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This paper presents some ideas of how to use Web Services
for the implementation of innovative collaborative technologies. A major goal here is the idea to build re-usable collaborative software components to foster knowledge exchange and learning. This paper describes two examples of how we used Web Services to achieve this goal. The first example we will describe implements a digital notice board with large, public displays. Here, we used web service to provide flexible data access. Web services provide the possibility to use our infrastructure with different programming languages and devices. The second example we will present is an application that enables students to construct and
model experiments descriptions using a control plant-growth system, the biotube, remotely via Web Services.
In recent years, hardware for the production and consumption of virtual reality content has reached level of prices that make it affordable to everyone. Accordingly schools and universities are showing increased interest in implementations of virtual reality technologies for supporting their innovative educational activities. Hence, this paper presents a flexible architecture for supporting the development of virtual reality learning scenarios conveniently deployed for educational purposes. We also suggest an example of such
educational scenario for medical purposes deployable with the suggested architecture. In addition, we developed and used a questionnaire answered by 17 medical students in order to derive additional requirements for refining such scenarios. Then, we present these efforts while aiming at deployments usable also for additional domains. Finally, we summarize and mention aspects we will address
in our coming efforts while deploying such activities.
In recent years, teachers have started to conduct pedagogical activities to promote different kinds of learning interactions supported by rich media. The deployment of such activities is rapidly increasing, as teachers and students own technological means that allow supporting them along such interactions. These activities can be carried out in traditional classroom settings while using regular computers. Additionally, they can also be conducted from anywhere at any time while using smartphones and tablets. In this paper, we describe a pedagogical activity requiring students to author and later peer- assess learning interactions
incorporated to videos in YouTube. We describe EDU.Tube, an environment that enables them to create, share and consume such rich media learning activities across a variety of devices. We then detail a plan for the implementation of an activity that took place in 3 different classes dealing with diverse materials addressing computer science related topics. Finally, we also
provide an evaluation presenting students' insights and feedbacks resulting from the experienced activity. We discuss and analyze these outcomes in order to elaborate on them as concerns that could be applied for the further deployment of the EDU.Tube environment.
Nowadays, teachers and students utilize different ICT devices for conducting innovative and educational activities from anywhere at any time. The enactment of these activities relies on robust communication and computational infrastructures used for supporting technological devices enabling better accessibility to educational resources and pedagogical scaffolds, wherever and whenever necessary. In this paper, we present EDU.Tube: an interactive environment that relies on web and mobile solutions offered to teachers and students for authoring and incorporating educational interactions at specific moments along the time line of occasional YouTube video-clips. The teachers and students could later experience these authored artefacts while interacting from their stationary or mobile devices. We describe our efforts related to the design, deployment and evaluation of an educational activity supported by the EDU.Tube environment. Furthermore, we illustrate the specific teachers’ and students’ efforts practiced along the different phases of this educational activity. The evaluation of this activity and results are presented, followed by a discussion of these findings, as well as some recommendations for future research efforts further elaborating on EDU.Tube’s aspects in relation to learning analytics.
In this paper we describe our efforts to foster educational interoperability in scenarios using mobile and wireless technologies to support hands-on scientific experimentation and learning. A special focus is given to the idea that innovative uses of mobile and wireless technologies enhance the learners' scientific experience. Specific contributions include the creation of new applications to support interoperability between different mobile devices, thus to provide "glue" between different learning situations. We describe a number of educational scenarios as well as the technologies and the architectural principles behind them.
Mobile devices, in the form of smartphones, are endowed with rich capabilities in terms of multimedia, sensors and connectivity. The wide adoption of these devices allows using them across different settings and situations. One area in which mobile devices become more and more prominent is within the field of mobile learning. Here, mobile devices provide rich possibilities for the contextualization of the learner, by using the set of sensors available in the device. On the one hand, the usage of mobile devices enables participation in learning activities independent of time and space. Nevertheless, developing mobile learning applications for the heterogeneity of mobile devices available in the market becomes a challenge. Not only this is a problem related to form factor aspects, but also the large number of different operating systems, platforms and app infrastructures (app stores) are aspects to be considered. In this paper we present our initial efforts with regard to the development of cross-platform mobile applications to support the contextualization of learning content.
In this paper we present an approach for People-to-People recommendations based on a Rich Context Model (RCM). We consider personal user information as contextual information used for our recommendations. The evaluation of our recommendation approach was performed on a social network of students. The obtained results do show a significant increase in performance while, at the same time, a slight increase in quality in comparison to a manual matching process. The proposed approach is flexible enough to handle different data types of contextual information and easy adaptable to other recommendation domains.
Recommender systems have become an important application domain related to the development of personalized mobile services. Thus, various recommender mechanisms have been developed for filtering and delivering relevant information to mobile users. This paper presents a rich context model to provide the relevant content of news to the current context of mobile users. The proposed rich context model allows not only providing relevant news with respect to the user’s current context but, at the same time, also determines a convenient representation format of news suitable for mobile devices.
In this paper we present an approach for contextual big data analytics in social networks, particularly in Twitter. The combination of a Rich Context Model (RCM) with machine learning is used in order to improve the quality of the data mining techniques. We propose the algorithm and architecture of our approach for real-time contextual analysis of tweets. The proposed approach can be used to enrich and empower the predictive analytics or to provide relevant context-aware recommendations.
This chapter describes our current research efforts related to the contextualization of learners in mobile learning activities. Substantial research in the field of mobile learning has explored aspects related to contextualized learning scenarios. However, new ways of interpretation and consideration of contextual information of mobile learners are necessary. This chapter provides an overview regarding the state of the art of innovative approaches for supporting contextualization in mobile learning. Additionally, we provide the description of the design and implementation of a flexible multi-dimensional vector space model to organize and process contextual data together with visualization tools for further analysis and interpretation. We also present a study with outcomes and insights on the usage of the contextualization support for mobile learners. To conlcude, we discuss the benefits of using contextualization models for learners in different use-cases. Moreover, a description is presented in order to illustrate how the proposed contextual model can easily be adapted and reused for different use-cases in mobile learning scenarios and potentially other mobile fields.
This chapter describes our research efforts related to the design of mobile learning (m-learning) applications in cloud-computing (CC) environments. Many cloud-based services can be used/integrated in m-learning scenarios, hence, there is a rich source of applications that could easily be applied to design and deploy those within the context of cloud-based services. Here, we present two cloud-based approaches—a flexible framework for an easy generation and deployment of mobile learning applications for teachers, and a flexible contextualization service to support personalized learning environment for mobile learners. The framework provides a flexible approach that supports teachers in designing mobile applications and automatically deploys those in order to allow teachers to create their own m-learning activities supported by mobile devices. The contextualization service is proposed to improve the content delivery of learning objects (LOs). This service allows adapting the learning content and the mobile user interface (UI) to the current context of the user. Together, this leads to a powerful and flexible framework for the provisioning of potentially ad hoc mobile learning scenarios. We provide a description of the design and implementation of two proposed cloud-based approaches together with scenario examples. Furthermore, we discuss the benefits of using flexible and contextualized cloud applications in mobile learning scenarios. Hereby, we contribute to this growing field of research by exploring new ways for designing and using flexible and contextualized cloud-based applications that support m-learning.
This paper describes the design and development stages of a web-based framework, aiming to support the creation of mobile applications within the context of mobile learning. The suggested approach offers the opportunity to deploy and execute these applications on mobile devices. This web-based solution additionally offers the possibility to visualize the data collected by the mobile applications in a web-browser. Despite previous research efforts carried out in this domain, few of the projects have addressed these processes from a purely web-based perspective. Currently, a prototype of an authoring tool for creating mobile data collection applications is already implemented. In order to integrate and validate this solution in everyday educational settings, we are collaborating with a network of high schools. On the basis of workshops with teachers we will carry out, refinements and requirements for further enhancements will be collected and will be used to guide our coming efforts.
This paper presents a web-based framework that allows the creation and deployment of mobile learning activities. We present an authoring tool that allows not-technically skilled persons to design mobile learning tasks and deploy them as a web-based mobile application. Since the presented approach is based exclusively on web-technologies, the deployed mobile application can be executed via a mobile browser and therefore is platform independent. Despite previous research efforts carried out in this domain, few of the projects have addressed this course of actions from a purely web-based perspective. Through the latest development of web technologies, mobile applications have access to internal sensors like camera, microphone and GPS and therefore allow data collection within web-applications. In order to validate whether the proposed framework can be applied in educational settings, we conducted a pilot study with experienced teachers and present the results of these efforts in this paper.
This paper discusses the efforts carried out related to the design and development of a web-based framework that allows designing, deploying and executing mobile data collecting applications. Furthermore, it also allows analyzing and presenting the data that is generated during the mentioned process. The fact that the framework is completely web-based provides a platform independent execution of the mobile application on any mobile device with a web-browser. As a result that the whole life-cycle of creating, executing and discussing a mobile learning activity is implemented in pure web-based manner separates this work from similar efforts. In the course of this work, the current state of development of two of the components, the authoring tool and the mobile application is presented. This framework was introduced to teachers in an activity to follow up an initial study. On the basis of a workshop with teachers, we performed an explorative study regarding the technology acceptance and usability of two components of the proposed framework. The results are discussed and analyzed in this paper.
The continuous evolution of learning technologies combined with the changes within ubiquitous learning environments in which they operate result in dynamic and complex requirements that are challenging to meet. The fact that these systems evolve over time makes it difficult to adapt to the constant changing requirements. Existing approaches in the field of Technology Enhanced Learning (TEL) are generally not addressing those issues and they fail to adapt to those dynamic situations. In this chapter, we investigate the notion of an adaptive and adaptable architecture as a possible solution to address these challenges. We conduct a literature survey upon the state of the art and state of practice in this area. The outcomes of those efforts result in an initial model of a Domain-specific architecture to tackle the issues of adaptability and adaptiveness. To illustrate these ideas, we provide a number of scenarios where this architecture can be applied or is already applied. Our proposed approach serves as a foundation for addressing future ubiquitous learning applications where new technologies constantly emerge and new requirements evolve.