Data-Based Decision Making, Assessment for Learning, and Diagnostic Testing in Formative Assessment

• In Event: Poster Session 6
  In Poster Session: Studies of Assessment Comparability, Teacher Perceptions and Use of Data, and Student Preparation for Testing

Abstract

Recent research has highlighted the lack of a uniform definition of formative assessment, although its effectiveness is widely acknowledged. This study addresses the theoretical differences and similarities amongst three approaches to formative assessment that are currently most frequently discussed in educational research literature: Data-based decision making (DBDM), assessment for learning (AfL), and diagnostic testing (DT). This study shows that although the theoretical underpinnings of DBDM, AFL, and DT differ, possibilities for implementing an overarching formative assessment and formative evaluation approach exist. Moreover, the integration of the three assessment approaches can lead to more valid formative decisions. Future research is needed to examine the actual implementation of a mix of these three approaches, with their associated challenges and opportunities.

Authors

• Fabienne Van der Kleij, Cito

• Jorine Adinda Vermeulen, Universiteit Twente

• Kim Schildkamp, Universiteit Twente

• Theo Eggen, Cito