Selver Softic

Intuitive E-Teaching by Using Combined HCI Devices: Experiences with Wiimote Applications

The wide availability of game based technologies and sophisticated e-Learning possibilities creates new demands and challenges on Human---Computer Interaction and Usability Engineering (HCI&UE). Solid research in HCI must support improvement in learning ability and creativity for both teachers and students. According to recent market surveys the Wii remote controller or Wiimote is currently more wide spread than standard Tablet PCs and is the most used computer input device worldwide. As a collection of many sensors, also including Bluetooth technology, accelerometers and IR sensors, Wiimote is of great interest for HCI experiments, especially in the area of e-Learning and e-Teaching. In this paper, we present results gained from the investigation of the potential of Wiimote as both a standard input device --- such as mouse or presenter --- and as a gesture and finger tracking sensor. We demonstrate, on the basis of examples from e-Teaching, how easily everyday gestures can be interpreted in regular computer applications utilizing Wiimotes hardware modules and some additional software modules.

Monitoring Learning Activities in PLE Using Semantic Modelling of Learner Behaviour

We report on the reflection of learning activities and revealing hidden information based on tracked user behaviour in our widget based PLE (Personal Learning Environment) at Graz University of Technology. Our reference data set includes information of more then 4000 active learners for a period of around two years. We have modelled activity and usage traces using domain specific ontologies like Activity Ontology and Learning Context Ontology from the IntelLEO EU project. Generally we distinguish three different metrics: user centric, learning object (widget) centric and activity centric. We have used Semantic Web query languages like SPARQL and representation formats like RDF to implement a human and machine readable web service along with a learning analytics dashboard for metrics visualization. The results offer a quick overview of learning habits, preferred set-ups of learning objects (widgets) and overall reflection of usages and activity dynamics in the PLE platform over time. The architecture delivers insights for intervening and recommending as closure of a learning analytics cycle[1] to optimize confidence in the PLE.

Aligning web collaboration tools with research data for scholars

Resources for research are not always easy to explore, and rarely come with strong support for identifying, linking and selecting those that can be of interest to scholars. In this work we introduce a model that uses state-of-the-art semantic technologies to interlink structured research data and data from Web collaboration tools, social media and Linked Open Data. We use this model to build a platform that connects scholars, using their profiles as a starting point to explore novel and relevant content for their research. Scholars can easily adapt to evolving trends by synchronizing new social media accounts or collaboration tools and integrate then with new datasets. We evaluate our approach by a scenario of personalized exploration of research repositories where we analyze real world scholar profiles and compare them to a reference profile.

Thought Bubbles: a conceptual prototype for a Twitter based recommender system for research 2.0

The concept of so called Thought Bubbles deals with the problem of finding appropriate new connections within Social Networks, especially Twitter. As a byproduct of exploring new users, Tweets are classified and rated and are used to generate a kind of news feed, which will extend the personal Twitter feed. Each user has several interests that can be classified by first evaluating their Tweets and then by evaluating user related and already existing contacts. By categorizing a user and related connections, one can be placed in an imaginary category specific subset of users, called Thought Bubbles. Following the trace of people who are also active within the same specific Thought Bubble, should reveal interesting and helpful connections between similar minded users.

Visualizing Collaborations and Online Social Interactions at Scientific Conferences for Scholarly Networking

The various ways of interacting with social media, web collaboration tools, co-authorship and citation networks for scientific and research purposes remain distinct. In this paper, we propose a solution to align such information. We particularly developed an exploratory visualization of research networks. The result is a scholar centered, multi-perspective view of conferences and people based on their collaborations and online interactions. We measured the relevance and user acceptance of this type of interactive visualization. Preliminary results indicate a high precision both for recognized people and conferences. The majority in a group of test-users responded positively to a set of statements about the acceptance.

Is enterprise search useful at all?: lessons learned from studying user behavior

Enterprise search is a growing industry: A recent report from the EU states the total revenue of EU-headquartered search vendors between 100 and 200 million Euros. However, enterprise search seems to be widely ignored by the academic information systems (IS) community. Little is known about user-adoption aspects of enterprise search, as almost no academic case studies and very few user evaluations are reported, leaving the topic more or less in hand of practitioners. A preliminary literature review reveals enterprise search user-aspects and especially perceived overall helpfulness as under-investigated subjects. The following paper provides insights into a qualitative study involving ten engineers from automotive and rail industry. While observing them using a piloted enterprise search engine, the authors report qualitative findings on how engineers apply enterprise search on project-relevant documents. With this paper, the authors want to contribute to the user-centered investigation of enterprise search and intranet search behavior and highlight the importance of scientific user studies in enterprise search.

Exploring barriers of enterprise search implementation: a qualitative user study

– Despite a growing demand for enterprise search from practice, little is known about its implementation from an academic perspective. As the few available practice-oriented investigations show, enterprise search user satisfaction is rather low. The purpose of this paper is therefore to explore user-centric barriers of enterprise search implementation in order to increase user satisfaction. , – Results are built on a qualitative user study in an R & D organization. Findings are gained from think-aloud observations introduced by semi-structured interviews in which ten knowledge workers explore a newly implemented enterprise search tool. , – Findings illustrate barriers that knowledge workers have to overcome when adopting enterprise search to find project-relevant documents. Implementation barriers relate to selection for keywords, search query formulation, availability and adequacy of metadata, relevance judging of search results, current search strategies, and overall perception of enterprise search usefulness. , – Limitations address the piloted enterprise search software, along with its specific configuration and scope, the chosen research approach of generating qualitative findings from a single case, and the size of the involved sample of engineers. Implications address measures to increase enterprise search adoption. , – This study provides project managers with knowledge to take appropriate actions in the early phases of enterprise search implementation, and even prior to that, to raise the success of enterprise search projects. It contributes to a better understanding of enterprise search engine user needs and assists in concretizing user requirements. , – While existing studies primarily focus on advancing the technical perspective of search in organizations, the author elaborate on the under-investigated social and organizational aspects. The author furthermore stress the importance of user-centered approaches for enterprise search adoption.

Semantically based visual tracking of engineering tasks in automotive product lifecycle

Stakeholders in specific disciplines, departments, companies and at different locations within the automotive production process save their results in different data management systems. Project management is currently done separately and does not interact with engineering objects. Our work aims on providing flexible data insights on collaboration tasks between participants within the product lifecycle. We applied semantic technologies RDF, OWL and SPARQL with a specific domain related ontology PROTARES (PROject TAsks RESources) to interlink, describe and query domain knowledge about the product. As proof of concept a software prototype is introduced, which resides on the domain ontology and allows knowledge based browsing and visualisation of specific aspects within the production process. With this example we want to demonstrate, how semantically driven customized views can support monitoring and reflection of engineering tasks and decision making within the early phases of the automotive product lifecycle.

ResXplorer : revealing relations between resources for researchers in the web of data

Recent developments on sharing research results and ideas on the Web, such as research collaboration platforms like Mendeley or ResearchGate, enable novel ways to explore research information. Current search interfaces in this field focus mostly on narrowing down the search scope through faceted search, keyword matching, or filtering. The interactive visual aspect and the focus on exploring relationships between items in the results has not sufficiently been addressed before. To facilitate this exploration, we developed ResXplorer, a search interface that interactively visualizes linked data of research-related sources. By visualizing resources such as conferences, publications and proceedings, we reveal relationships between researchers and those resources. We evaluate our search interface by measuring how it affects the search productivity of targeted lean users. Furthermore, expert users reviewed its information retrieval potential and compared it against both popular academic search engines and highly specialized academic search interfaces. The results indicate how well lean users perceive the system and expert users rate it for its main goal: revealing relationships between resources for researchers.

Finding and Exploring Commonalities between Researchers Using the ResXplorer

Researcher community produces a vast of content on the Web. We assume that every researcher interest oneself in events, persons and findings of other related community members who share the same interest. Although research related archives give access to their content most of them lack on analytic services and adequate visualizations for this data. This work resides on our previous achievements[1,2,3,4] we made on semantically and Linked Data driven search and user interfaces for Research 2.0. We show how researchers can find and visually explore commonalities between each other within their interest domain, by introducing for this matter the user interface of “ResXplorer”, and underlying search infrastructure operating over Linked Data Knowledge Base of research resources. We discuss and test most important components of “ResXplorer” relevant for detecting commonalities between researchers, closing up with conclusions and outlook for future work.