dijous, 29 de desembre de 2011

dimarts, 27 de desembre de 2011

Entender es percibir patrones

El autor leyó a Steven Johnson en Sistemas emergentes – O qué tienen en común hormigas, neuronas, ciudades y software. Posiblemente también a Barábasi en Bursts, para llegar a las conclusiones que expresa en el vídeo: cuanto más sofisticadas son nuestras tecnologías, más se parecen sus leyes a las de la naturaleza. (El caparazón, Dolors Reig)

TO UNDERSTAND IS TO PERCEIVE PATTERNS from jason silva on Vimeo.

dimecres, 21 de desembre de 2011

Cómo matar al intermediario

Des del tweetedtimes de jordi adell

diumenge, 27 de novembre de 2011

El camino de las competencias básicas

"El camino de las Competencia Básicas según iCOBAE: una apuesta por los docentes como expertos"

dimarts, 8 de novembre de 2011

Felipe G. Gil - La Remezcla como Educación Expandida

Vist a Educación en red, de José Cuerva

diumenge, 6 de novembre de 2011

Habilidades y competencias para el siglo XXI

Compartit per Isabel Ferrer

Seré más freak que el coordinador TIC

Una mica d'humor i música en Educared

dilluns, 10 d’octubre de 2011

diumenge, 9 d’octubre de 2011

Escola 2.0

Inauguració del congrés Escuela 2.0

Cooperar-colaborar

Cuando implantamos una metodología de aprendizaje en cooperación lo que pretendemos es desarrollar las habilidades socio-afectivas de los integrante del grupo; es decir gracias a que nos ayudamos conseguimos el objetivo. Es decir reforzamos al equipo.

Mientras que si utilizamos la metodología del aprendizaje en colaboración damos más liberatd al alumno" para que investigue, pruebe, contraste, experimente, ... El "facilitador da las instrucciones y el "alumno" participa en su aprendizaje de manera individual. El conjunto de aportaciones, aprendizajes individuales configura el aprendizaje del grupo.

He aquí el matiz. Si quiero trabajar como un grupo mi estrategia de aprendizaje será el aprendizaje en colaboración mientras que si deseo funcionar como un equipo y reforzarlo utilizaré la estrategia del aprendizaje en cooperación
(Àlex Vallès, consultor en procesos formación y desarrollo profesional)

Gràcies

Un video motivacional

dissabte, 8 d’octubre de 2011

dijous, 15 de setembre de 2011

Entorns Personals d'Aprenentatge

Jordi i Linda en una actuació genial

diumenge, 17 d’abril de 2011

dilluns, 11 d’abril de 2011

Enginyeria estadística, by Thomas Pyzdek

Statistical Engineering

In the movie “The Graduate,” the new graduate is told by a would-be mentor to remember only one word as he heads out into the world: Plastics. Times have changed. Hal Varian, the chief economist at Google says, ‘‘I keep saying that the sexy job in the next 10 years will be statisticians. And I’m not kidding.’’ Statistical methods are being used by a larger cross-section of people in a wider variety of industries than ever before. There are numerous reasons for this. Nearly everyone has what was once considered to be a supercomputer sitting on their desktop. Powerful statistical software is widely available, including popular packages like Minitab, JMP, SAS and SPSS, and extremely powerful free software. Oracle’s Crystal Ball software makes it possible to create a statistical distribution for any cell in a spreadsheet, making statistical simulation a snap. While becoming more sophisticated, the software is also becoming easier to use. Output is increasingly graphical and easier to explain to laypersons. The number of people trained in Lean Six Sigma methods is growing rapidly. There is an enormous amount of data saved in public and corporate data warehouses. The list goes on and on.
But perhaps the most important reason for the ballooning use of statistics is: it works.

If we take Aristotle’s logic as the historical starting point for rational analysis, and Galileo’s experimental method as the next major leap, then statistical methods might be viewed as the next step in applied analysis. Many problems don’t lend themselves to solution by pure logic nor by carefully planned and controlled experimentation. Most organizations, especially in the commercial sector, must deal with so many problems and such a dynamic external environment that they are forced to make quick decisions despite large uncertainty, then move on to the next problem. Statistical methods help these decision makers evaluate the evidence and make better decisions quickly. The tools and technology described in the first paragraph make this easier than ever before.

This situation is much more akin to engineering than it is to pure science. The approach has been termed “Statistical Engineering.” Authors Roger W. Hoerl and Ron Snee describe Statistical Engineering as follows:

“The statistical engineering discipline [is] the study of how to utilize the principles and techniques of statistical science for benefit of humankind. From an operational perspective we define statistical engineering as the study of how to best utilize statistical concepts, methods, and tools and integrate them with information technology and other relevant sciences to generate improved results. In other words, engineers—statistical or otherwise—do not focus on advancement of the fundamental laws of science but rather how they might be best utilized for practical benefit.

This definition goes beyond applied statistics. Statistical Engineering implies the application of statistics in a systematic framework that utilizes technology to create or improve products, processes and services that improve the lives of people. Disciplines such as Lean Six Sigma, Quality Engineering, Reliability Engineering, and others can be said to do this to some degree, but there are other ways to use Statistical Engineering, some quite unexpected. Billy Beane, general manager of MLB’s Oakland A’s and protagonist of Michael Lewis’s book Moneyball, had a problem: how to win in the Major Leagues with a budget that’s smaller than that of nearly every other team. Conventional wisdom long held that big name, highly athletic hitters and young pitchers with rocket arms were the ticket to success. But Beane and his staff, buoyed by massive amounts of carefully interpreted statistical data, believed that wins could be had by more affordable methods such as hitters with high on-base percentage and pitchers who get lots of ground outs. Given this information and a tight budget, Beane defied tradition and his own scouting department to build winning teams of young affordable players and inexpensive castoff veterans. Author Michael Lewis examines how in 2002 the Oakland Athletics achieved a spectacular winning record while having the smallest player payroll of any major league baseball team. Given the heavily publicized salaries of players for teams like the Boston Red Sox or New York Yankees, baseball insiders and fans assume that the biggest talents deserve and get the biggest salaries. However, argues author Michael Lewis, little-known numbers and statistics matter more.

Statistical Engineering is not limited to applied statistics, theoretical statistics have a place too. In a paper published in the April-June 2011 issue of the journal Quality Engineering author Philip R. Scinto offers this list of Statistical Engineering attributes:

* Meets high-level needs of an organization
* Work/study for the greater good
* Use of statistical concepts and tools
* Collaborative effort with other sciences
* Integrated with other sciences
* Documented protocol
* Activity continuous with sustainable life
* Improved results

It isn’t necessary that all items on the list be checked off, but the list is useful in evaluating whether an activity qualifies as Statistical Engineering or if it’s merely another clever use of statistics. The important thing isn’t the label we apply, but the improvement that can be achieved by properly using statistical methods along with science and technology to achieve a challenging goal.
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diumenge, 10 d’abril de 2011

dilluns, 4 d’abril de 2011

diumenge, 3 d’abril de 2011

dissabte, 12 de març de 2011

dimecres, 9 de febrer de 2011

Corbes que semblen papallones

Aquesta aplicació crea corbes matemàtiques que semblen papallones



divendres, 21 de gener de 2011

segona part

Entorns Personals d'Aprenentatge

No em puc resistir a presentar-vos aquesta presentació de Jordi Adell. Genial com sempre

dijous, 20 de gener de 2011

La percepció

Gràcies a Pedro Villarubia, professor de dibuix

dimecres, 12 de gener de 2011

L'obsolescència programada

Aquest video és una mica llarg, però paga la pena. Espere que us agrade

Comprar, tirar, comprar