Analysing current data mining techniques in the context of today's teaching/learning environments

Changes in the education system are creating a host of new challenges for colleges and universities. Due to the almost unlimited mobility of learners, the willingness to continue their education and the industry's demand for shorter study periods, not only are the framework conditions for today's degree programmes changing, but the requirements for learning content are also undergoing a process of change. In general, but particularly in the case of training on operational application systems (such as ERP systems), a stronger practical orientation is required. The teaching of theoretical content must go hand in hand with practical work on the system so that the students, as the future users, are able to cope with the ever-increasing complexity of the systems. The aim of future developments in this area should be to learn how to handle these systems so that they can be used efficiently in day-to-day operations. In order to meet these new requirements in terms of framework conditions and learning content, new teaching and learning environments need to be designed. But what techniques can be used to improve teaching, particularly in the context of business application systems? For example, how can the success or failure of tasks or work steps be measured? Data mining, the process of recognising patterns from large amounts of data, has been the subject of countless scientific studies for many years. Over the course of time, a variety of forms of data mining have emerged for different areas of application. Process mining, for example, focuses on the extraction of formalised process knowledge from the recording of process executions. For some time now, data mining techniques have also been playing an increasingly important role in teaching/learning environments. Based on web mining, educational data mining involves analysing data sets from teaching/learning environments, such as learning management systems. These and other data mining techniques have emerged over the years, but do they sufficiently fulfil the current requirements of the changing higher education environment?

Prof. Dr Jorge Marx Gómez
Dipl.-Inform. Dirk Peters