평가 리터러시(assessment literacy)

  1. 평가 리터러시란 무엇인가?
  2. 교육자들이 아직 평가에 익숙하지 않은 이유는 무엇인가?
  3. 교육자가 평가에 능숙해야 하는 이유는 무엇인가?
  4. 교육자가 평가에 능숙해지려면 어떻게 해야 할까?

평가 리터러시는 교육적 결정에 영향을 미칠 수 있는 기본적인 평가 개념과 절차에 대한 개인의 이해로 구성됨(Popham, 2018)

CHECKLIST FOR SEM

SEM 연구를 발표할 때 유용한 일반적 제안

  1. Provide a review of literature that supports your theoretical model.
  2. Provide information about the software program used along with the version.
  3. Indicate the type of SEM model analysis.
  4. Include correlation matrix, sample size, means, and standard deviations of
    variables.
  5. Include a diagram of your theoretical model.
  6. Describe issues concerning normality and missing data.
  7. For interpretation of results, indicate estimation procedure used and why:
    describe fit indices used and why; include power and sample size determination.
  8. Provide unstandardized parameter estimates with corresponding standard
    errors as well as standardized parameter estimates.
  • Basic Issues

    1. Is sample size sufficient (power, effect size)?
    2. Have you addressed missing data (MCAR, MAR, etc.)?
    3. Have you addressed normality, outliers, linearity, restriction of range?
    4. Are you using the correct covariance matrix?
    5. Have you selected the correct estimation method?
    6. Is the theoretical model identified (df = 0 or greater)?
  • Analysis Issues

    1. Have you reported the correct fit indices?
    2. Have you provided unstandardized estimates (with corresponding standard
      errors) and standardized estimates?
    3. Have you scaled the latent factors appropriately?
    4. Have you justified any model modifications (e.g., adding error covariances)?
    5. Have you cross- validated the model (assuming sufficient sample size)?
    6. Have you diagrammed the model and/ or provided estimates in the diagram?