Since the school year 20022003, the IUFM of Alsace has provided an on-line training program for its teacher trainees. The trainees gain experience by teaching a class in primary school, using computer technology. This training program provides on-line feed-back, familiarizes our trainees with new techniques and prepares them to use these techniques to improve the way they teach. We encourage ou...

In recent years, the development of Information and Communication Technologies (ICT) has contributed to the generation of a number of interesting initiatives in the field of music education and training in virtual learning environments. However, music education initiatives employing virtual learning environments have replicated and perpetuated the traditional model, resulting in sub-optimal use...

This study is a phenomenological study exploring faculty experiences teaching online coursework in master’s programs in education. The study sought to understand and categorize learning factors that might produce stress and job burnout in the online instructional environment. In addition, the demands, expectations, and associated stress-producing factors in the online instructional environment ...

We propose a novel online learning algorithm for Restricted Boltzmann Machines (RBM), namely, the Online Generative Discriminative Restricted Boltzmann Machine (OGD-RBM), that provides the ability to build and adapt the network architecture of RBM according to the statistics of streaming data. The OGD-RBM is trained in two phases: (1) an online generative phase for unsupervised feature represen...

-Classification is one of the data mining techniques that analyses a given data set and induces a model for each class based on their features present in the data. Bagging and boosting are heuristic approaches to develop classification models. These techniques generate a diverse ensemble of classifiers by manipulating the training data given to a base learning algorithm. They are very successfu...

It is widely recognized that the Internet offers tremendous potential for education at all levels. This article describes a case study examining how an Internet communication program, EdPsy Web, which was used to support a pre-service teacher training course changed the quality of social and intellectual interactions relative to those found in a traditional classroom setting. Using a post-cours...

The applications of network technology to pre-service and in-service teacher training are wide in scope but may nevertheless be grouped into two broad categories: the network as a source of assistance (or self-help) for teachers during the classroom transfer of knowledge which they have gained on an on-site training course; and the network as an environment where the training process actually t...

This article focuses on the impact on learning processes when digital technologies are integrated into PBL (problem-based learning) oriented distance training. Based on socio-cultural perspectives on learning and a comparative distance-campus as well as a time-perspective, instructor and student roles, and learning activities were explored. Interviews with instructors and students were collecte...

Online algorithms that process one example at a time are advantageous when dealing with very large data or with data streams. Stochastic Gradient Descent (SGD) is such an algorithm and it is an attractive choice for online Support Vector Machine (SVM) training due to its simplicity and effectiveness. When equipped with kernel functions, similarly to other SVM learning algorithms, SGD is suscept...

BACKGROUND A novel online resource has been developed to aid OSCE examiner training comprising a series of videos of OSCE performances that allow inter-examiner comparison of global grade decisions. AIMS To evaluate this training resource in terms of usefulness and ability to improve examiner confidence in awarding global grades in OSCEs. METHOD Data collected from the first 200 users inclu...