Design, development and evaluation of an adaptive open and distance learning system

Learning systems that can adapt the content or the way the content is served according to learners' needs, characteristics or preferences are called as adaptive learning systems. One of the first steps in building an adaptive learning environment is learner modelling. Then, in the second step, individualized learning experiences are designed and the means of adaptivity are identified. The main purpose of this mixed method study is to design, develop and evaluate an adaptive open and distance learning environmen. Focus group discussions, semi-structured interviews, an online questionnaire, and analytics were used to collect data and analysis. A massive open online course on data mining, entitled as "Intorduction to Data Mining" (Veri Madenciliğine Giriş) was offered in three terms. The results indicated that the learners were highly satisfied with the adaptive learning environment. They believed the adaptive learning environment helped their learning and allow to be more persistent in the course. On the other hand, there was no statistically significant difference in their perceived learning, perceived satisfaction and engagement according to their cognitive styles and adaptation status. Based on the research findings, a series of recommendations for future research and implementations were presented.