Philip Andersson and Simon Kalicinski
This study aims to assert if using statistical graphics for data visualization can make the identification of data variation, trends and significance, as well as connecting these to corresponding changes or events in a student’s academic progress, easier. Focus lies on exploring the idea of individualizing education and the theory behind data visualization, accompanied by an empirical comparative study of how decision-making is affected by use of statistical graphics compared to conventional data multitudes. The main study was preceded by a pre-study and a literature study, which were used to gather knowledge of the current ambitions in and knowledge of individualized education and learning styles amongst teachers, as well as providing a solid backing of theory to support the development and conducting of the main study. The main study concluded that teachers are more keen to take learning styles into account in their decisions for individualized learning when presented with visualized data. On the other hand, a consequence is that the focus on their students shifts and other significant attributes are overlooked during assessment of students.