Building an interactive simulator on a cloud computing platform to enhance students' understanding of computer systems

Cloud computing technologies have been widely adopted to improve the competitiveness and efficiency of core operations in many enterprises through additional computational resources and/or storage as provided on the underlying cloud platforms. Yet there are relatively few studies on how cloud computing may enhance students' understanding of a specific subject in e-learning systems. In a research project awarded by the Microsoft Research Asia, we successfully developed an interactive simulator aimed to enhance the students' understanding of essential concepts related to computer systems through live animations on a cloud computing platform. Essentially, we propose to integrate the latest technologies of cloud computing and learning objects into an efficient, flexible and interactive simulator to deliver powerful computing services for dynamic simulations of various computer systems specified as 'reactive' models of learning objects on the cloud storage. More importantly, through adopting the IEEE learning object metadata standard to represent each key concept/component in different computer systems, our proposed simulator can readily facilitate the sharing and reuse of relevant concepts for future e-learning applications. The system design and prototype implementation of our cloud-based interactive simulator is carefully considered with a thorough evaluation plan to investigate on how learners may benefit from our interactive simulator in various ways. And there are many directions for future extensions. © 2013 IEEE.published_or_final_versio

Managing a Fleet of Autonomous Mobile Robots (AMR) using Cloud Robotics Platform

In this paper, we provide details of implementing a system for managing a fleet of autonomous mobile robots (AMR) operating in a factory or a warehouse premise. While the robots are themselves autonomous in its motion and obstacle avoidance capability, the target destination for each robot is provided by a global planner. The global planner and the ground vehicles (robots) constitute a multi agent system (MAS) which communicate with each other over a wireless network. Three different approaches are explored for implementation. The first two approaches make use of the distributed computing based Networked Robotics architecture and communication framework of Robot Operating System (ROS) itself while the third approach uses Rapyuta Cloud Robotics framework for this implementation. The comparative performance of these approaches are analyzed through simulation as well as real world experiment with actual robots. These analyses provide an in-depth understanding of the inner working of the Cloud Robotics Platform in contrast to the usual ROS framework. The insight gained through this exercise will be valuable for students as well as practicing engineers interested in implementing similar systems else where. In the process, we also identify few critical limitations of the current Rapyuta platform and provide suggestions to overcome them.Comment: 14 pages, 15 figures, journal pape

Framework to Enhance Teaching and Learning in System Analysis and Unified Modelling Language

Cowling, MA ORCiD: 0000-0003-1444-1563; Munoz Carpio, JC ORCiD: 0000-0003-0251-5510Systems Analysis modelling is considered foundational for Information and Communication Technology (ICT) students, with introductory and advanced units included in nearly all ICT and computer science degrees. Yet despite this, novice systems analysts (learners) find modelling and systems thinking quite difficult to learn and master. This makes the process of teaching the fundamentals frustrating and time intensive. This paper will discuss the foundational problems that learners face when learning Systems Analysis modelling. Through a systematic literature review, a framework will be proposed based on the key problems that novice learners experience. In this proposed framework, a sequence of activities has been developed to facilitate understanding of the requirements, solutions and incremental modelling. An example is provided illustrating how the framework could be used to incorporate visualization and gaming elements into a Systems Analysis classroom; therefore, improving motivation and learning. Through this work, a greater understanding of the approach to teaching modelling within the computer science classroom will be provided, as well as a framework to guide future teaching activities

To enhance collaborative learning and practice network knowledge with a virtualization laboratory and online synchronous discussion

This work is licensed under a Creative Commons Attribution 4.0 Internatinal License.Recently, various computer networking courses have included additional laboratory classes in order to enhance students' learning achievement. However, these classes need to establish a suitable laboratory where each student can connect network devices to configure and test functions within different network topologies. In this case, the Linux operating system can be used to operate network devices and the virtualization technique can include multiple OSs for supporting a significant number of students. In previous research, the virtualization application was successfully applied in a laboratory, but focused only on individual assignments. The present study extends previous research by designing the Networking Virtualization-Based Laboratory (NVBLab), which requires collaborative learning among the experimental students. The students were divided into an experimental group and a control group for the experiment. The experimental group performed their laboratory assignments using NVBLab, whereas the control group completed them on virtual machines (VMs) that were installed on their personal computers. Moreover, students using NVBLab were provided with an online synchronous discussion (OSD) feature that enabled them to communicate with others. The laboratory assignments were divided into two parts: Basic Labs and Advanced Labs. The results show that the experimental group significantly outperformed the control group in two Advanced Labs and the post-test after Advanced Labs. Furthermore, the experimental group's activities were better than those of the control group based on the total average of the command count per laboratory. Finally, the findings of the interviews and questionnaires with the experimental group reveal that NVBLab was helpful during and after laboratory class

Exploring the Use of Virtual Worlds as a Scientific Research Platform: The Meta-Institute for Computational Astrophysics (MICA)

We describe the Meta-Institute for Computational Astrophysics (MICA), the first professional scientific organization based exclusively in virtual worlds (VWs). The goals of MICA are to explore the utility of the emerging VR and VWs technologies for scientific and scholarly work in general, and to facilitate and accelerate their adoption by the scientific research community. MICA itself is an experiment in academic and scientific practices enabled by the immersive VR technologies. We describe the current and planned activities and research directions of MICA, and offer some thoughts as to what the future developments in this arena may be.Comment: 15 pages, to appear in the refereed proceedings of "Facets of Virtual Environments" (FaVE 2009), eds. F. Lehmann-Grube, J. Sablating, et al., ICST Lecture Notes Ser., Berlin: Springer Verlag (2009); version with full resolution color figures is available at http://www.mica-vw.org/wiki/index.php/Publication

An active tangible user interface framework for teaching and learning artificial intelligence

Interactive and tangible computing platforms have garnered increased interest in the pursuit of embedding active learning pedagogies within curricula through educational technologies. Whilst Tangible User Interface (TUI) systems have successfully been developed to edutain children in various research, TUI architectures have seen limited deployment in more complex and abstract domains. In light of these limitations, this paper proposes an active TUI framework that addresses the challenges experienced in teaching and learning artificial intelligence (AI) within higher educational institutions. The proposal extends an aptly designed tabletop TUI architecture with the novel interactive paradigm of active tangible manipulatives to provide a more engaging and effective user interaction. The paper describes the deployment of the proposed TUI framework within an undergraduate laboratory session to aid in the teaching and learning of artificial neural networks. The experiment is assessed against currently adopted educational computer software and the obtained results highlight the potential of the proposed TUI framework to augment students’ gain in knowledge and understanding of abstracted threshold concepts in higher education