Requirements for the use of virtual worlds in corporate training : perspectives from the post-mortem of a corporate e-learning provider approach of Second Life and OpenSimulator

Between 2009 and 2011, a joint academia-industry effort took place to integrate Second Life and OpenSimulator platforms into a corporate elearning provider’s learning management platform. The process involved managers and lead developers at the provider and an academic engineering research team. We performed content analysis on the documents produced in this process, seeking data on the corporate perspective of requirements for virtual world platforms to be usable in everyday practice. In this paper, we present the requirements found in the documents, and detail how they emerged and evolved throughout the process.

Studies of CMS data access patterns with machine learning techniques

This thesis presents a study of the Grid data access patterns in distributed analysis in the CMS experiment at the LHC accelerator. This study ranges from the deep analysis of the historical patterns of access to the most relevant data types in CMS, to the exploitation of a supervised Machine Learning classification system to set-up a machinery able to eventually predict future data access patterns - i.e. the so-called dataset “popularity” of the CMS datasets on the Grid - with focus on specific data types. All the CMS workflows run on the Worldwide LHC Computing Grid (WCG) computing centers (Tiers), and in particular the distributed analysis systems sustains hundreds of users and applications submitted every day. These applications (or “jobs”) access different data types hosted on disk storage systems at a large set of WLCG Tiers. The detailed study of how this data is accessed, in terms of data types, hosting Tiers, and different time periods, allows to gain precious insight on storage occupancy over time and different access patterns, and ultimately to extract suggested actions based on this information (e.g. targetted disk clean-up and/or data replication). In this sense, the application of Machine Learning techniques allows to learn from past data and to gain predictability potential for the future CMS data access patterns. Chapter 1 provides an introduction to High Energy Physics at the LHC. Chapter 2 describes the CMS Computing Model, with special focus on the data management sector, also discussing the concept of dataset popularity. Chapter 3 describes the study of CMS data access patterns with different depth levels. Chapter 4 offers a brief introduction to basic machine learning concepts and gives an introduction to its application in CMS and discuss the results obtained by using this approach in the context of this thesis.

Improving Resource Management in Virtualized Data Centers using Application Performance Models

The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity. We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.

E-learning ABC

Ma már nagyon sokan találkoznak az e-learning kifejezéssel, azonban a mögé képzelt tartalom egyénenként eltérő lehet: az e-learning gyors fejlődése és térnyerése következtében rengeteg új fogalom alakult ki és terjedt el, melyek definíciója korántsem egységes, megnehezítve az eligazodást még a szakemberek számára is. Ennek feloldása fontos feladat: a cikk elsősorban e fogalmakat igyekszik tisztázni a nemzetközi szakirodalom széles körű áttekintésével, az egyes szerzők különböző megközelítéseit alapul véve és összevetve. Az alapvető fogalmak definiálásán túl a szerző meghatározza az e-learning összetevőit (rendszer, résztvevők és tartalom) és azok jellemzőit. Végezetül példákon keresztül mutatja be az e-learning lehetséges alkalmazási területeit és az ezekhez tartozó specifikus elemeket, ezzel kontextusba helyezve a laikusok számára is az e-learningben rejlő lehetőségeket, és a gyakorlatban már alkalmazott megoldásokat. A cikk végén rövid kitekintést tesz azokra a kihívásokra, amelyek az e-learning megjelenésével bukkannak fel az oktatás területén.

From the workplace to the classroom:examining the impact of self-leadership learning strategies on higher educational attainment and success

Self-leadership is a concept from the organisational and management literature broadly combining processes of self-goal setting, self-regulation and self-motivation. Research has typically focused on the impact of self-leadership on work performance outcomes, with little attention to potential benefits for learning and development. In this paper, we employ a longitudinal design to examine the association of a number of processes of self-leadership with higher educational attainment in a sample of business students (N = 150). Self-reported use of strategies related to behavioural, cognitive and motivational aspects of self-leadership were measured in the first semester of the academic year, and correlated with end-of year grade point average. We found that in particular, self-goal setting, pro-active goal-related behaviour, behaviour regulation and direction, motivational awareness, and optimism were all significant predictors of educational attainment. We discuss implications for educational research and for teachers and tutors in practice.

Geometrical Methods in Multivariate Risk Management: Algorithms and Applications

This thesis builds a framework for evaluating downside risk from multivariate data via a special class of risk measures (RM). The peculiarity of the analysis lies in getting rid of strong data distributional assumptions and in orientation towards the most critical data in risk management: those with asymmetries and heavy tails. At the same time, under typical assumptions, such as the ellipticity of the data probability distribution, the conformity with classical methods is shown. The constructed class of RM is a multivariate generalization of the coherent distortion RM, which possess valuable properties for a risk manager. The design of the framework is twofold. The first part contains new computational geometry methods for the high-dimensional data. The developed algorithms demonstrate computability of geometrical concepts used for constructing the RM. These concepts bring visuality and simplify interpretation of the RM. The second part develops models for applying the framework to actual problems. The spectrum of applications varies from robust portfolio selection up to broader spheres, such as stochastic conic optimization with risk constraints or supervised machine learning.

Healthcare Computer Reasoning Addressing Chronically Ill Societies Using IoT: Deep Learning AI to the Rescue of Home-Based Healthcare

The authors present a proposal to develop intelligent assisted living environments for home based healthcare. These environments unite the chronical patient clinical history sematic representation with the ability of monitoring the living conditions and events recurring to a fully managed Semantic Web of Things (SWoT). Several levels of acquired knowledge and the case based reasoning that is possible by knowledge representation of the health-disease history and acquisition of the scientific evidence will deliver, through various voice based natural interfaces, the adequate support systems for disease auto management but prominently by activating the less differentiated caregiver for any specific need. With these capabilities at hand, home based healthcare providing becomes a viable possibility reducing the institutionalization needs. The resulting integrated healthcare framework will provide significant savings while improving the generality of health and satisfaction indicators.

Comparison of Explicit and Implicit Methods of Cross-Cultural Learning in an International Classroom

The paper addresses a gap in the literature concerning the difference between enhanced and not enhanced cross-cultural learning in an international classroom. The objective of the described research was to clarify if the environment of international classrooms could enhance cross-cultural competences significantly enough or if additional focus on cross-cultural learning as an explicit objective of learning activities would add substantially to the experience. The research question was defined as “how can a specific exercise focused on cross-cultural learning enhance the cross-cultural skills of university students in an international classroom?”. Surveys were conducted among interna- tional students in three leading Central-European Universities in Lithuania, Poland and Hungary to measure the increase of their cross-cultural competences. The Lithuanian and Polish classes were composed of international students and concentrated on International Management/Business topics (explicit method). The Hungarian survey was done in a general business class that just happened to be international in its composition (implicit method). Overall, our findings prove that the implicit method resulted in comparable, somewhat even stronger effectiveness than the explicit method. The study method included the analyses of students’ individual increases in each study dimension and construction of a compound measure to note the overall results. Our findings confirm the power of the international classroom as a stimulating environment for latent cross-cultural learning even without specific exercises focused on cross-cultural learning itself. However, the specific exercise did induce additional learning, especially related to cross-cultural awareness and communication with representatives of other cultures, even though the extent of that learning may be interpreted as underwhelming. The main conclusion from the study is that the diversity of the students engaged in a project provided an environment that supported cross-cultural learning, even without specific culture-focused reflections or exercises.

Information Usefulness To Support Dialogue Management in Healthcare

The main objective of the framework we are proposing is to help the physician obtain information about the patient's condition in order to reach the \emph{correct} diagnosis as soon as possible. In our proposal, the number of interactions between the physician and the patient is reduced to a strict minimum on the one hand and, on the other hand, it is made possible to increase the number of questions to be asked if the uncertainty about the diagnosis persists. These advantages are due to the fact that (i) we implement a reasoning component that allows us to predict a symptom from another symptom without explicitly asking the patient, (ii) we consider non-binary values for the weights associated with the symptoms, we introduce a dataset filtering process in order to choose which partition should be used with respect to some particular characteristics of the patient, and, in addition, (iv) it was added new functionality to the framework: the ability to detect further future risks of a patient already knowing his pathology. The experimental results we obtained are very encouraging

The management of schools’ websites in Cantabria, Spain

School websites are not only sources of information and documentation, but also means of communication that are increasingly being accessed by members of society, especially by the different educational communities, thanks to the democratisation of Internet access. This paper deals with a qualitative research project in which information and communication technology coordinators of infant and primary publicly funded private schools (concertados) and state schools in urban, rural and semi-urban/rural areas within the Region of Cantabria (Spain) were interviewed in order to understand how school websites are managed. The findings show a range of views and practices in the schools’ management of their websites, some positive developments in their uses and functions, and numerous opportunities for improvement. School websites are essential communication tools, which need to be continuously improved/updated by their managers, with the support of the education authorities.

A study of the role of a technology-enhanced learning implementation group in mediating an institutional VLE minimum standards policy

Recent years have seen a focus on responding to student expectations in higher education. As a result, a number of technology-enhanced learning (TEL) policies have stipulated a requirement for a minimum virtual learning environment (VLE) standard to provide a consistent student experience. This paper offers insight into an under-researched area of such a VLE standard policy development using a case study of one university. With reference to the implementation staircase model, this study takes cue from the view that an institutional VLE template can affect lower levels directly, sidestepping the chain in the implementation staircase. The Group's activity whose remit is to design and develop a VLE template, therefore, becomes significant. The study, drawing on activity theory, explores the mediating role of such a Group. Factors of success and sources of tension are analysed to understand the interaction between the individuals and the collective agency of Group members. The paper identifies implications to practice for similar TEL development projects. Success factors identified demonstrated the importance of good project management principles, establishing clear rules and division of labour for TEL development groups. One key finding is that Group members are needed to draw on both different and shared mediating artefacts, supporting the conclusion that the nature of the group's composition and the situated expertise of its members are crucial for project success. The paper's theoretical contribution is an enhanced representation of a TEL policy implementation staircase.

Two-way text messaging: an interactive mobile learning environment in higher education

Short messaging service (SMS) is perhaps the most popular mobile technology prevalent among students in higher education due to its ubiquitous nature and the capability of two-way communication. However, a major limitation in two-way text messaging is sending back a part of received data with the reply message. This limitation results in users of a mobile learning environment being unable to reply back to the correct destination. This article presents a two-way text messaging system that can be integrated into a learning management system (LMS) to provide an interactive learning experience to the user community. Initially, a database is integrated into the LMS that holds message information such as recipient's phone number, message body and user data header. A specific port associated with the SMS is used to conceal and exchange data of a particular course unit. Subsequently, software in the student's mobile device captures this message and sends back the reply message to the appropriate course unit allowing both teachers and students to view messages sent and replies received pertaining to a particular course. Results indicate the educational impact of the proposed system in improving the learning environment and benefits it offers to the community in a campus-wide implementation.

The space for social media in structured online learning

In this paper, we explore the benefits of using social media in an online educational setting, with a particular focus on the use of Facebook and Twitter by participants in a Massive Open Online Course (MOOC) developed to enable educators to learn about the Carpe Diem learning design process. We define social media as digital social tools and environments located outside of the provision of a formal university-provided Learning Management System. We use data collected via interviews and surveys with the MOOC participants as well as social media postings made by the participants throughout the MOOC to offer insights into how participants’ usage and perception of social media in their online learning experiences differed and why. We identified that, although some participants benefitted from social media by crediting it, for example, with networking and knowledge-sharing opportunities, others objected or refused to engage with social media, perceiving it as a waste of their time. We make recommendations for the usage of social media for educational purposes within MOOCs and formal digital learning environments.

Interdisciplinary project-based learning: technology for improving student cognition

The article studies a way of enhancing student cognition by using interdisciplinary project-based learning (IPBL) in a higher education institution. IPBL is a creative pedagogic approach allowing students of one area of specialisation to develop projects for students with different academic profiles. The application of this approach in the Ural State University of Economics resulted in a computer-assisted learning system (CALS) designed by IT students. The CALS was used in an analytical chemistry course with students majoring in Commodities Management and Expertise (‘expert’ students). To test how effective the technology was, the control and experimental groups were formed. In the control group, learning was done with traditional methods. In the experimental group, it was reinforced by IPBL. A statistical analysis of the results, with an application of Pearson χ 2 test, showed that the cognitive levels in both IT and ‘expert’ experimental groups improved as compared with the control groups. The findings demonstrated that IPBL can significantly enhance learning. It can be implemented in any institution of higher or secondary education that promotes learning, including the CALS development and its use for solving problems in different subject areas.