Problem
Research questions and friction points this paper is trying to address.
Causal Modelling
Student Competency Assessment
Intervention
Counterfactual Reasoning
Causal Modelling of Support Interventions for Student Competency Assessment
🤖 AI Summary
该研究采用结构因果建模方法改进学生能力评估，通过明确建模干预措施和反事实推理来提高教育策略的有效性。
📝 Abstract
Accurate assessment of student competencies is essential for enabling educators to identify individual needs, design targeted interventions, and evaluate the effectiveness of educational strategies. Empirical assessment procedures are typically grounded in psychometric models, such as item response theory, which relate student competence levels to performance on assessment tasks. In this paper, we advocate adopting a structural causal modelling approach to educational assessment, moving beyond probabilistic belief updating toward a framework that explicitly supports interventional and counterfactual reasoning. We propose a corresponding protocol for its construction and analyse the practical relevance of forms of reasoning that remain inaccessible to standard associative models, including the explicit modelling of interventions such as hints and the related counterfactual scenario analysis. Although our protocol requires the structural equations to be elicited from experts, the necessary information is purely logical and does not rely on probabilistic, less tenable assumptions. We illustrate the approach using data from an assessment that employs complex tasks designed to measure compulsory school student algorithmic skills.
Innovation
Methods, ideas, or system contributions that make the work stand out.
structural causal modelling
interventional reasoning
counterfactual analysis
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