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Applications and research efforts in Mobile Learning constitute a growing field in the area of Technology Enhanced Learning. However, despite a permanent increase of mobile internet accessibility and availability of mobile devices over the past years, a mobile learning environment that is easy to use, widely accepted by teachers and learners, uses widespread off-the-shelf software, and that covers various application scenarios and mobile devices, is not yet available. In this paper, we address this issue by presenting an approach and technical framework called "Mobile Contributions" ("MoCo"). MoCo supports learners to create and send contributions through various channels (including third-party solutions like Twitter, SMS and Facebook), which are collected and stored in a central repository for processing, filtering and visualization on a shared display. A set of different learning and teaching scenarios that can be realized with MoCo are described along with first experiences and insights gained from qualitative and quantitative evaluation.
This paper presents an approach towards a mobile learning environment, which is flexible in terms of supported scenarios, supported devices and input channels. The approach makes use of existing and commonly used channels like SMS, Twitter or Face book to increase acceptance and ease-of-use of mobile devices in learning scenarios. Envisaged application scenarios are described along with technical details for their realization.
Knowledge of fundamentals of human-computer interaction resp. usability engineering is getting more and more important in technical domains. However this interdisciplinary field of work and corresponding degree programs are not broadly known. Therefore at the Hochschule Ruhr West, University of Applied Sciences, a program was developed to give teen-aged pupils insights into this area in a project-based learning environment with professional tools. Within the last 18 month this project was successfully conducted several times with participants of different age.
In recent years the diversity and the ownership of mobile devices steadily increased while the prices for this kind of devices decreased to a level that allows many students to own reasonably powerful devices. As mobile devices are also being used in learning scenarios, the challenge of today is the integration of multiple heterogeneous devices into existing and upcoming learning scenarios. This paper describes an architecture that allows easy integration of various kinds of mobile and non-mobile devices. The presented architecture will be exemplified by a group discussion scenario in a heterogeneous learning environment. The paper concludes with the description of a pilot study using the described system.
The Desire project aimed at the development and implementation of a mobile service robotic research platform (technology platform) able to handle real world scenarios regarding service robotic tasks. Different modules for different tasks plus an interaction infrastructure were integrated on this platform. An example of a real world scenario task is the support of a handicapped person to clean up a kitchen in home environments.
One of the main challenges to be solved in this field is the interaction with people. To start an interaction process between a robot and a person, the most important information is the knowledge about the interacting partner’s identity and whether the interacting partner is present or not. This means, the robot must be able to detect and be finally able to identify persons. Accurate identification of specific individuals has to be done by analyzing the individual features of each person. A typical feature set that allows for a distinct identification of a specific person is often extracted from the facial image acquired by a camera. This feature-set is stored in a database to allow the identification of different persons independent from place and time by comparing given feature-sets. Thus, a face recognition module was integrated into the technology platform which includes face detection and identification algorithms.
The production and deformation of perforated sheets introduces high levels of mechanical stress into the material. In a significant fraction, such stress levels lead to crack formation in the processed sheets. Additionally, the material might be thinned and weakened in the exposed areas; these areas tend to crack at any later dates. Currently no measuring device for the detection of such material cracks or narrowing in perforated sheet metals is in practical use. Such device should be able to test the deformed circumference of the processed sheets within the very limited time of the production cycles. This paper describes the physical principles and a metrological implementation of a potential method for fast crack detection in perforated sheet metals. Even a critical material thinning - prior to the formation of a crack - can be observed. The measuring task appears to be solvable on the basis of high frequency electromagnetic fields.
Collaboration and Technology
(2012)
This book constitutes the proceedings of the 18th Collaboration Researchers' International Working Group Conference on Collaboration and Technology, held in Raesfeld, Germany, in September 2012. The 9 revised papers presented together with 12 short papers were carefully reviewed and selected from numerous submissions. They are grouped into five themes that represent collaborative learning, social media analytics, conceptual and design models, formal modeling and technical approaches and collaboration support in emergency scenarios.