INTERPRETING LARGE SCALE NATIONAL LEVEL ASSESSMENT DATA IN MATHEMATICS BY USING RASCH ANALYSIS

Pāvels Pestovs, Dace Namsone

Abstract


Latvia is undergoing a nation-wide curriculum reform in general education, with an aim to help students to develop 21st century skills. In order to successfully implement reform, not only teacher performance in the classroom is important, but also the transformation of the school culture is of high priority. One of the key dimensions that is characteristic for a school as learning organization culture is whether it has data-driven culture and is using data on continuous basis to improve student achievement.

Large scale national level assessment data is used for many different purposes, however, this data only rarely is recognised as useful data source for planning actions to improve student achievement at school level. Authors argue that in different grades average performance of students cannot be compared in a meaningful way to develop action plan and evaluate the impact of the initiatives at the school level. It is based on the issues rising from varying difficulty level of the tests and different skills, which are being assessed. The study design is based on in-depth analysis of items of large-scale national level assessment in mathematics, defining minimum level of competency of mathematics and calculating percentage of students in school with minimum level of competence in a cohort. This analysis is conveyed for the students of 3rd, 6th and 9th grade by using Rasch model, thus allowing to effectively monitor the student performance during the general education and use of data to make informed decisions.

 


Keywords


assessment data; data-driven decisions; large scale national level assessment

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DOI: https://doi.org/10.17770/sie2020vol3.5118

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