▶ Addresses the accessibility, usability, and, ultimately, acceptability of Information Society Technologies by anyone, anywhere, at anytime, and through any media and device. ▶ Focuses on theoretical, methodological, and empirical research, of both technological and non-technological nature. ▶ Features papers that report on theories, methods, tools, empirical results, reviews, case studies, and best-practice examples.

Universal access in the information society

Manouselis, N., Drachsler, H., Vuorikari, R., Hummel, H. G. K., & Koper, R. (2011). Recommender Systems in Technology Enhanced Learning. In P. B. Kantor, F. Ricci, L. Rokach, & B. Shapira (Eds.), Recommender Systems Handbook (pp. 387-415). Berlin: Springer.

https://www.ise.bgu.ac.il/faculty/liorr/recsyshb/chLearning.pdf

Recommender Systems in Technology Enhanced Learning

As an area, Technology Enhanced Learning (TEL) aims to design, develop and test socio-technical innovations that will support and enhance learning practices of individuals and organizations. Information retrieval is a pivotal activity in TEL and the deployment of recommender systems has attracted increased interest during the past years.Recommendation methods, techniques and systems open an interesting new approach to facilitate and support learning and teaching. The goal is to develop, deploy and evaluate systems that provide learners and teachers with meaningful guidance in order to help identify suitable learning resources from a potentially overwhelming variety of choices.Contributions address the following topics: i) user and item data that can be used to support learning recommendation systems and scenarios, ii) innovative methods and techniques for recommendation purposes in educational settings and iii) examples of educational platforms and tools where recommendations are incorporated.

Recommender Systems for Technology Enhanced Learning: Research Trends and Applications

A survey of industrial augmented reality

The increasing number of publications on recommender systems for Technology Enhanced Learning (TEL) evidence a growing interest in their development and deployment. In order to support learning, recommender systems for TEL need to consider specific requirements, which differ from the requirements for recommender systems in other domains like e-commerce. Consequently, these particular requirements motivate the incorporation of specific goals and methods in the evaluation process for TEL recommender systems. In this article, the diverse evaluation methods that have been applied to evaluate TEL recommender systems are investigated. A total of 235 articles are selected from major conferences, workshops, journals, and books where relevant work have been published between 2000 and 2014. These articles are quantitatively analysed and classified according to the following criteria: type of evaluation methodology, subject of evaluation, and effects measured by the evaluation. Results from the survey suggest that there is a growing awareness in the research community of the necessity for more elaborate evaluations. At the same time, there is still substantial potential for further improvements. This survey highlights trends and discusses strengths and shortcomings of the evaluation of TEL recommender systems thus far, thereby aiming to stimulate researchers to contemplate novel evaluation approaches.

/pdf/evaluating-recommender-systems-for-technology-enhanced-1nonqr81cj.pdf

Evaluating Recommender Systems for Technology Enhanced Learning: A Quantitative Survey

Research on how to take advantage of Augmented Reality and Virtual Reality applications and technologies in the domain of manufacturing has brought forward a great number of concepts, prototypes, and working systems. Although comprehensive surveys have taken account of the state of the art, the design space of industrial augmented and virtual reality keeps diversifying. We propose a visual approach towards assessing this space and present an interactive, community-driven tool which supports interested researchers and practitioners in gaining an overview of the aforementioned design space. Using such a framework we collected and classified relevant publications in terms of application areas and technology platforms. This tool shall facilitate initial research activities as well as the identification of research opportunities. Thus, we lay the groundwork, forthcoming workshops and discussions shall address the refinement.

The Design Space of Augmented and Virtual Reality Applications for Assistive Environments in Manufacturing: A Visual Approach

Tracking assembly processes is a necessary prerequisite to provide assistance in smart factories. In this paper, we show how to track the construction of complex components. For this we employ formal task models as background knowledge and simple sensors like RFIDs. The background knowledge is converted into a probabilistic model that actually tracks the process. As a result, we are able to provide assistance in smart factories. We discuss the performance of the approach, as well as potential applications.

Tracking Assembly Processes and Providing Assistance in Smart Factories

Information assistance helps in many application domains to structure, guide and control human work processes. However, it lacks a formalisation and automated processing of background knowledge which vice versa is required to provide ad-hoc assistance. In this paper, we describe our conceptual and technical work to include contextual background knowledge in raising awareness, guiding, and monitoring the assembly worker. We present cognitive architectures as missing link between highly sophisticated manufacturing data systems and implicitly available contextual knowledge on work procedures and concepts of the work domain. Our work is illustrated with examples in SWI-Prolog and the Soar cognitive architecture.

Information Assistance for Smart Assembly Stations

The growing complexity of manufacturing calls for new approaches to support the human workforce with situation-aware information and tools which in consequence ease the process of understanding and applying work related knowledge. With this paper we introduce a theoretical model for a systematic information transfer between assistance system and worker. It defines assistance objectives and reviews the role of artifacts during the assistance process focusing on the cognitive aspects of work. Our approach was implemented using smartwatches for application in industrial assembly environments extending the Plant@Hand manufacturing performance support system.

/pdf/follow-me-smartwatch-assistance-on-the-shop-floor-3viiykjfoc.pdf

Follow-Me: Smartwatch Assistance on the Shop Floor

Situation-aware information assistance strongly depends on the quality of available contextual background knowledge for an application domain and on its automatic processing In this paper we present a conceptual approach towards using cognitive architectures to provide information assistance and allow complex decision making based on expert knowledge We transfer our approach into a technical concept which was finally implemented as part of the Plant@Hand assembly assistance system within a mobile workshop trolley The paper gives insights into our work on formalizing knowledge and providing ad-hoc mechanisms for planning, assisting and controlling assembly tasks on the manufacturing shop floor

/pdf/the-knowledge-gap-providing-situation-aware-information-onl2qyohix.pdf

Mario Aehnelt

Papers

The Design Space of Augmented and Virtual Reality Applications for Assistive Environments in Manufacturing: A Visual Approach

Tracking Assembly Processes and Providing Assistance in Smart Factories

Information Assistance for Smart Assembly Stations

Follow-Me: Smartwatch Assistance on the Shop Floor

The Knowledge Gap: Providing Situation-Aware Information Assistance on the Shop Floor