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Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
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Related Experiment Video

Updated: Apr 11, 2026

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties
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Demystifying reflective practice: Using the DATA model to enhance evaluators' professional activities.

Tiffany L Smith1, Patrick B Barlow2, John M Peters3

  • 1University of Wisconsin-Stout, USA.

Evaluation and Program Planning
|June 9, 2015
PubMed
Summary
This summary is machine-generated.

Reflective practice (RP) is crucial for evaluators. The DATA framework provides a structured approach to critically analyze and improve evaluation practices through describing, analyzing, theorizing, and acting.

Keywords:
CompetenciesEvaluationReflectionReflective practiceStandards

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Area of Science:

  • Evaluation Practice
  • Professional Development
  • Applied Psychology

Background:

  • Reflective practice (RP) is a core competency in evaluation.
  • Evaluators currently lack sufficient guidance for implementing RP.
  • This gap hinders professional growth and practice improvement.

Purpose of the Study:

  • To introduce the "DATA" integrated RP framework.
  • To demonstrate RP as a practical tool for evaluators.
  • To provide a model for enhancing evaluation practice.

Main Methods:

  • Description of the "DATA" acronym framework by Peters (1991, 2009).
  • Explanation of each step: Describing, Analyzing, Theorizing, and Acting.
  • Introduction to the application of the framework in a practical context.

Main Results:

  • The "DATA" framework offers a systematic process for RP.
  • Each step (Describe, Analyze, Theorize, Act) guides evaluators through critical reflection.
  • The model facilitates the development of practical theories to inform action.

Conclusions:

  • The "DATA" framework serves as a valuable tool for evaluators.
  • Implementing RP through this model can enhance evaluation practice.
  • This structured approach supports continuous professional improvement.