Maite Martín

Helping Teachers to Track Student Evolution in a B-Learning Environment

SigMa is an adaptable feedback generation tool for the three kinds of actors involved in a blended-learning process: teachers, students, and the e-learning platform. This paper focuses on the teacher tool and defines its desirable functionalities and main components. The teacher tool gathers data provided by the e-learning platform’s diagnostic capabilities and analyses it. The results are shown to teachers by means of a Visualisation Interface that informs them about course development and suggests possible changes and improvements. A Teacher Profile is used to adapt the feedback to match teachers’ strategies and preferences.

Generating Teacher Adapted Suggestions for Improving Distance Educational Systems with SIgMa

In this paper we present SIgMa, an adaptable feedback generation tool for teachers which gives information about course development in an educational Web environment with diagnostic capabilities. First student results are analysed using statistical calculations and data mining techniques. Afterwards, the feedback provision is carried out by a rule-based system that recognizes anomalous behaviour patterns among the analysis results and provides some suggestions for improvement which are adapted to teacher strategies and preferences by means of a teacher model. We present the main proposal and the implementation and a test of a restricted prototype.

Experiences in Visualizing the Analysis of Blended-Learning Interactions to Support Teachers

In the context of the MAgAdI environment, this paper presents SIgMa, a teacher oriented tool, and SIgBLE, its general framework basis. SIgMas general aims are to automatically detect visible signs of failure or success among data coming from interactions happened on blended learning environments, and to provide relevant feedback adapted to teachers. First, we introduce SIgBLE and the interface of the SIgMa prototype. A usability test of the current prototype is also presented.

Focusing on Personal Organization to Enhance Overall E-learning

This paper describes the inclusion of a recommendation system in the MAGADI [1] blended-learning environment. It seeks to help students with their overall study process by recommending both which courses to study for and the contents to be developed on each

Supporting Blended-Learning: tool requirements and solutions with OWLish

Currently, most of the educational approaches applied to higher education combine face-to-face (F2F) and computer-mediated instruction in a Blended-Learning (B-Learning) approach. One of the main challenges of these approaches is fully integrating the traditional brick-and-mortar classes with online learning environments in an efficient and flexible way. In this paper, we present a set of requirements to be met by a computer system in order to adequately support both students and teachers in a B-Learning context. Then, it defines a suitable conceptual architecture to meet the requirements, and the multi-agent implementation of the architecture. Next, it presents the evaluation of the functionality implemented. Finally some conclusions are drawn.