Social skills as predictors of communication, performance and quality of collaboration in project-based learning

The assumption that social skills are necessary ingredients of collaborative learning is well established but rarely empirically tested. In addition, most theories on collaborative learning focus on social skills only at the personal level, while the social skill configurations within a learning group might be of equal importance. Using the integrative framework, this study investigates which social skills at the personal level and at the group level are predictive of task-related e-mail communication, satisfaction with performance and perceived quality of collaboration. Data collection took place in a technology-enhanced long-term project-based learning setting for pre-service teachers. For data collection, two questionnaires were used, one at the beginning and one at the end of the learning cycle which lasted 3 months. During the project phase, the e-mail communication between group members was captured as well. The investigation of 60 project groups (N = 155 for the questionnaires; group size: two or three students) and 33 groups for the e-mail communication (N = 83) revealed that personal social skills played only a minor role compared to group level configurations of social skills in predicting satisfaction with performance, perceived quality of collaboration and communication behaviour. Members from groups that showed a high and/or homogeneous configuration of specific social skills (e.g., cooperation/compromising, leadership) usually were more satisfied and saw their group as more efficient than members from groups with a low and/or heterogeneous configuration of skills.

The InterHerz project--a web-based psychological treatment for cardiac patients with depression: study protocol of a randomized controlled trial

Patients with heart disease often suffer from difficulties in psychological adaptation during cardiac rehabilitation. Mood disorders such as depression are known to be highly prevalent in cardiac patients and to have a negative impact on the progression of coronary heart disease. However, cardiac patients have difficulties to get psychological treatments due to low availability and motivational difficulties. Web-based interventions have been proven to be effective in treating depressive symptoms. Deprexis is a promising web-based psychological treatment which was devised for depressed patients. The aim of the study InterHerz is to examine if Deprexis is an effective psychological treatment to reduce stress and depression in cardiac patients.

Design-based stereology to quantify structural properties of artificial and natural snow using thin sections

The quantification of the structural properties of snow is traditionally based on model-based stereology. Model-based stereology requires assumptions about the shape of the investigated structure. Here, we show how the density, specific surface area, and grain boundary area can be measured using a design-based method, where no assumptions about structural properties are necessary. The stereological results were also compared to X-ray tomography to control the accuracy of the method. The specific surface area calculated with the stereological method was 19.8 ± 12.3% smaller than with X-ray tomography. For the density, the stereological method gave results that were 11.7 ± 12.1% larger than X-ray tomography. The statistical analysis of the estimates confirmed that the stereological method and the sampling used are accurate. This stereological method was successfully tested on artificially produced ice beads but also on several snow types. Combining stereology and polarisation microscopy provides a good estimate of grain boundary areas in ice beads and in natural snow, with some limitatio

Design-based stereology: Planning, volumetry and sampling are crucial steps for a successful study

Quantitative data obtained by means of design-based stereology can add valuable information to studies performed on a diversity of organs, in particular when correlated to functional/physiological and biochemical data. Design-based stereology is based on a sound statistical background and can be used to generate accurate data which are in line with principles of good laboratory practice. In addition, by adjusting the study design an appropriate precision can be achieved to find relevant differences between groups. For the success of the stereological assessment detailed planning is necessary. In this review we focus on common pitfalls encountered during stereological assessment. An exemplary workflow is included, and based on authentic examples, we illustrate a number of sampling principles which can be implemented to obtain properly sampled tissue blocks for various purposes.

Social Learning Processes in Swiss Soil Protection? The 'From Farmer - To Farmer' Project

Social learning approaches have become a prominent focus in studies related to sustainable agriculture. In order to better understand the potential of social learning for more sustainable development, the present study assessed the processes, effects and facilitating elements of interaction related to social learning in the context of Swiss soil protection and the innovative ‘From Farmer - To Farmer’ project. The study reveals that social learning contributes to fundamental transformations of patterns of interactions. However, the study also demonstrates that a learning-oriented understanding of sustainable development implies including analysis of the institutional environments in which the organizations of the individual representatives of face-to-face-based social learning processes are operating. This has shown to be a decisive element when face-to-face-based learning processes of the organisations’ representatives are translated into organisational learning. Moreover, the study revealed that this was achieved not directly through formalisation of new lines of institutionalised cooperation but by establishing links in a ‘boundary space’ trying out new forms of collaboration, aiming at social learning and co-production of knowledge. It is argued that further research on social learning processes should give greater emphasis to this intermediary level of ‘boundary spaces’.

The PRO-AGE study: an international randomised controlled study of health risk appraisal for older persons based in general practice

BACKGROUND: This paper describes the study protocol, the recruitment, and base-line data for evaluating the success of randomisation of the PRO-AGE (PRevention in Older people-Assessment in GEneralists' practices) project. METHODS/DESIGN: A group of general practitioners (GPs) in London (U.K.), Hamburg (Germany) and Solothurn (Switzerland) were trained in risk identification, health promotion, and prevention in older people. Their non-disabled older patients were invited to participate in a randomised controlled study. Participants allocated to the intervention group were offered the Health Risk Appraisal for Older Persons (HRA-O) instrument with a site-specific method for reinforcement (London: physician reminders in electronic medical record; Hamburg: one group session or two preventive home visits; Solothurn: six-monthly preventive home visits over a two-year period). Participants allocated to the control group received usual care. At each site, an additional group of GPs did not receive the training, and their eligible patients were invited to participate in a concurrent comparison group. Primary outcomes are self-reported health behaviour and preventative care use at one-year follow-up. In Solothurn, an additional follow-up was conducted at two years. The number of older persons agreeing to participate (% of eligible persons) in the randomised controlled study was 2503 (66.0%) in London, 2580 (53.6%) in Hamburg, and 2284 (67.5%) in Solothurn. Base-line findings confirm that randomisation of participants was successful, with comparable characteristics between intervention and control groups. The number of persons (% of eligible) enrolled in the concurrent comparison group was 636 (48.8%) in London, 746 (35.7%) in Hamburg, and 1171 (63.0%) in Solothurn. DISCUSSION: PRO-AGE is the first large-scale randomised controlled trial of health risk appraisal for older people in Europe. Its results will inform about the effects of implementing HRA-O with different methods of reinforcement.

Spatio-temporal credit assignment in population learning

Learning by reinforcement is important in shaping animal behavior, and in particular in behavioral decision making. Such decision making is likely to involve the integration of many synaptic events in space and time. However, using a single reinforcement signal to modulate synaptic plasticity, as suggested in classical reinforcement learning algorithms, a twofold problem arises. Different synapses will have contributed differently to the behavioral decision, and even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike-time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward, but also by a population feedback signal. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference (TD) based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task, the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second task involves an action sequence which is itself extended in time and reward is only delivered at the last action, as it is the case in any type of board-game. The third task is the inspection game that has been studied in neuroeconomics, where an inspector tries to prevent a worker from shirking. Applying our algorithm to this game yields a learning behavior which is consistent with behavioral data from humans and monkeys, revealing themselves properties of a mixed Nash equilibrium. The examples show that our neuronal implementation of reward based learning copes with delayed and stochastic reward delivery, and also with the learning of mixed strategies in two-opponent games.

Spatio-Temporal Credit Assignment in Neuronal Population Learning

n learning from trial and error, animals need to relate behavioral decisions to environmental reinforcement even though it may be difficult to assign credit to a particular decision when outcomes are uncertain or subject to delays. When considering the biophysical basis of learning, the credit-assignment problem is compounded because the behavioral decisions themselves result from the spatio-temporal aggregation of many synaptic releases. We present a model of plasticity induction for reinforcement learning in a population of leaky integrate and fire neurons which is based on a cascade of synaptic memory traces. Each synaptic cascade correlates presynaptic input first with postsynaptic events, next with the behavioral decisions and finally with external reinforcement. For operant conditioning, learning succeeds even when reinforcement is delivered with a delay so large that temporal contiguity between decision and pertinent reward is lost due to intervening decisions which are themselves subject to delayed reinforcement. This shows that the model provides a viable mechanism for temporal credit assignment. Further, learning speeds up with increasing population size, so the plasticity cascade simultaneously addresses the spatial problem of assigning credit to synapses in different population neurons. Simulations on other tasks, such as sequential decision making, serve to contrast the performance of the proposed scheme to that of temporal difference-based learning. We argue that, due to their comparative robustness, synaptic plasticity cascades are attractive basic models of reinforcement learning in the brain.

Service-Centric Networking

Content-centric networking is a novel paradigm for the Future Internet that treats content as a first class citizen. This paper argues that content-centric networking should be generalized towards a service-centric networking scheme. We propose a service-centric networking design based on an object-oriented approach, in which content and services are considered objects. We show implementation architectures for example services and how these can benefit from service-oriented networking.

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.

Estimating and quantifying uncertainties on level sets using the Vorob'ev expectation and deviation with Gaussian process models

Several methods based on Kriging have recently been proposed for calculating a probability of failure involving costly-to-evaluate functions. A closely related problem is to estimate the set of inputs leading to a response exceeding a given threshold. Now, estimating such a level set—and not solely its volume—and quantifying uncertainties on it are not straightforward. Here we use notions from random set theory to obtain an estimate of the level set, together with a quantification of estimation uncertainty. We give explicit formulae in the Gaussian process set-up and provide a consistency result. We then illustrate how space-filling versus adaptive design strategies may sequentially reduce level set estimation uncertainty.

An adjustable focusing system for a 2 MeV H- ion beam line based on permanent magnet quadrupoles

A compact adjustable focusing system for a 2 MeV H- RFQ Linac is designed, constructed and tested based on four permanent magnet quadrupoles (PMQ). A PMQ model is realised using finite element simulations, providing an integrated field gradient of 2.35 T with a maximal field gradient of 57 T/m. A prototype is constructed and the magnetic field is measured, demonstrating good agreement with the simulation. Particle track simulations provide initial values for the quadrupole positions. Accordingly, four PMQs are constructed and assembled on the beam line, their positions are then tuned to obtain a minimal beam spot size of (1.2 x 2.2) mm^2 on target. This paper describes an adjustable PMQ beam line for an external ion beam. The novel compact design based on commercially available NdFeB magnets allows high flexibility for ion beam applications.