that a researcher uses to logically and coherently integrate the components of a study
• Types of research design

  • Descriptive
  • Correlational
  • Ex post facto
  • Quasi-experimental
  • Experimental
  • Prototyping
• Descriptive research design


  • Aims to observe and report on a phenomenon, manifestation of behavior or traits
• Correlational research design


  • Determines association among variables
• Ex post facto research design


  • Aims to infer a cause from the already existing effects
• Quasi-experimental research design


  • Aims to establish causal relationship with intervention
• Experimental research design


  • Aims to establish causal relationship with intervention
• Prototyping research design


  • Improve planning and execution of creative designs
• Sampling


  The process of selecting individuals, units, or groups to be analyzed during the conduct of the study
• Generalizability


  The extent your findings can be applied in other contexts
• Determining the sample size

  • Heuristic (rule of thumb)
  • Literature review (check sample size of similar studies)
  • Formulas (Cochran's formula, NEA's formula)
  • Power analysis (most precise)
• Statistical power

  Probability that there is, indeed, a relationship between the independent and dependent variable (80%)
• Effect size


  The degree of the difference between the control and treatment groups (t-test= 0.2, 0.5, 0.8; r= 0.1, 0.3, 0.5)
• Probability sampling methods

  • Simple random
  • Stratified random
  • Cluster
  • Systematic
  • Interval

  
• Simple random sampling


  All members of the population have an equal chance of being selected (e.g. Fish Bowl Technique)
• Stratified random sampling


  Population is divided into subgroups or strata
• Cluster sampling


  Grouping the population into clusters
• Systematic sampling


  Participants are selected based on their order on a list or predetermined interval
• Interval sampling


  Divide the population size by the sample size
• Developing a research instrument

  • Adopt a research instrument
  • Modify an existing research instrument
  • Create your own research instrument
• Instrument validity


  • Face validity
  • Content validity
  • Construct validity
  • Criterion validity
  • Concurrent validity
  • Predictive validity
• Face validity


  Does not ensure that the instrument has actual validity
• Content validity


  Covers specific elements of the variable to be measured
• Construct validity


  The instrument is able to detect what should exist theoretically
• Criterion validity


  Evaluated through statistical methods
• Concurrent validity


  Predict the results similar to a test validated in the past
• Predictive validity


  Produces results similar to those of other instruments that will be employed in the future
• Instrument reliability


  • Test-retest
  • Equivalent forms
  • Internal consistency
  • Inter rater
• Test-retest reliability


  Administering an instrument twice to the same group
• Equivalent forms reliability


  Administering two identical tests in all aspects except for the actual wording of items
• Internal consistency reliability


  How well the items in two instruments measure the same construct
• Inter rater reliability


  Measures the consistency of scores assigned by two or more raters on a certain set of results
• Planning the data gathering procedure


  1. Develop data collection instruments and materials

  2. Seek permission to the authorities

  3. Use appropriate sampling technique

  4. Train the researchers or other people involved

  5. Obtain informed consent from participants

  6. Pilot-test the instruments
• Informed consent


  A document that explains the objectives of the study and extent of participant's involvement, and ensures confidentiality
• During data collection


  1. Provide instructions to the participants

  2. Administer the instruments

  3. Utilize triangulation
• Triangulation


  A technique for validating data using two or more sources and methods
• After data collection


  1. Immediately encode or transcribe data

  2. Safeguard the confidentiality of data

  3. Examine and analyze data using appropriate statistical tools
• Types of data analysis

  • Univariate (one variable)
  • Bivariate (two variables)
  • Multivariate (three or more variables)
• Descriptive statistics

  • Frequencies
  • Percentages
  • Range
  • Measures of central tendency (mean, median, mode)

  
• Inferential statistics


  Allows you to make predictions from the data