There have been many reforms in schools throughout history aimed at improv- ing quality and thereby enhancing the learning of the students. In recent dec- ades, many efforts have been made to implement data-driven methods in schools to improve the quality of education. There are some studies that show that this can lead to significant improvements in students’ academic achieve- ment, while other studies show mixed results. The aim of this thesis is to in- vestigate how data can be used by teachers, principals, and district adminis- trators to improve quality in education. The aim was accomplished by study- ing how data-driven projects were planned and implemented in a number of K-12 schools in Sweden. The schools were part of a three-year-long research and development program facilitated by an independent research institute, Ifous. The planning and implementation process was investigated using a case study and mixed methods. Multiple sources of data, including interviews and project plans, were collected and analyzed using thematic analysis.

Results show that data-driven decision-making can lead to insights that could not be achieved without frequent and systematic data collection. The thesis also concludes that there are a number of factors that influence the implemen- tation process of data-driven methods, namely data collection and analysis, frequency, anonymity, involving students, and organizational changes. There are also a number of challenges that schools face in their planning process: time and resources, competence, ethics, digital systems, and common lan- guage. Among these, the main challenge was shown to be competence in data literacy among teachers and school staff, and there is a need for professional development in this area in order to create the conditions necessary for suc- cessful projects. Another conclusion is that schools should not only use data in temporary projects, as this needs to be part of their daily work in their effort to achieve continuous improvement. To accomplish this, there is a need to build a capacity for using data, which includes data systems, processes, organ- izational changes, and professional development.

The main contributions of this thesis are: 1) enabling an understanding of the necessary conditions for a successful implementation of data-driven decision- making (DDDM); 2) contributing to the previously developed framework for data literacy; 3) exploring how data-driven methods can be used to enhance democratic values among students as a part of school development; 4) inves- tigating the role of a common language in school improvement; and 5) identi- fying the lack of models for collaboration between micro, meso, and macro levels (classroom, school, and district) within the school organization.