A Fast Platform for Interactive E-Learning Systems

Modern e-learning systems represent a special type of web information systems. By definition, information systems are special computerized systems used to perform data operations by multiple users simultaneously. Each active user consumes an amount of hardware resources. A shortage of hardware resources can be caused by growing number of simultaneous users. Such situation can result in overall malfunctioning or slowed-down system. In order to avoid this problem, the underlying hardware system gets usually continuously upgraded. These upgrades, typically accompanied with various software updates, usually result in a temporarily increased amount of available resources. This work deals with the problem in a different way by proposing an implementation of a web e-learning system with a modified software architecture reducing resource usage of the server part to the bare minimum. In order to implement a full-scale e-learning system that could be used as a substitute to a conventional web e-learning system, a Rich Internet Application framework was used as basis. The technology allowed implementation of advanced interactivity features and provided an easy transfer of a substantial part of the application logic from server to clients. In combination with a special server application, the server part of the new system is able to run with a reasonable performance on a hardware with very limited computing resources.

Governing individual learning in the transition phase of software maintenance offshoring: a dynamic perspective

Prior studies suggest that clients need to actively govern knowledge transfer to vendor staff in offshore outsourcing. In this paper, we analyze longitudinal data from four software maintenance offshore out-sourcing projects to explore why governance may be needed for knowledge transfer and how governance and the individual learning of vendor engineers inter-act over time. Our results suggest that self-control is central to learning, but may be hampered by low levels of trust and expertise at the outset of projects. For these foundations to develop, clients initially need to exert high amounts of formal and clan controls to enforce learning activities against barriers to knowledge sharing. Once learning activities occur, trust and expertise increase and control portfolios may show greater emphases on self-control.

Learning Software-Maintenance Tasks in the Transition Phase of Offshore Outsourcing Projects: Two Learning-Theoretical Perspectives

The increasing practice of offshore outsourcing software maintenance has posed the challenge of effectively transferring knowledge to individual software engineers of the vendor. In this theoretical paper, we discuss the implications of two learning theories, the model of work-based learning (MWBL) and cognitive load theory (CLT), for knowledge transfer during the transition phase. Taken together, the theories suggest that learning mechanisms need to be aligned with the type of knowledge (tacit versus explicit), task characteristics (complexity and recurrence), and the recipients’ expertise. The MWBL proposes that learning mechanisms need to include conceptual and practical activities based on the relative importance of explicit and tacit knowledge. CLT explains how effective portfolios of learning mechanisms change over time. While jobshadowing, completion tasks, and supportive information may prevail at the outset of transition, they may be replaced by the work on conventional tasks towards the end of transition.

Knowledge Transfer Processes in the IS Offshore Outsourcing Transition: A Conceptual Model

Despite promising cost saving potential, many offshore software projects fail to realize the expected benefits. A frequent source of failure lies in the insufficient transfer of knowledge during the transition phase. Former literature has reported cases where some domains of knowledge were successfully transferred to vendor personnel whereas others were not. There is further evidence that the actual knowledge transfer processes often vary from case to case. This raises the question whether there is a systematic relationship between the chosen knowledge transfer process and know-ledge transfer success. This paper introduces a dynamic perspective that distinguishes different types of knowledge transfer processes explaining under which circumstances which type is deemed most appropriate to successfully transfer knowledge. Our paper draws on knowledge transfer literature, the Model of Work-Based Learning and theories from cognitive psychology to show how characteristics of know-ledge and the absorptive capacity of knowledge recipients fit particular knowledge transfer processes. The knowledge transfer processes are conceptualized as combinations of generic knowledge transfer activities. This results in six gestalts of know-ledge transfer processes, each representing a fit between the characteristics of the knowledge process and the characteristics of the knowledge to be transferred and the absorptive capacity of the knowledge recipient.

Knowledge transfer in software-maintenance offshore outsourcing

Software-maintenance offshore outsourcing (SMOO) projects have been plagued by tedious knowledge transfer during the service transition to the vendor. Vendor engineers risk being over-strained by the high amounts of novel information, resulting in extra costs that may erode the business case behind offshoring. Although stakeholders may desire to avoid these extra costs by implementing appropriate knowledge transfer practices, little is known on how effective knowledge transfer can be designed and managed in light of the high cognitive loads in SMOO transitions. The dissertation at hand addresses this research gap by presenting and integrating four studies. The studies draw on cognitive load theory, attributional theory, and control theory and they apply qualitative, quantitative, and simulation methods to qualitative data from eight in-depth longitudinal cases. The results suggest that the choice of appropriate learning tasks may be more central to knowledge transfer than the amount of information shared with vendor engineers. Moreover, because vendor staff may not be able to and not dare to effectively self-manage learn-ing tasks during early transition, client-driven controls may be initially required and subsequently faded out. Collectively, the results call for people-based rather than codification-based knowledge management strategies in at least moderately specific and complex software environments.

Personalized Tuning of a Reinforcement Learning Control Algorithm for Glucose Regulation

Artificial pancreas is in the forefront of research towards the automatic insulin infusion for patients with type 1 diabetes. Due to the high inter- and intra-variability of the diabetic population, the need for personalized approaches has been raised. This study presents an adaptive, patient-specific control strategy for glucose regulation based on reinforcement learning and more specifically on the Actor-Critic (AC) learning approach. The control algorithm provides daily updates of the basal rate and insulin-to-carbohydrate (IC) ratio in order to optimize glucose regulation. A method for the automatic and personalized initialization of the control algorithm is designed based on the estimation of the transfer entropy (TE) between insulin and glucose signals. The algorithm has been evaluated in silico in adults, adolescents and children for 10 days. Three scenarios of initialization to i) zero values, ii) random values and iii) TE-based values have been comparatively assessed. The results have shown that when the TE-based initialization is used, the algorithm achieves faster learning with 98%, 90% and 73% in the A+B zones of the Control Variability Grid Analysis for adults, adolescents and children respectively after five days compared to 95%, 78%, 41% for random initialization and 93%, 88%, 41% for zero initial values. Furthermore, in the case of children, the daily Low Blood Glucose Index reduces much faster when the TE-based tuning is applied. The results imply that automatic and personalized tuning based on TE reduces the learning period and improves the overall performance of the AC algorithm.

Cognitive Interventions with Children with Special Needs - Transfer effects and multidisciplinary perspectives

Our last study with regularly developed children demonstrated a positive effect of working memory training on cognitive abilities. Building upon these findings, the aim of this multidisciplinary study is to investigate the effects of training of core functions with children who are suffering from different learning disabilities, like AD/HD, developmental dyslexia or specific language impairment. In addition to working memory training (BrainTwister), we apply a perceptual training, which concentrates on auditory-visual matching (Audilex), as well as an implicit concept learning task. We expect differential improvements of mental capacities, specifically of executive functions (working memory, attention, auditory and visual processing), scholastic abilities (language and mathematical skills), as well as of problem solving. With that, we hope to find further directions regarding helpful and individually adapted interventions in educational settings. Interested parties are invited to discuss and comment the design, the research question, and the possibilities in recruiting the subjects.

Managing Knowledge Transfer in Software-Maintenance Outsourcing Transitions: A System-Dynamics Perspective

The existing literature suggests that transitions in software-maintenance offshore outsourcing projects are prone to knowledge transfer blockades, i.e. situations in which the activities that would yield effective knowledge transfer do not occur, and that client management involvement is central to overcome them. However, the theoretical understanding of the knowledge transfer blockade is limited, and the reactive management behavior reported in case studies suggests that practitioners may frequently be astonished by the dynamics that may give rise to the blockade. Drawing on recent research from offshore sourcing and reference theories, this study proposes a system dynamics framework that may explain why knowledge transfer blockades emerge and how and why client management can overcome the blockade. The results suggest that blockades may emerge from a vicious circle of weak learning due to cognitive overload of vendor staff and resulting negative ability attributions that result in reduced helping behavior and thus aggravate cognitive load. Client management may avoid these vicious circles by selecting vendor staff with strong prior related experience. Longer phases of coexistence of vendor staff and subject matter experts and high formal and clan controls may also mitigate vicious circles.

University-industry technology transfer models: an empirical analysis

The aim of this paper is to contribute to the understanding of the underlying factors in the process of transferring technology from university to industry. Findings point to strategic importance of critical factors as the definition of common objectives, cooperation, motivation, and the elimination of technical and legal barriers. These challenges must have implications in the incorporation of cooperative aspects of research projects in the design of public innovation policies.

Cooperation in the knowledge transfer process: evidence from the demand side in Mexico

This paper presents the results of the analysis focused on scientific-technological KT in four Mexican firms and carried out by the case study approach. The analysis highlights the use of KT mechanisms as a means to obtain scientific-technological knowledge, learning, building S&T capabilities, and achieve the results of the R&D and innovation by firms.

The role of a firm's absorptive capacity and the technology transfer process in clusters: How effective are technology centres in low-tech clusters?

This paper analyses how the internal resources of small- and medium-sized enterprises determine access (learning processes) to technology centres (TCs) or industrial research institutes (innovation infrastructure) in traditional low-tech clusters. These interactions basically represent traded (market-based) transactions, which constitute important sources of knowledge in clusters. The paper addresses the role of TCs in low-tech clusters, and uses semi-structured interviews with 80 firms in a manufacturing cluster. The results point out that producer–user interactions are the most frequent; thus, the higher the sector knowledge-intensive base, the more likely the utilization of the available research infrastructure becomes. Conversely, the sectors with less knowledge-intensive structures, i.e. less absorptive capacity (AC), present weak linkages to TCs, as they frequently prefer to interact with suppliers, who act as transceivers of knowledge. Therefore, not all the firms in a cluster can fully exploit the available research infrastructure, and their AC moderates this engagement. In addition, the existence of TCs is not sufficient since the active role of a firm's search strategies to undertake interactions and conduct openness to available sources of knowledge is also needed. The study has implications for policymakers and academia.

Traditional education vs modern education. What is the impact of teaching techniques' evolution on students learning process?

The main objective of this article is to focus on the analysis of teaching techniques, ranging from the use of the blackboard and chalk in old traditional classes, using slides and overhead projectors in the eighties and use of presentation software in the nineties, to the video, electronic board and network resources nowadays. Furthermore, all the aforementioned, is viewed under the different mentalities in which the teacher conditions the student using the new teaching technique, improving soft skills but maybe leading either to encouragement or disinterest, and including the lack of educational knowledge consolidation at scientific, technology and specific levels. In the same way, we study the process of adaptation required for teachers, the differences in the processes of information transfer and education towards the student, and even the existence of teachers who are not any longer appealed by their work due which has become much simpler due to new technologies and the greater ease in the development of classes due to the criteria described on the new Grade Programs adopted by the European Higher Education Area. Moreover, it is also intended to understand the evolution of students’ profiles, from the eighties to present time, in order to understand certain attitudes, behaviours, accomplishments and acknowledgements acquired over the semesters within the degree Programs. As an Educational Innovation Group, another key question also arises. What will be the learning techniques in the future?. How these evolving matters will affect both positively and negatively on the mentality, attitude, behaviour, learning, achievement of goals and satisfaction levels of all elements involved in universities’ education? Clearly, this evolution from chalk to the electronic board, the three-dimensional view of our works and their sequence, greatly facilitates the understanding and adaptation later on to the business world, but does not answer to the unknowns regarding the knowledge and the full development of achievement’s indicators in basic skills of a degree. This is the underlying question which steers the roots of the presented research.

Learning from the living bodies: New principles and techniques for photonic sensing

Signal processing in any living being is much more complex than the one performed in artificial systems. Cortex architecture, although only partly known, gives some useful ideas to be employed in sensing technology. To analyze some of these structures is the objective of this paper. Among the points to be analyzed are the parallel transfer of information, the similarity of the different systems and the massive amount of data analyzed by physical techniques. As an example of these concepts, the possibility to transmit images in a parallel way will be reported.

Assessment of learning outcomes in computing studies

The assessment of learning outcomes is a key concept in the European Credit Transfer and Accumulation System (ECTS) since credits are awarded when the assessment shows the competences which were aimed at have been developed at an appropriate level. This paper describes a study which was first part of the project of the Bologna Experts Team-Spain and then developed as an independent study. It was carried out with the overall goal to gain experience in the assessment of learning outcomes. More specifically it aimed at 1) designing procedures for the assessment of learning outcomes related to these compulsory generic competences; 2) testing some basic psychometric features that an assessment device with some consequences for the subjects being evaluated needs to prove; 3) testing different procedures of standard setting, and 4) using assessment results as orienting feedback to students and their tutors. The process of development of tests to carry out the assessment of learning outcomes related to these competences, as well as some basic features regarding their reliability and validity is described and first results on the comparison of results achieved at two academic levels, will also be described at a later stage.

Cooperative Learning Model based on Multi-Agent Architecture for Embedded Intelligent Systems

Cooperative systems are suitable for many types of applications and nowadays these system are vastly used to improve a previously defined system or to coordinate multiple devices working together. This paper provides an alternative to improve the reliability of a previous intelligent identification system. The proposed approach implements a cooperative model based on multi-agent architecture. This new system is composed of several radar-based systems which identify a detected object and transmit its own partial result by implementing several agents and by using a wireless network to transfer data. The proposed topology is a centralized architecture where the coordinator device is in charge of providing the final identification result depending on the group behavior. In order to find the final outcome, three different mechanisms are introduced. The simplest one is based on majority voting whereas the others use two different weighting voting procedures, both providing the system with learning capabilities. Using an appropriate network configuration, the success rate can be improved from the initial 80% up to more than 90%.