Dynamic Assessment: Co-constructing the Future with English Language Learners

Matthew E. Poehner, Tianyu Qin, Lu Yu

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Scopus citations


All forms of assessment are concerned with interpreting individuals’ performances not merely for the sake of describing those performances but for employing them as a basis for making claims about the knowledge and abilities believed to underlie them. Dynamic Assessment (DA) is a framework that challenges more conventional views of performance and the evidence of abilities most appropriate to forming generalizations regarding abilities. Specifically, DA requires the integration of teaching into assessment activity for the purpose of understanding learner responsiveness. Based on the theoretical writings of L. S. Vygotsky, DA proponents consider learner independent performance of tasks to reveal abilities that have fully formed whereas learner responsiveness to support that is offered when difficulties arise indicates abilities that may not have fully developed but are emerging. In this way, DA offers a developmental diagnosis that does not predict learner future functioning solely on the basis of past development but that instead begins to construct a future with learners during the assessment itself. This chapter considers the major theoretical underpinnings of DA and the models and principles elaborated in the extensive DA research literature concerned with cognitive abilities and general education. Discussion then turns to implementation of DA with L2 learners. Two studies are presented in detail that emphasize DA’s potential in both formal language testing situations and instructional contexts.

Original languageEnglish (US)
Title of host publicationSpringer International Handbooks of Education
PublisherSpringer Nature
Number of pages22
StatePublished - 2019

Publication series

NameSpringer International Handbooks of Education
VolumePart F1628
ISSN (Print)2197-1951
ISSN (Electronic)2197-196X

All Science Journal Classification (ASJC) codes

  • Education
  • Social Sciences (miscellaneous)

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