Intelligent Decision Technologies

In this paper, we describe an intelligent hybrid recommender system incorporated in a collaborative learning environment for UML. It exports recommendations for both the trainees and the trainer of the system. The recommendations directed to the trainees are related to the help topics that they should study and the appropriate colleague/s with whom s/he could collaborate according to his/her present level of expertise and matching personality characteristics. The addressed to the trainer recommendations concern the most effective organization of the trainees into groups evaluating a given groups' structure (related to the level of expertise of the trainees) and desired/undesired combinations of stereotypes of personality characteristics. The recommender system uses both the Content-based and the Collaborative Filtering technique to export these recommendations. The algorithm used is Simulated Annealing. The system builds hybrid student models based on the perturbation and the stereotype-based modelling techniques. The evaluation presented at the end of this paper indicates optimistic results.

This paper, based on an analysis of current research and relevant implementations proposes the implementation of OWLearn an adaptive and personalized e-Learning system developed with open source technologies. Adaptation and personalization received very little coverage in the most commonly used e-learning platforms. An e-learning course in these systems is usually designed without matching students' and teachers' needs and objectives as closely as possible, and without adapting during course progression. The proposed open source e-learning system offers profiling and personalization services for the teacher and student while at the same time adapts the educational content and tools in the basis of the acquired user's profile. Finally, the proposed system offers collaborative learning using social networking services and mobile learning tools for achieving ubiquitous life long learning.

Personalization (i.e., addressing the learner personally by the formulation of instructional explanations) is an important motivational factor when learning with animations in computer-based settings [11]. We analyzed this method by teaching the complex subject of the circulatory system in a computer-based learning environment with narrated graphics lasting approximately 12 min. We experimentally compared three conditions ( n = 59 students) that differed with respect to whether and how the narrations were personalized: (1) formal text using third-person constructions, (2) weak personalized text using the pronouns “you” and “I” and their associated possessive forms rather than the third-person constructions, and (3) strong personalized text that included the weak personalization and additional direct comments to the learner. We found that personalization fostered the acquisition of transfer knowledge compared to the formal control condition, but retention performance was not affected. The variation of the intensity of personalization, however, had no influence on learning outcome. The groups also did not differ in their acceptance of the learning environment.

During the last decades there have been extensive investments in order to stimulate ICT-supported flexible learning. The increased interest in flexible learning has heightened the need for a critical analysis of the consequences of on-line teaching. However, critics argue that the new teacher role has not yet been thoroughly scrutinized. The aim of this paper is to trigger a debate about the changes and challenges related to the modified teacher role at universities. The methodology follows empirical data from interviews and literature surveys as well as our own experience in different flexible courses and continuous training of colleagues. Results of this study problematize both positive and negative implications on the teacher role in ICT-supported flexible learning, e.g. tendencies of teacher de-professionalization, increased ICT-dependency and uncertainty of quality in learning outcome. In conclusion our findings emphasize the need for increased teacher training in using ICT in educational settings.

World representation is a crucial aspect of any design and development effort in the field of Virtual Environments today. Approaches presented so far don't seem to address all relevant needs. In this paper, we propose a model for the representation of physical properties, functionality and semantics of objects in virtual environments. Our proposed model aims to be uniform, pragmatic, systematic and extendible. We demonstrate practical usage of the proposed model through a complete example. Also, we briefly describe two case studies of fully-implemented virtual environment applications that encompass the proposed model in the context of diverse virtual agent interactions.

Augmented Reality is a technological area that has met with significant growth in our times and its applications cover an ever increasing range of everyday life activities. Despite the rapid development of Augmented Reality technology, not much attention has been given to the important aspect of system's interface usability. To date, some of the methods used in the assessment of common software applications are also employed in the limited number of studies regarding the usability assessment of Augmented Reality systems. In this paper, we investigate the issue of usability evaluation of Augmented Reality systems and we discuss the use of the assessment methods currently employed for traditional applications. Furthermore, we present and discuss issues that arise from their employment in the assessment of Augmented Reality systems and possible ways to overcome these issues.

Effectively transmitting alert information to soldiers on patrol is important and challenging. Such signals must be covertly presented, yet must effectively represent appropriate levels of urgency. Few researchers have investigated the joint effects of signal reliability and modality on receiver trust and compliance. The purpose of this study was to investigate whether alerts delivered through different sensory modalities (visual, auditory, or tactile) and different reliabilities (60% or 80% true alerts) yielded different trust levels and target identification behaviors. Thirty undergraduates completed two sessions of a virtual reconnaissance mission. During each session, they received 10 alerts about nearby opposing forces. They indicated trust or distrust of each alert, and subsequently identified the avatar as a friend or a foe. Results indicated that participants trusted more historically reliable alerts, and that they showed quicker identification behavior for visually presented alerts. Future researchers should investigate the match between modality and threat presentation.

In the paper the so-called Virtual Whiteboard is presented which may be an alternative solution for modern electronic whiteboards based on electronic pens and sensors. The presented tool enables the user to write, draw and handle whiteboard contents using his/her hands only. An additional equipment such as infrared diodes, infrared cameras or cyber gloves is not needed. The user's interaction with the Virtual Whiteboard computer application is based on dynamic hand gesture recognition. Gestures are recognized in the process of analyzing video stream obtained from a webcam coupled with a multimedia projector displaying whiteboard contents. The tracking positions of hands in the image is supported by Kalman filtering. In the paper the hardware and software of the Virtual Whiteboard is presented with a special focus on utilizing Kalman filters for prediction of consecutive hand positions. For the gestures applied to handle whiteboard contents, examined efficacy of Kalman filter supported recognition and the efficacy without using the filtering is given. In addition, the results of system efficiency tests are provided.

The paper presents a new approach to hand gesture classification which may be useful in testing and monitoring patients with neurological conditions. Since applying gesture recognition based on static image processing may easily fail when it comes to work with patients with neurological disorders, it is crucial to convert static masks into dynamic 3-dimensional geometrical model. The system being developed is meant to be used by patients with Parkinson Disease (PD). Three tests based on UPDRS (Unified Parkinson's Disease Rating Scale) are envisioned to be performed by a patient with the use of the system, i.e.: finger tapping (test No. 23), hand movements (test No. 24) and rapid alternating hand movements (test No. 25). In this concept presentation the movement interpolation curves based on various parameters are to be used as an input to the fuzzy logic classifier. In conclusion the aim of this research is presented and the approach advantages and disadvantages are shown and discussed.

An algorithm for real-time speech stretching is presented. It was designed to modify input signal dependently on its content and on its relation with the historical input data. The proposed algorithm is a combination of speech signal analysis algorithms, i.e. voice, vowels/consonants, stuttering detection and SOLA (Synchronous-Overlap-and-Add) based speech stretching algorithm. This approach enables stretching input speech signal in real-time with high quality and provides “global” synchronization of the input and output signals. Finally, the effectiveness of the engineered algorithms as well as the quality of the processed speech are discussed.