A framework for decision support for learning management systems

Learning Management Systems (LMS) provide a valuable platform for e-learning that offer great flexibility. However, compared to traditional learning environments they are challenging and complex for decision-makers, both teachers and learners. At the same time, LMS environments offer opportunities for analysis by storing large quantities of data, such as web log files and data about students and content, which are not generally available in the traditional environment.Motivated by approaches in other domains, such as e-commerce and clinical management, in this article we propose to relatethe complex decision environment with the possibilities of using large quantities of data.In this paper we review relevant literature on educational data mining (EDM) and combining that with a standard data mining methodology we propose a conceptual framework that appropriately relates the methods of data mining to the settings of teaching and learning in a LMS environment. In contrast to other frameworks, our conceptual framework enables EDM research to be more integrated with the task domain. In our framework, teaching and learning activities and the decisions required to control those activities are addressed by relating the following three elements: pedagogy; learning activities; and decision-making. The significance of our work is that the framework enables us to compare between different research studies as well as provide practical guidelines for developing EDM solutions. The framework also provides a number of further directions for researchers which follow naturally from a decision-centric perspective and from the full implementation of the contextual phases of the data mining life cycle.