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Reliability and Validity01:29

Reliability and Validity

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Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
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Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...
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Accuracy and Precision01:52

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Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.  Highly accurate...
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The representative heuristic describes a biased way of thinking, in which you unintentionally stereotype someone or something. For example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.
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Uncertainty in Measurement: Accuracy and Precision03:37

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Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
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Regression Toward the Mean01:52

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Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
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Meta-analysis in a digitalized world: A step-by-step primer.

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Related Experiment Video

Updated: Jun 19, 2025

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA
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Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA

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Teachers' judgment accuracy: A replication check by psychometric meta-analysis.

Esther Kaufmann1

  • 1Research Methods, Assessment and iScience, Department of Psychology, University of Konstanz, Konstanz, Germany.

Plos One
|July 25, 2024
PubMed
Summary

Teachers

Area of Science:

  • Educational Psychology
  • Psychometrics

Background:

  • Teacher judgment accuracy is crucial for student assessment.
  • Previous meta-analyses have estimated teachers' accuracy in judging student academic achievement.
  • Accurate judgment relies on correlating teacher perceptions with student test scores.

Purpose of the Study:

  • To update and re-analyze existing meta-analyses on teacher judgment accuracy.
  • To investigate sources of variance in previous findings using psychometric meta-analysis.
  • To highlight methodological limitations in existing studies and propose improvements.

Main Methods:

  • Conducted a psychometric meta-analysis on updated databases of teacher judgment accuracy studies.
  • Analyzed and corrected for artifacts such as sampling error and measurement error.

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  • Assessed the impact of aggregation and publication bias on study results.
  • Main Results:

    • Previous reviews underestimated teachers' judgment accuracy.
    • Overestimation of variance in accuracy estimates was linked to uncorrected artifacts (at least 10%).
    • Many studies lack sufficient data for rigorous meta-analysis.

    Conclusions:

    • Classical meta-analysis can misattribute variance to moderators instead of artifacts.
    • Psychometric meta-analysis provides a more accurate synthesis of teacher judgment accuracy.
    • Online data repositories and standardized reporting are needed to improve replicability and scientific rigor.