What is it like to learn and participate in rhizomatic MOOCs? a collaborative autoethnography of #RHIZO14

In January 2014, we participated in a connectivist-style massive open online course (cMOOC) called "Rhizomatic Learning – The community is the curriculum" (#rhizo14). In rhizomatic learning, teacher and student roles are radically restructured. Course content and value come mostly from students; the teacher, at most, is a curator who provides a starting point and guidance and sometimes participates as a learner. Early on, we felt that we were in a unique learning experience that we wanted to capture in writing. Explaining #rhizo14 to others without the benefit of traditional processes, practices, roles, or structures, however, presented a challenge. We invited participants to contribute narratives to a collaborative autoethnography (CAE), which comprises an assortment of collaborative Google Docs, blog posts by individuals, and comments on those documents and posts. This strategy afforded insight into what many participants found to be a most engaging course and what for some was a transformative experience. In discussing the findings from the CAE, our intent is to benefit others interested in rhizomatic learning spaces such as cMOOCs. This authoethnography specifically addresses gaps both in the understanding of the learner experience in cMOOCs and in the nature of rhizomatic learning

Evaluating uncertainty estimates in hydrologic models: borrowing measures from the forecast verification community

The hydrologic community is generally moving towards the use of probabilistic estimates of streamflow, primarily through the implementation of Ensemble Streamflow Prediction (ESP) systems, ensemble data assimilation methods, or multi-modeling platforms. However, evaluation of probabilistic outputs has not necessarily kept pace with ensemble generation. Much of the modeling community is still performing model evaluation using standard deterministic measures, such as error, correlation, or bias, typically applied to the ensemble mean or median. Probabilistic forecast verification methods have been well developed, particularly in the atmospheric sciences, yet few have been adopted for evaluating uncertainty estimates in hydrologic model simulations. In the current paper, we overview existing probabilistic forecast verification methods and apply the methods to evaluate and compare model ensembles produced from two different parameter uncertainty estimation methods: the Generalized Uncertainty Likelihood Estimator (GLUE), and the Shuffle Complex Evolution Metropolis (SCEM). Model ensembles are generated for the National Weather Service SACramento Soil Moisture Accounting (SAC-SMA) model for 12 forecast basins located in the Southeastern United States. We evaluate the model ensembles using relevant metrics in the following categories: distribution, correlation, accuracy, conditional statistics, and categorical statistics. We show that the presented probabilistic metrics are easily adapted to model simulation ensembles and provide a robust analysis of model performance associated with parameter uncertainty. Application of these methods requires no information in addition to what is already available as part of traditional model validation methodology and considers the entire ensemble or uncertainty range in the approach

Current Practices in the Development of Decision Support Systems

Decision support systems are one of the latest developments incomputer-based information systems. There are a variety of indications that their development differs in important ways from othertypes of information systems. This article reports the findings of an investigation of how 18 decision support systems were developed. Six major areas were explored: (1) the nature of the developmental approach; (2) user involvement in system development; (3) the time required for system development; (4) the incorporation of the decision maker\u27s style in the system; (5) the role of information systems and operations research/management science personnel in the developmental effort; and (6) specific procedures and techniques used in system developmen

Single-photon detection timing jitter in a visible light photon counter

Visible light photon counters (VLPCs) offer many attractive features as photon detectors, such as high quantum efficiency and photon number resolution. We report measurements of the single-photon timing jitter in a VLPC, a critical performance factor in a time-correlated single-photon counting measurement, in a fiber-coupled closed-cycle cryocooler. The measured timing jitter is 240 ps full-width-at-half-maximum at a wavelength of 550 nm, with a dark count rate of 25 000 counts per second. The timing jitter increases modestly at longer wavelengths to 300 ps at 1000 nm, and increases substantially at lower bias voltages as the quantum efficiency is reduced

Age and Growth of Bluegill, Lepomis macrochirus Rafinesque, from Lake Fort Smith, Arkansas

A total of 337 bluegill from Lake Fort Smith were used for this study. Annuli were formed between late February and early June, the younger fish forming annuli earlier than older fish. Total length-scale radius and length-weight relationships were determined. Growth of bluegill was compared with that reported in other studies. Growth curves were analyzed by the Von Bertalanffy growth formula and the parameters were evaluated in terms of physical and biological factors

Writing the unreadable untext: a collaborative autoethnography of #rhizo14

No abstract available