Integrating data-based decision making, Assessment for Learning and diagnostic testing in formative assessment

Fabienne M. van der Kleij*, Jorine A. Vermeulen, Kim Schildkamp, Theo J.H.M. Eggen

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

75 Citations (Scopus)
270 Downloads (Pure)

Abstract

Recent research has highlighted the lack of a uniform definition of formative assessment, although its effectiveness is widely acknowledged. This paper 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). Furthermore, the differences and similarities in the implementation of each approach were explored. This analysis shows that although differences exist amongst the theoretical underpinnings of DBDM, AfL and DT, the combination of these approaches can create more informed learning environments. The thoughtful integration of the three assessment approaches should lead to more valid formative decisions, if a range of evidence about student learning is used to continuously optimise student learning.
Original languageEnglish
Pages (from-to)324-343
Number of pages20
JournalAssessment in education
Volume22
Issue number3
Early online date22 Jan 2015
DOIs
Publication statusPublished - 3 Jul 2015

Keywords

  • formative assessment
  • data-based decision making
  • assessment for learning
  • diagnostic testing
  • theoretical comparison
  • 2023 OA procedure

Fingerprint

Dive into the research topics of 'Integrating data-based decision making, Assessment for Learning and diagnostic testing in formative assessment'. Together they form a unique fingerprint.

Cite this