IDENTIFYING AND FOSTERING STUDENTS' EXPERIMENTAL COMPETENCES

Competence Development in Experimentation

Overview

• Competence development in experimentation can be classified into three main fields:

  • Evaluation of theory and development of hypotheses.

  • Development of experimental design and conducting experiments.

  • Evaluation of evidence obtained from experiments.

Field 1: Evaluation of Theory and Development of Hypotheses

• Level 0: No Hypotheses

  • Students perform hands-on activities without clear assumptions or understanding of cause-and-effect.

• Level 1: Unsystmatic Hypothesis Usage

  • Students generate hypotheses, but they are often irrelevant or incomplete, indicating a lack of deep understanding of the theory.

• Level 2: Systematic Hypothesis Application

  • Students can identify relevant hypotheses but struggle with revisions based on experimental outcomes.

• Level 3: Adequate and Systematic Application

  • Students efficiently apply and revise hypotheses as needed, demonstrating strong analytical skills.

Field 2: Development and Conducting of Experiments

• Level 0: Unsystematic Use of Variables

  • Students change all variables randomly without understanding their effects, e.g., changing all ingredients while baking bread.

• Level 1: Partial Systematic Use

  • Students manage to include or exclude some relevant variables but fail to test the critical variable.

• Level 2: Systematic Testing in Familiar Domains

  • Students can plan and evaluate experiments effectively in familiar situations but struggle with unfamiliar contexts.

• Level 3: Competence Transfer Across Domains

  • Students can apply learned competencies from one domain to another, indicating advanced understanding and adaptability.

Field 3: Evaluation of Evidence

• Level 0: Lack of Data Relation

  • Students analyze results but fail to connect data with hypotheses, showing a misunderstanding of experimental goals.

• Level 1: Illogical Data Analysis

  • Students analyze data but do so in a flawed manner, failing to recognize key contrasts (e.g., experimental vs. control groups).

• Level 2: Logical Analysis of Data

  • Students can logically apply data to hypotheses but struggle with unexpected results or anomalies.

• Level 3: Advanced Data Analysis

  • Students can manage unexpected data, including measurement errors, and relate findings to hypotheses appropriately.

Correlation Between Competence Fields

• Competence levels in the three fields are highly correlated; achievement in one area often reflects similar proficiency in others.

• Uncertainty exists about whether these competencies are context-dependent:

  • Some research suggests competencies are transferable across contexts, while other studies point to strong context dependencies.

Application of Competence Models

• Competence models serve as tools to track student progress in experimentation.

• They help identify areas specifically needing improvement, enabling targeted interventions for enhancing students' experimental competencies.