Collaborative Learning and Authoring in the Frame of e-Projects

It is presented a research on the application of a collaborative learning and authoring during all delivery phases of e-learning programmes or e-courses offered by educational institutions. The possibilities for modelling of an e-project as a specific management process based on planned, dynamically changing or accidentally arising sequences of learning activities, is discussed. New approaches for project-based and collaborative learning and authoring are presented. Special types of test questions are introduced which allow test generation and authoring based on learners’ answers accumulated in the frame of given e-course. Experiments are carried out in an e-learning environment, named BEST.

An Approach to Collaborative Filtering by ARTMAP Neural Networks

Recommender systems are now widely used in e-commerce applications to assist customers to find relevant products from the many that are frequently available. Collaborative filtering (CF) is a key component of many of these systems, in which recommendations are made to users based on the opinions of similar users in a system. This paper presents a model-based approach to CF by using supervised ARTMAP neural networks (NN). This approach deploys formation of reference vectors, which makes a CF recommendation system able to classify user profile patterns into classes of similar profiles. Empirical results reported show that the proposed approach performs better than similar CF systems based on unsupervised ART2 NN or neighbourhood-based algorithm.

Collaborative Learning and Assessment in e-Learning

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2016