An evaluation of scaffolding for virtual interactive tutorials

Scaffolding refers to a temporary support framework used during construction. Applied to teaching and learning it describes measures to support a learner to become confident and self-reliant in a subject. In a Web environment scaffolding features need to replace the instructor. We discuss our approach to Web-based scaffolding based on the cognitive apprenticeship and activity theories. We suggest a set of four scaffold types that have made our scaffolding-supported virtual interactive tutorial successful. We present a novel evaluation approach for virtual tutorials that is embedded into an iterative, evolutionary instructional design

Towards modeling complex robot training tasks through system identification

Previous research has shown that sensor-motor tasks in mobile robotics applications can be modelled automatically, using NARMAX system identi�cation, where the sensory perception of the robot is mapped to the desired motor commands using non-linear polynomial functions, resulting in a tight coupling between sensing and acting | the robot responds directly to the sensor stimuli without having internal states or memory. However, competences such as for instance sequences of actions, where actions depend on each other, require memory and thus a representation of state. In these cases a simple direct link between sensory perception and the motor commands may not be enough to accomplish the desired tasks. The contribution to knowledge of this paper is to show how fundamental, simple NARMAX models of behaviour can be used in a bootstrapping process to generate complex behaviours that were so far beyond reach. We argue that as the complexity of the task increases, it is important to estimate the current state of the robot and integrate this information into the system identification process. To achieve this we propose a novel method which relates distinctive locations in the environment to the state of the robot, using an unsupervised clustering algorithm. Once we estimate the current state of the robot accurately, we combine the state information with the perception of the robot through a bootstrapping method to generate more complex robot tasks: We obtain a polynomial model which models the complex task as a function of predefined low level sensor motor controllers and raw sensory data. The proposed method has been used to teach Scitos G5 mobile robots a number of complex tasks, such as advanced obstacle avoidance, or complex route learning

Automated tutoring for a database skills training environment

Universities are increasingly offering courses online. Feedback, assessment, and guidance are important features of this online courseware. Together, in the absence of a human tutor, they aid the student in the learning process. We present a programming training environment for a database course. It aims to offer a substitute for classroom based learning by providing synchronous automated feedback to the student, along with guidance based on a personalized assessment. The automated tutoring system should promote procedural knowledge acquisition and skills training. An automated tutoring feature is an integral part of this tutoring system

Towards adaptive multi-robot systems: self-organization and self-adaptation

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible

An ontology of agile aspect oriented software development

Both agile methods and aspect oriented programming (AOP) have emerged in recent years as new paradigms in software development. Both promise to free the process of building software systems from some of the constraints of more traditional approaches. As a software engineering approach on the one hand, and a software development tool on the other, there is the potential for them to be used in conjunction. However, thus far, there has been little interplay between the two. Nevertheless, there is some evidence that there may be untapped synergies that may be exploited, if the appropriate approach is taken to integrating AOP with agile methods. This paper takes an ontological approach to supporting this integration, proposing ontology enabled development based on an analysis of existing ontologies of aspect oriented programming, a proposed ontology of agile methods, and a derived ontology of agile aspect oriented development