La misión principal de la escuela ya no es enseñar cosas


“Internet lo hace mejor”, dice Francesco Tonucci

“La misión de la escuela ya no es enseñar cosas. Eso lo hace mejor la TV o Internet.” La definición, llamada a suscitar una fuerte polémica, es del reconocido pedagogo italiano Francesco Tonucci. Pero si la escuela ya no tiene que enseñar, ¿cuál es su misión? “Debe ser el lugar donde los chicos aprendan a manejar y usar bien las nuevas tecnologías, donde se transmita un método de trabajo e investigación científica, se fomente el conocimiento crítico y se aprenda a cooperar y trabajar en equipo”, responde.

Para Tonucci, de 68 años, nacido en Fano y radicado en Roma, el colegio no debe asumir un papel absorbente en la vida de los chicos. Por eso discrepa de los que defienden el doble turno escolar.

“Necesitamos de los niños para salvar nuestros colegios”, explica Tonucci, licenciado en Pedagogía en Milán, investigador, dibujante y autor…

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“El algoritmo” la nueva celebridad entre diseñadores

A pesar de que los seres humanos aún somos mejores para tomar decisiones subjetivas en cuestiones de estética por ejemplo. El diseño computacional explora la alternativa a través de la programación para ofrecer una variedad de opciones que pueden ayudar en las etapa mas tediosas del proceso de diseño a las que denominamos comúnmente “talacha”. Esté artículo muestra el porqué en el diseño de información debemos de prestar mas atención al algoritmo.


Why Algorithms Are The Next Star Designers


The industrial designer of the future might just be a computer. The traditional design process can be a laborious one, full of iterations and tweaks to make a product just so. For years, design software makerAutodesk has been working on an alternative: a program that sorts through all the ways to make a product of specific measurements and then spits out the best option.


“In the past couple of years, we have experienced such an explosion of computing power that we can completely change the design equation,” says Autodesk chief technology officer Jeff Kowalski. Rather than using software to draw and analyze a designer’s vision, Autodesk wants to use that computing power to generate the idea itself–by running through a nearly infinite number of ways to build the same product.

Though still in the experimental phase, Autodesk has been working on computational design for the last seven years through research projects such as Project Dreamcatcher, a system that generates CAD geometry based on a list of functional requirements. This approach could prove especially effective in sectors where being light and strong are of the utmost importance–as with cars and airplanes, where extra pounds have a direct impact on fuel efficiency.

Here’s how it works. You type in a set of constraints for the product. Then an algorithm “will go through a nearly infinite set of results and head towards ones that are going to satisfy the designer,” Kowalksi explains. Say you want a chair that needs to support 200 pounds of weight and be two feet off the ground while using the least amount of material possible. The program might start off with 1,000 ways to make the same chair, and then intermix what it sees as the most effective components of those 1,000 chairs to make 1,000 new options. It can go through a million iterations of the same chair “in the time that it would take the designer to describe just one.” It can also suggest what type of material to use.

A computer isn’t constrained by preconceived notions of what a chair should look like. The example above, chosen from several designs the algorithm generated, has a curvy, slightly portly, webbed aesthetic, quite unlike our traditional conception of how a chair should look. Other options for making the same chair might include straighter legs, or just a single pedestal leg, but the algorithm is capable of generating a variety of different designs that all meet the required criteria.

It’s not a process that’s limited to making chairs. “This applies to buildings, bridges, automotive parts–everything we do where we have to draw things,” Kowalski explains. It could be used to design a lightweight underlying structure of, say, a bicycle, which could then be covered by a skin to give it a different look–so you’re not limited to the lattice aesthetic, even if that’s the most efficient material for that product.

Computational design isn’t aimed at replacing human insight. People are still better at making more subjective selections over issues such as aesthetics. But the program certainly does serve up a panoply of options and can help sort through some of the more tedious aspects of the design process.

El reto de enseñar creatividad

∞ Posted May 6th, 2014 at 12:52 pm
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Attempting to “teach” creativity is difficult. I would argue it can’t be done well in our standard, current educational environment.

When your expectations involve creativity, the task of training or optimizing for it becomes difficult, if not entirely impossible. How do you measure what’s truly creative when there are expectations set? How can anyone value whether something is creative or not if creative ideas exist, by nature, outside of expectations?

As Cevin Soling mentions in Can Any School Foster Pure Creativity?:

“Creativity is based on thinking unconventionally, having time to daydream or simply reflect, understanding that there is no single right answer, and appreciating and valuing failure. All of these experiences run counter to what’s measured, and thus valued, in the public school system.”
A popular retelling of this exact situation comes from Sir Ken Robinson’s 2006 TED talk How schools kill creativity. In the talk, Sir Robinson tells us:

“I heard a great story recently…of a little girl who was in a drawing lesson. She was six and she was at the back, drawing, and the teacher said this little girl hardly ever paid attention, and in this drawing lesson she did. The teacher was fascinated and she went over to her and she said, ‘What are you drawing?’ And the girl said, ‘I’m drawing a picture of God.’ And the teacher said, ‘But nobody knows what God looks like.’ And the girl said, ‘They will in a minute.’”
Note the reaction the teacher had in this story when she heard what the little girl was drawing. Rather than viewing the girl’s approach as creative and imaginative, the teacher has an initial reaction to explain to the girl that she simply couldn’t be drawing god, nobody knows what he looks like.

In teaching creativity, we run into this problem again and again: how do educators remove their own biases to make way for natural creative insights? How do we, as advocates for promoting creativity in the workplace (as an example), get out of our own way?

Rather than trying to teach creativity (the act of generating unique and valuable thoughts), it’s worthwhile to instead teach and actively promote the attributes that make up creativity.

Exercises that build confidence, that promote curiosity and exploration, that force participants to be resourceful, those are worthwhile endeavors that build creativity.

We also know that these are attributes that can be taught without hindering the process of teaching or grading them. We can teach students and employees to be resourceful and curious by offering them playful challenges. We can instill a sense of humility in those we teach, and encourage a mindset that allows restful breaks whenever they’re needed.

If we want to teach creativity to our children, peers, co-workers, or ourselves, we have to focus on the individual attributes that drive it, not merely on the act of generating ideas.

To teach and encourage creativity yourself, look to the various attributes that cause creativity. When those aspects are built or strengthened, the result is almost always some level of creative output.