Reinforcement learning utilizes proxemics: an avatar learns to manipulate the position of people in immersive virtual reality

A reinforcement learning (RL) method was used to train a virtual character to move participants to a specified location. The virtual environment depicted an alleyway displayed through a wide field-of-view head-tracked stereo head-mounted display. Based on proxemics theory, we predicted that when the character approached within a personal or intimate distance to the participants, they would be inclined to move backwards out of the way. We carried out a between-groups experiment with 30 female participants, with 10 assigned arbitrarily to each of the following three groups: In the Intimate condition the character could approach within 0.38m and in the Social condition no nearer than 1.2m. In the Random condition the actions of the virtual character were chosen randomly from among the same set as in the RL method, and the virtual character could approach within 0.38m. The experiment continued in each case until the participant either reached the target or 7 minutes had elapsed. The distributions of the times taken to reach the target showed significant differences between the three groups, with 9 out of 10 in the Intimate condition reaching the target significantly faster than the 6 out of 10 who reached the target in the Social condition. Only 1 out of 10 in the Random condition reached the target. The experiment is an example of applied presence theory: we rely on the many findings that people tend to respond realistically in immersive virtual environments, and use this to get people to achieve a task of which they had been unaware. This method opens up the door for many such applications where the virtual environment adapts to the responses of the human participants with the aim of achieving particular goals.

Online Learning and Teaching in Higher Education, a book review

Peer-reviewed

An ontology to automated learning scenarios? an approach to its knowledge domain

Automation or semi-automation of learning scenariospecifications is one of the least exploredsubjects in the e-learning research area. There isa need for a catalogue of learning scenarios and atechnique to facilitate automated retrieval of stored specifications. This requires constructing anontology with this goal and is justified inthis paper. This ontology must mainlysupport a specification technique for learning scenarios. This ontology should also be useful in the creation and validation of new scenarios as well as in the personalization of learning scenarios or their monitoring. Thus, after justifying the need for this ontology, a first approach of a possible knowledge domain is presented. An example of a concrete learning scenario illustrates some relevant concepts supported by this ontology in order to define the scenario in such a way that it could be easy to automate.

Lifelong learning teachers' needs in virtual learning environments

Peer-reviewed

A virtual learning environment for pregraduate mathematical students

Peer-reviewed

Identifying pedagogical, technological and organizational barriers in virtual learning environments

Virtual learning environments are online spaces where learners interact with other learners, teachers, resources and the environment in itself. Although technology is meant to enhance the learning process, there are important issues regarding pedagogical and organizational aspects that must be addressed. In this paper we review the barriers detected in a virtual university which exclusively uses Internet as the main channel of communication, with no face-to-face requirements exceptthose related to final evaluation.

User Centered Desing in E-Learning Environments : from Usability to Learner Experience

The advent of the Internet had a great impact on distance education and rapidly e-learning has become a killer application. Education institutions worldwide are taking advantage of the available technology in order to facilitate education to a growing audience. Everyday, more and more people use e-learning systems, environments and contents for both training and learning. E-learning promotes educationamong people that due to different reasons could not have access to education: people who could nottravel, people with very little free time, or withdisabilities, etc. As e-learning systems grow and more people are accessing them, it is necessary to consider when designing virtual environments the diverse needs and characteristics that different users have. This allows building systems that people can use easily, efficiently and effectively, where the learning process leads to a good user experience and becomes a good learning experience.

Social Networks for learning : wikis, blogs and tagging in education

Fast developments in information and communications technologies and changes in the behaviour of learners demand educational institutions to continuously evaluate their pedagogical approaches to the learning and teaching process, both in face-to-face and virtual classrooms.

Analyzing lifelong learning student behavior in a progressive degree

Peer-reviewed

A catalogue of Primitive Scenario-Types : The First Step to the Automation of Learning Scenarios

Peer-reviewed