Building the capacity for learning and change through reflective conversation

Conversation is central to the process of organizational learning and change. Drawing on the notion of reflective conversation, we describe an action research project, "learning through listening" in Omega, a residential healthcare organization. In this project, service users, staff, members of management committees, trustees, managers, and central office staff participated in listening to each other and in working together towards building capacity for creating their own vision of how the organization could move into the future, according to its values and ethos. In doing so they developed ways of engaging in reflective conversation that enabled progress towards a strategic direction.

Feedback von Schülerinnen und Schülern als Quelle des Lernprozesses im Praktikum von Lehramtsstudierenden

Rückmeldungen von Schülerinnen und Schülern zum Unterricht nehmen eine wichtige Rolle zur Verbesserung der Unterrichtsqualität ein. Während der Ausbildung von Lehrpersonen wird dieses Potenzial bisher aber selten genutzt. Der Beitrag stellt Ergebnisse aus dem Forschungsprojekt "Lernen im Praktikum" vor. Befragt wurden 150 Studierende des Lehramts für 7.-9. Klassen (Sekundarstufe 1) zur Bedeutung von Schülerrückmeldungen im Praktikum sowie 1331 Schülerinnen und Schüler aus Praktikumsklassen zum Praktikum und zum Lernprozess der Praktikantinnen und Praktikanten. Die Ergebnisse unterstützen einerseits die Relevanz systematischer Schülerrückmeldungen für das Lernen im Praktikum. Andererseits machen sie auf die Notwendigkeit aufmerksam, die Kriterien, die Schülerbeurteilungen zugrunde liegen, weiter zu erforschen.

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’.

Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)

The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models.

Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP)

Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.

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.

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.

Virtual Cilicia Project. How to use Google Earth as a visualization environment in an archaeological context

Over the past few years, archaeology has experienced a rapid development in geophysical prospection and remote sensing techniques. At the same time, the focus of archaeological research has shifted to landscape evelopment and human interaction. To impart the results, new methods and techniques are necessary. Virtual globes such as Google Earth offer fascinating methods of giving interested amateurs the possibility to interactively explore ancient cities and landscapes. Thanks to the increasing usage of GIS in cultural heritage, the implementation of interactive three dimensional learning opportunities becomes less and less tedious, but the non-linear narrative story telling medium demands for a special adaption of the content. This paper summarizes the experience gained during the realization of the “Virtual Cilicia Project” and outlines the future potential of virtual globes in the field of cultural heritage.

The German business and information technologies project

The Business and Information Technologies (BIT) project strives to reveal new insights into how modern IT impacts organizational structures and business practices using empirical methods. Due to its international scope, it allows for inter-country comparison of empirical results. Germany — represented by the European School of Management and Technologies (ESMT) and the Institute of Information Systems at Humboldt-Universität zu Berlin — joined the BIT project in 2006. This report presents the result of the first survey conducted in Germany during November–December 2006. The key results are as follows: • The most widely adopted technologies and systems in Germany are websites, wireless hardware and software, groupware/productivity tools, and enterprise resource planning (ERP) systems. The biggest potential for growth exists for collaboration and portal tools, content management systems, business process modelling, and business intelligence applications. A number of technological solutions have not yet been adopted by many organizations but also bear some potential, in particular identity management solutions, Radio Frequency Identification (RFID), biometrics, and third-party authentication and verification. • IT security remains on the top of the agenda for most enterprises: budget spending was increasing in the last 3 years. • The workplace and work requirements are changing. IT is used to monitor employees' performance in Germany, but less heavily compared to the United States (Karmarkar and Mangal, 2007).1 The demand for IT skills is increasing at all corporate levels. Executives are asking for more and better structured information and this, in turn, triggers the appearance of new decision-making tools and online technologies on the market. • The internal organization of companies in Germany is underway: organizations are becoming flatter, even though the trend is not as pronounced as in the United States (Karmarkar and Mangal, 2007), and the geographical scope of their operations is increasing. Modern IT plays an important role in enabling this development, e.g. telecommuting, teleconferencing, and other web-based collaboration formats are becoming increasingly popular in the corporate context. • The degree to which outsourcing is being pursued is quite limited with little change expected. IT services, payroll, and market research are the most widely outsourced business functions. This corresponds to the results from other countries. • Up to now, the adoption of e-business technologies has had a rather limited effect on marketing functions. Companies tend to extract synergies from traditional printed media and on-line advertising. • The adoption of e-business has not had a major impact on marketing capabilities and strategy yet. Traditional methods of customer segmentation are still dominating. The corporate identity of most organizations does not change significantly when going online. • Online sales channel are mainly viewed as a complement to the traditional distribution means. • Technology adoption has caused production and organizational costs to decrease. However, the costs of technology acquisition and maintenance as well as consultancy and internal communication costs have increased.

Envisioning sustainable water futures in a transdisciplinary learning process: combining normative, explorative, and participatory scenario approaches

Competing water demands for household consumption as well as the production of food, energy, and other uses pose challenges for water supply and sustainable development in many parts of the world. Designing creative strategies and learning processes for sustainable water governance is thus of prime importance. While this need is uncontested, suitable approaches still have to be found. In this article we present and evaluate a conceptual approach to scenario building aimed at transdisciplinary learning for sustainable water governance. The approach combines normative, explorative, and participatory scenario elements. This combination allows for adequate consideration of stakeholders’ and scientists’ systems, target, and transformation knowledge. Application of the approach in the MontanAqua project in the Swiss Alps confirmed its high potential for co-producing new knowledge and establishing a meaningful and deliberative dialogue between all actors involved. The iterative and combined approach ensured that stakeholders’ knowledge was adequately captured, fed into scientific analysis, and brought back to stakeholders in several cycles, thereby facilitating learning and co-production of new knowledge relevant for both stakeholders and scientists. However, the approach also revealed a number of constraints, including the enormous flexibility required of stakeholders and scientists in order for them to truly engage in the co-production of new knowledge. Overall, the study showed that shifts from strategic to communicative action are possible in an environment of mutual trust. This ultimately depends on creating conditions of interaction that place scientists’ and stakeholders’ knowledge on an equal footing.

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.

Interprofessional Education in Anatomy: Learning Together in Medical and Nursing Training

Teamwork and the interprofessional collaboration of all health professions are a guarantee of patient safety and highly qualified treatment in patient care. In the daily clinical routine, physicians and nurses must work together, but the education of the different health professions occurs separately in various places, mostly without interrelated contact. Such training abets mutual misunderstanding and cements professional protectionism, which is why interprofessional education can play an important role in dismantling such barriers to future cooperation. In this article, a pilot project in interprofessional education involving both medical and nursing students is presented, and the concept and the course of training are described in detail. The report illustrates how nursing topics and anatomy lectures can be combined for interprofessional learning in an early phase of training. Evaluation of the course showed that the students were highly satisfied with the collaborative training and believed interprofessional education (IPE) to be an important experience for their future profession and understanding of other health professionals. The results show that the IPE teaching concept, which combines anatomy and nursing topics, provides an optimal setting for learning together and helps nurses and doctors in training to gain knowledge about other health professionals’ roles, thus evolving mutual understanding.