Introduction. Development of a robotic arm that can be operated using an exoskeletal position sensing harness as well as a dry electrode brain-computer interface headset. Design priorities comprise an intuitive and immersive user interface, fast and smooth movement, portability, and cost minimization. Materials and Methods. A robotic arm prototype capable of moving along 6 degrees of freedom has been developed, along with an exoskeletal position sensing harness which was used to control it. Commercially available dry electrode BCI headsets were evaluated. A particular headset model has been selected and is currently being integrated into the hybrid system. Results and Discussion. The combined arm-harness system has been successfully tested and met its design targets for speed, smooth movement, and immersive control. Initial tests verify that an operator using the system can perform pick and place tasks following a rather short learning curve. Further evaluation experiments are planned for the integrated BCI-harness hybrid setup. Conclusions. It is possible to design a portable robotic arm interface comparable in size, dexterity, speed, and fluidity to the human arm at relatively low cost. The combined system achieved its design goals for intuitive and immersive robotic control and is currently being further developed into a hybrid BCI system for comparative experiments.

Life-long learning is currently being embraced as a central process that could disrupt traditional educational paths. Apparently, the (ideal) type of learning often promoted is deep and meaningful learning, though it is not always required to be so. Deep learning goes beyond superficial knowledge assimilation of unlinked facts; it aims at developing deep disciplinary understanding, transformative knowledge, personal meaning, emotional intelligence, critical thinking, creativity and metacognitive skills. Meaningful learning occurs when learning is active, constructive, intentional, authentic, and cooperative. Technology enhanced teaching and learning methods should prove their potential to transform life-long learning provision and facilitate the achievement of deep and meaningful learning. In the context of distance education in life-long learning, one important challenge is the design of versatile quality assurance strategies for e-training. Based on the experiences in U P E C L -Long Learning (KEDIVIM) the authors present how the principles and attributes of deep and meaningful learning can be combined with project management in practice and be incorporated in an e-Learning quality strategy. We present i) the methods used to assess the quality of the e-Learning programmes, ii) key findings of the evaluation process and iii) first research evaluation results on the quality of learning. This research study on learning process quality was conducted by learning methods such as collaborative learning. Some results of the evaluation indicate that the e-Learning quality strategy led to e-L deep and meaningful learning.

Abstract-This paper presents the development, pilot testing and user assessment results for a body-machine interface (BMI) designed to control a 6-degree of freedom robotic arm, developed by our research team. The BMI was designed to be wearable, immersive and intuitive, constituting the first part of a hybrid real-time user interface. A total of 34 volunteers participated in this study, performing two sets of three tasks in which they controlled the robotic arm, a) within direct line of sight and b) through a video link. All participants completed questionnaires to evaluate their technological background, familiarization with informatics, electronics, robotics and video teleconferencing. At this point of development the system does not capture brainwaves or electric neural input, it simply captures the motion of the operator's arm. The complete MERCURY prototype system is still under development and additionally comprises a wearable, wireless brain-computer interface (BCI) headset. The BCI headset is currently being integrated into the system and has not yet been pilot tested. The complete hybrid-interface system is primarily intended for research into human-computer interfaces, neurophysiological experiments, as well as industrial applications requiring immersive remote control of robotic machinery.