#schoolofdata

[timothygrantwriter]

You run into the best people at #SchoolofData #DataDonuts (at Los Angeles, California) https://www.instagram.com/p/BtT6xpLgTeAkZmo8bYGShTy78PhOGttIBGbOVU0/?utm_source=ig_tumblr_share&igshid=gkyqyrghsoue

[kaythaney]

Data is a Team Sport: Mentors Mediators and Mad Skills with Emma Prest of @DataKind and @tingeber https://t.co/hOaxJlmreL #schoolofdata http://pic.twitter.com/WWycGcbd0t

— Open Knowledge Intl (@OKFN) August 8, 2017

[social-tic]

La Escuela de Datos se esparce por el mundo

A un año de haberse lanzado Escuela de Datos, Open Knowledge Foundation (OKFN) da un siguiente paso internacional con el inicio de un programa de mentores (llamados fellows) que tendrán la vital labor de promover el uso de datos y entrenar en toda la cadena de valor de datos a periodistas, activistas y grupos involucrados. En la sesión inaugural del OKFest 2014, se dio a conocer los 12 fellows que integran la 1ra generación, que abarca países en África, Asia, América Latina y Europa.

El potencial de una red de formadores y formadoras tan amplia y diversa es extraordinaria ya que, de articularse de manera dinámica y proactiva, fomenta un intercambio de experiencias, tácticas y contenidos del que se beneficiarán todas las personas involucradas. Por ejemplo, las experiencias iniciales que hemos impulsado desde SocialTIC a la comunidad de Escuela de Datos, como el fusionar expediciones de datos con micro-sesiones de aprendizaje de herramientas, ya han permeado en las estructuras metodológicas de entrenadores en Latinoamérica, Sudáfrica y Europa. A nivel temático, la red de entrenadores podrá mejorar sus capacidades técnicas al estar en contacto directo con contrapartes especializadas.

Al finalizar OKFest, se realizó el #DataCamp, un fin de semana de convivencia, intercambio de saberes y articulación programática. Dos días bastaron para ver cómo la unión e interacción de individuos con metas similares es posible y se inician los lazos que podrán llevar la formación en datos desde Tijuana hasta Yakarta pasando por Johannesburgo y Nueva Delhi.

En América Latina, esta experiencia inicia con fellows en México (que tendrán actividad en Centroamérica también) y Perú, pero fuertemente vinculados con las iniciativas existentes en muchos países de la región. Se espera que una nueva generación de fellows se reclute a inicios de 2015 para aumentar la formación en datos donde más se necesita. Para saber más sobre este programa visita escueladedatos.org y sigue la actividad en redes sociales de los fellows y de Escuela de Datos.

[datajournalismlinks]

As a School of Data fellow, you will receive data and leadership training, as well as coaching to organise events and build your community in your country or region. You will also be part of a growing global network of School of Data practitioners, benefiting from the network effects of sharing resources and knowledge and contributing to our understanding about how best to localise our training efforts.

[the-compiler]

Designing for Data Literacy Learners

Download paper here We really like this bit of research from Rahul Bhargava and Catherine D'Ignazio because it pins down some key practical elements that anyone trying to help people learn about using data should remember. They point out that though more and more tools are now available to help people start to work with data, they rarely help people learn more deeply: "a tool that is easy to learn is not necessarily designed to support rich learning.” As they put it, many tools “introduce themselves as ‘magic’, explicitly hiding the mental models and software operations that they run through to produce their outputs."  

They recommend that tool designers and educators “design from the start with...strong pedagogical principles in mind,” referring to Paulo Freire and Seymour Papert in particular. If you’re building a tool, aim to do so according to four design principles:

Focused: A focused tool does one thing well - giving enough space for a learner to experiment, but not so many options that they get lost.

Guided: guiding a learner through an example activity as soon as they start (potentially creating example outputs too).

Inviting: Making tools appealing and non-intimidating to learners by using relevant information, or funny and playful approaches that encourage learners to experiment.

Expandable: Pitching a tool at the right level for the learner's abilities, while also giving them a path to find out more about how the tool works and learn more deeply about the issue.

(They also come up with a helpful definition of data literacy - the ability to read, work with, analyze and argue with data.)

Reading data: understanding what data is, and what aspects of the world it represents.

Working with data: creating, acquiring, cleaning,and managing it.

Analysing data: filtering, sorting, aggregating, comparing, and performing other such analytic operations on it.

Arguing with data: using data to support a larger narrative intended to communicate some message to a particular audience.)

[datajournalismlinks]

School of Data is inviting journalists, civil society advocates and anyone interested in pushing data literacy forward to apply for its 2016 Fellowship Programme, which will run from April to December 2016. Up to 10 positions are open, with an application deadline set on March 10, 2016.