Ten Quick Tips for Using a Raspberry Pi

Much of biology (and, indeed, all of science) is becoming increasingly computational. We tend to think of this in regards to algorithmic approaches and software tools, as well as increased computing power. There has also been a shift towards slicker, packaged solutions--which mirrors everyday life, from smart phones to smart homes. As a result, it's all too easy to be detached from the fundamental elements that power these changes, and to see solutions as "black boxes". The major goal of this piece is to use the example of the Raspberry Pi--a small, general-purpose computer--as the central component in a highly developed ecosystem that brings together elements like external hardware, sensors and controllers, state-of-the-art programming practices, and basic electronics and physics, all in an approachable and useful way. External devices and inputs are easily connected to the Pi, and it can, in turn, control attached devices very simply. So whether you want to use it to manage laboratory equipment, sample the environment, teach bioinformatics, control your home security or make a model lunar lander, it's all built from the same basic principles. To quote Richard Feynman, "What I cannot create, I do not understand".Comment: 12 pages, 2 figure

Oii-web: An interactive online programming contest training system

In this paper we report our experience, related to the online training for the Italian and International Olympiads in Informatics. We developed an interactive online system, based on CMS, the grading system used in several major programming contests including the International Olympiads in Informatics (IOI), and used it in three distinct context: training students for the Italian Olympiads in Informatics (OII), training teachers in order to be able to assist students for the OII, and training the Italian team for the IOI. The system, that is freely available, proved to be a game changer for the whole italian olympiads in informatics ecosystem: in one year, we almost doubled the participation to OII, from 13k to 21k secondary school students. The system is developed basing on the Contest Management System (CMS, http://cms- dev.github.io/), so it is highly available to extensions supporting, for instance, the pro- duction of feedback on problems solutions submitted by trainees. The system is also freely available, with the idea of allowing for support to alternative necessities and developmen

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Researching into Teaching Methods in Colleges and Universities by Clinton Bennett, Lorraine Foreman‐Peck and Chris Higgins, London: Kogan Page, 1996. ISBN: 0–7494–1768–4, 136 (+ vii) pages, paperback. £14.99

Computational Economics: Help for the Underestimated Undergraduate

Our concern in this paper is that the capability of economics undergraduates is substantially underestimated in the design of the present college curriculum and that our students are insufficiently challenged and motivated. Students enter our classrooms with substantial previous knowledge about computers and computation and we are not taking full advantage of this opportunity. We suggest a set of examples from computational economics which are challenging enough to motivate students and simple enough that they can master them within a few hours. By encouraging the students to modify the models in directions of their own interest avenues for creative endeavor are opened which deeply involve the students in their own education.teaching computational economics

After-School Toolkit: Tips, Techniques and Templates for Improving Program Quality

This toolkit offers program managers a practical, hands-on guide for implementing quality programming in the after-school hours. The kit includes the tools and techniques that increased the quality of literacy programming and helped improve student reading gains in the Communities Organizing Resources to Advance Learning (CORAL) initiative of The James Irvine Foundation. CORAL is an eight-year, $58 million after-school initiative aimed at improving education achievement in low-performing schools in five California cities. In addition to strategies, process and instructions, this toolkit offers a series of tools program staff can use to build the quality of their after-school program

Nine quick tips for efficient bioinformatics curriculum development and training.

Biomedical research is becoming increasingly data driven. New technologies that generate large-scale, complex data are continually emerging and evolving. As a result, there is a concurrent need for training researchers to use and understand new computational tools. Here we describe an efficient and effective approach to developing curriculum materials that can be deployed in a research environment to meet this need