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Mapping multiple dimensions of student learning: the ConstructMap program.

Cathleen A Kennedy1, Karen Draney

  • 1KAC Group, San Carlos, CA 94070 USA. cakennedy@berkeley.edu

Journal of Applied Measurement
|March 21, 2009
PubMed
Summary
This summary is machine-generated.

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New computer programs like ConstructMap help teachers interpret complex performance-based assessment data. This allows for a better understanding of what students know and can do, moving beyond simple right/wrong answers.

Area of Science:

  • Educational Measurement
  • Psychometrics
  • Educational Technology

Background:

  • Traditional assessments often use items with single correct answers, limiting insight into student capabilities.
  • Performance-based assessments offer richer data but present scoring and interpretation challenges, including potential bias.
  • Advances in psychometrics and assessment design enhance the feasibility of evaluating performance-based tasks.

Purpose of the Study:

  • To develop a tool assisting educators in interpreting and representing complex performance-based assessment data.
  • To address the technical difficulties and potential biases associated with scoring performance tasks.
  • To provide a method for understanding students' knowledge and application of that knowledge.

Main Methods:

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  • Development of the ConstructMap computer program.
  • Inputting student scores on performance-based items.
  • Utilizing multidimensional item response theory (IRT) models for proficiency computation.
  • Generating graphical representations of student proficiencies.

    • Main Results:

    • ConstructMap facilitates the interpretation of multidimensional performance data.
    • The program computes student proficiencies using advanced psychometric models.
    • Graphical outputs provide clear visualizations of student performance across variables.

    Conclusions:

    • The ConstructMap program enhances the effective and efficient assessment of student performance.
    • It aids teachers in making informed interpretations of what students know and can do.
    • This technology supports a more nuanced understanding of student learning beyond traditional metrics.