A preliminary study of the progress on using Bayesian Networks for educational assessment

Educational assessment has been subject to numerous studies in recent years. The emergence of Bayesian Networks (BN) as a powerful probabilistic inference tool has been integrated by many into researches on modeling the education domain to measure technical as well as cognitive performance of a student. We have seen many different subjective perspectives in interpreting the educational context, such as measuring individual educational backgrounds, emotional state, teaching methods, financial background, students' learning styles, specific academic concept skills and many other abstract variables. Comparatively, there hasn't been a widely-accepted Bayesian Network model in the domain of educational assessment and we are in need of one. This paper provides a preliminary study of the progress of research on educational assessment methods using Bayesian Networks. In this summarized survey of literatures we review and compile the recent trends of how researchers have applied and implemented Bayesian Networks to solve the complex problem of educational assessment in their own environments.