Learning Analytics in an e-Testing Application: Premises and Conceptual Modelling
Learning Analytics in an e-Testing Application: Premises and Conceptual Modelling

Summary/Abstract: Learning analytics in online instruction is recognized as an emergent research field that continuously grows, taking the data generated in virtual learning environments and transforming it into information to improve teaching and learning processes. The main purpose of a learning analytics system is to offer customizable metrics that can be used to track specific features, e.g. the effectiveness of certain formative assessment tools, the correlation between virtual participation and final grades, that supports user’s goals and objectives. One of the most significant benefits of learning analytics is being able to offer support for eLearning experience personalization. The current paper presents a web based application that implements data analytics in a virtual learning environment, to validate the new paradigms of learning (social / collaborative, user-centred) and relies on the current technologies. The system is described as a useful tool for personalized feedback, allowing to track individual online learner progress throughout the assessment process, by comparing the results in the learning management system, using charts and tables to analyse each online learner’s performance and the user’s progress. This information allows us to recommend supplemental courses or modules to fill performance gaps and improve the comprehension. This tool builds the learner profile, by grouping the user's data from different sources, by analysing them and providing a complex result on four levels of the virtual behaviour of the student: the descriptive level (what has happened), the diagnosis level (why it happened), the predictive level (what will happen, for example signalling the lack of performance and the risk of failure) and the prescription level (what should be done, for example the recommendation of educational resources). The beneficiaries of the analytics module are the students who will become aware of the involvement or lack of involvement in their educational activities, and the quality of this participation and its effects on their lives (for example, finding a job), teachers / trainers who will be able to improve teaching to fulfil students’ needs, and universities that will be able to analyse the effectiveness of their educational offer.

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