Assessing Complex Patterns of Student Resources and Behavior in the Large Scale

Author:

Neumann Knut,Schecker Horst,Theyßen Heike

Abstract

Large-scale assessments still focus on those aspects of students’ competence that can be evaluated using paper-and-pencil tests (or computer-administered versions thereof). Performance tests are considered costly due to administration and scoring, and, more importantly, they are limited in reliability and validity. In this article, we demonstrate how a sociocognitive perspective provides an understanding of these issues and how, based on this understanding, an argument-based approach to assessment design, interpretation, and use can help to develop comprehensive, yet reliable and valid, performance-based assessments of student competence. More specifically, we describe the development of a computer-administered, simulation-based assessment that can reliably and validly assess students’ competence to plan, perform, and analyze physics experiments at a large scale. Data from multiple validation studies support the potential of adopting a sociocognitive perspective and assessments based on an argument-based approach to design, interpretation, and use. We conclude by discussing the potential of simulations and automated scoring methods for reliable and valid performance-based assessments of student competence.

Publisher

SAGE Publications

Subject

General Social Sciences,Sociology and Political Science

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Learning Sciences Perspective on the Design and Use of Assessment in Education;The Cambridge Handbook of the Learning Sciences;2022-04-30

2. Methodologies;The Cambridge Handbook of the Learning Sciences;2022-04-30

3. Instructional Coherence and the Development of Student Competence in Physics;Physics Education;2021

4. The digitalization of science education: Déjà vu all over again?;Journal of Research in Science Teaching;2020-09-11

5. Preservice Science Teachers’ Strategies in Scientific Reasoning: the Case of Modeling;Research in Science Education;2020-07-22

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