Can You Ink While You Blink? Assessing Mental Effort in a Sensor-Based Calligraphy Trainer

Sensors can monitor physical attributes and record multimodal data in order to provide feedback. The application calligraphy trainer, exploits these affordances in the context of handwriting learning. It records the expert’s handwriting performance to compute an expert model. The application then uses the expert model to provide guidance and feedback to the learners. However, new learners can be overwhelmed by the feedback as handwriting learning is a tedious task. This paper presents the pilot study done with the calligraphy trainer to evaluate the mental effort induced by various types of feedback provided by the application. Ten participants, five in the control group and five in the treatment group, who were Ph.D. students in the technology-enhanced learning domain, took part in the study. The participants used the application to learn three characters from the Devanagari script. The results show higher mental effort in the treatment group when all types of feedback are provided simultaneously. The mental efforts for individual feedback were similar to the control group. In conclusion, the feedback provided by the calligraphy trainer does not impose high mental effort and, therefore, the design considerations of the calligraphy trainer can be insightful for multimodal feedback designers

Designing and Implementing Gamification:GaDeP, Gamifire, and applied Case Studies

Gamification aims at addressing problems in various fields such as the high dropout rates, the lack of engagement, isolation, or the lack of personalisation faced by Massive Open Online Courses (MOOC). Even though gamification is widely applied, not only in MOOCs, only few cases are meaningfully designed and empirically tested. The Gamification Design Process (GaDeP) aims to cover this gap. This article first briefly introduces GaDeP, presents the concept of meaningful gamification, and derives how it motivates the need for the Gamifire platform (as a scalable and platform-independent reference infrastructure for MOOC). Secondly, it defines the requirements for platformindependent gamification and describes the development of the Gamifire infrastructure. Thirdly we describe how Gamifire was successfully applied in four different cases. Finally, the applicability of GaDeP beyond MOOC is presented by reporting on a case study where GaDeP has been successfully applied by four student research and development projects. From both, the Gamifire cases and the GaDeP cases we derive the key contribution of this article: insights in the strengths and weaknesses of the Gamifire infrastructure as well as lessons learned about the applicability and limitations of the GaDeP framework. The paper ends detailing our future works and planned development activities

From AR to Expertise:A User Study of an Augmented Reality Training to Support Expertise Development

Augmented reality and sensor technologies have been analysed extensively in several domains including education and training. Although, varieties of use cases and applications exist, these studies were conducted in controlled laboratory environments. This paper reports on the first user study of augmented reality prototype developed to support students to learn from trainers in professional domains using augmented reality and sensors. The prototype records the performance of trainers in the first phase to support students by making it available during practice in the second phase. The performance data is made available to both the students and trainers in the third phase for reflection. A total of 142 participants which included trainers and students from three professional domains, namely 1) aircraft maintenance 2) medical imaging and 3) astronaut training, evaluated the prototype. The trainers used the prototype to record their performance while the students used the prototype to learn from the recorded performance. Participants from the three professional domains evaluated the usability of the prototype by means of a questionnaire. Randomly selected participants were also interviewed to collect their opinions and suggestion for further usability improvement. Furthermore, they also evaluated the implementation of the instructional design methods, which were identified prior in a literature review, with a brief questionnaire. The questionnaire was designed to measure the acceptance of the implementation of instructional design methods and to evaluate its adherence to the authors definition. The results of this study show that the usability of the prototype is below expected standard acceptable level. The results of the questionnaire on the implementation of the instructional design methods varied show above average acceptance levels by both the trainers and the students in the three professional domains. To conclude, the prototype shows potential to be used in different domains to support expertise development

Enhancing Crew Training for Exploration Missions: The WEKIT Experience

Training is an essential component of astronauts’ mission preparation. Every astronaut receives specific trainings for the tasks to be performed in orbit, both routine and emergency, during the two years preceding the launch. Moreover, astronauts are assigned to perform On Board Training (OBT), in order to practice and maintain a high level of proficiency, in particular for complex and emergency procedures. The astronaut training process needs to further evolve and adapt to the different conditions and requirements that come with long-duration exploration missions. Currently, the training period for an astronaut takes between 18and 24 months. Projecting this estimate on to a Mars/Moon mission with two-year duration (i.e., including the long-distance journey to Mars and back), a training period of about six years would be required, but is not feasible. In addition, today, the Ground Team continuously supports crew members while they are performing activities onboard the International Space Station (ISS). This will not be possible during a mission to Mars, since the communication between Ground and Mars is affected by a delay that can range from 8 to 20 minutes, depending on how Mars and Earth are aligned in that specific moment. The WEKIT tool introduced in this paper is expected to fill these gaps by reducing the training duration necessary and by providing support to the crew when communication with Ground is not available, increasing their autonomy. WEKIT is a research and innovation project supported by the Horizon 2020 program dedicated to developing and testing novel ways of industrial training enabled by Smart Wearable Technology (WT). The twelve partners representing academia and industry from six countries in Europe have built a new learning technology platform and unique methodology to capture expert experience and share it with trainees making industrial training more efficient, affordable and engaging. This paper describes the methodology utilized by the consortium to design the WEKIT software and hardware, its features, and the feedback obtained from the almost 200 participants who tested the prototype in ALTEC to demonstrate and assess how the learning processes can be improved in terms of effectiveness, time reduction and user perception by using the proposed methodology