A framework for assessing computational thinking skills in the physics classroom: study on cognitive test development

Area of Science:

• Physics Education
• Educational Technology

Background:

• Computational thinking skills (CTs) are crucial for modern problem-solving.
• Assessing CTs in physics learning requires a robust framework.
• Existing assessment methods may not fully capture the nuances of CTs in science.

Purpose of the Study:

• To develop and validate a comprehensive assessment framework for computational thinking skills in physics learning.
• To establish reliable and empirically supported indicators for CTs.
• To create a tool for optimizing the measurement of CTs in science education.

Main Methods:

• A two-stage approach: theoretical framework development and empirical validation.
• Development of a test instrument with diverse question types (multiple-choice, essay) on sound waves.
• Empirical validation using item characteristic analysis, Explanatory Factor Analysis (EFA), and Confirmatory Factor Analysis (CFA) with 108-113 high school students.

Main Results:

• The theoretical study identified seven key CTs indicators: decomposition, redefine problems, modularity, data representation, abstraction, algorithmic design, and strategic decision-making.
• Empirical validation confirmed the test items fit the one-parameter logistic (1PL) model.
• Factor analysis (EFA and CFA) demonstrated the framework's unidimensionality, indicating a coherent construct.

Conclusions:

• The developed framework provides a valid and reliable method for assessing computational thinking skills in physics.
• The framework's indicators and empirical validation support its use in optimizing CTs measurement.
• This tool can enhance the evaluation of students' computational thinking abilities in science education.