Effects of a Data-Based Decision Making Intervention on Student Achievement

Laura Staman, Anneke Timmermans, A. J. Visscher

Research output: Contribution to journalArticleAcademicpeer-review

9 Citations (Scopus)


Data-based decision making (DBDM) is becoming important for teachers due to increasing amounts of digital feedback on student performance. In the quasi-experimental study reported here, teachers, principals, and academic coaches from 42 schools were trained for two years in using the results of half-year interim assessments for providing students with tailor-made instruction. Our results did not show any main effects of this DBDM training trajectory on student achievement but did indicate interaction effects with students’ low prior achievement levels and socioeconomic status. Teachers experience difficulties in translating student progress data into adaptive instruction in the classroom. Implications of our findings for teacher professionalization are discussed.
Original languageEnglish
Pages (from-to)58-67
Number of pages10
JournalStudies in Educational Evaluation
Early online date14-Jul-2017
Publication statusPublished - Dec-2017


  • Professional development
  • Intervention
  • Data-based decision making
  • Student achievement

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