Personalized Learning in Radiology - An Adaptive Learning Strategy for Teaching Chest X-ray Interpretation
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An adaptive learning system is a software system used in education that analyzes a student sinteractions in the system and adapts and presents learning material based on thisanalysis. The student gets a personalized learning experience that is tailored to focus onknowledge the student is lacking, and the knowledge is presented in a way that the specificstudent best understands. There are many commercial adaptive learning systems available,but most of them focus on the most common areas in education. These are areas likemathematics, language, physics, chemistry, biology or history. There are still some morespecialized areas where there are little or no available adaptive learning systems. This master's thesis is investigating how adaptive learning can be used to create a learningsystem in radiology. More specifically a learning system that teaches students howto interpret chest X-ray images, so that students learn how to detect serious and possiblylife threatening conditions. There are many different adaptive learning techniques, and akey question for this thesis is to identify which of these techniques that are applicable inthe teaching of chest X-ray interpretation. Chest X-ray interpretation can in general beclassified as a form of image analysis. Techniques that work here might therefore also beapplicable in teaching other forms of image analysis. In order to identify the appropriate adaptive learning techniques for chest X-ray interpretation, a prototype system was developed. The development was done in cooperationwith experts in radiology, who gave feedback during the development, and contributedby creating the learning material the system used as base material when it adapted to students. Three different adaptive methods were developed and implemented in the prototypesystem: adaptive case selection, adaptive follow-ups and adaptive task type. After the development the methods had to be tested to see if they managed to adapt to the students.The testing was done on students of medicine through two user testing sessions, wherethe students were observed as they tested the system. The students were also asked toanswer a series of questions in a survey, and the system automatically collected user datawhile the students tested the system. Analysis of these data showed that adaptive contenttechniques seem to be the preferred category of adaptive learning techniques when developingan adaptive learning system for chest X-ray interpretation. Also task design shouldhave a problem-solving focus, where educational instructions are presented, followed bya problem where the teaching from the instructions can be applied.