Group items tagged

ELA: There are more sobering notes among the n-grams. For instance, here's the trajectory of Marc Chagall, an artist born in 1887. And this looks like the normal trajectory of a famous person. He gets more and more and more famous, except if you look in German. If you look in German, you see something completely bizarre, something you pretty much never see, which is he becomes extremely famous and then all of a sudden plummets, going through a nadir between 1933 and 1945, before rebounding afterward. And of course, what we're seeing is the fact Marc Chagall was a Jewish artist in Nazi Germany. Now these signals are actually so strong that we don't need to know that someone was censored. We can actually figure it out using really basic signal processing. Here's a simple way to do it. Well, a reasonable expectation is that somebody's fame in a given period of time should be roughly the average of their fame before and their fame after. So that's sort of what we expect. And we compare that to the fame that we observe. And we just divide one by the other to produce something we call a suppression index. If the suppression index is very, very, very small, then you very well might be being suppressed. If it's very large, maybe you're benefiting from propaganda.

Now when Google digitizes a book, they put it into a really nice format. Now we've got the data, plus we have metadata. We have information about things like where was it published, who was the author, when was it published. And what we do is go through all of those records and exclude everything that's not the highest quality data. What we're left with is a collection of five million books, 500 billion words, a string of characters a thousand times longer than the human genome -- a text which, when written out, would stretch from here to the Moon and back 10 times over -- a veritable shard of our cultural genome.

One of the best examples I have seen of the flex model was in Morgan Hill, California. This is a district south of San Jose where about a third of its students are Hispanic and I believe over a third of its students are on free-and-reduced price lunch. The school is called the Silicon Valley Flex Academy - Grades 6 through 12. As you walk into the school there are a couple of huge open spaces on either side where every student has his/her own office. In this space, each student has his/her own computer. The students are encouraged to decorate their own space with things they like (in the same way an adult might decorate an office at work). There are break out classrooms around the perimeter of the building. Here teachers are getting the data on how the kids are doing. Teachers can pull students into these break-out classrooms in very small groups. The teacher is then able to focus on a student's individual issues. The teacher's job is totally different in this arrangement. The fascinating thing was how much ownership the students have over their learning. They all knew exactly what was expected of them the entire year. They knew exactly how they were doing at any point. Their job was to learn the material. If they could get the work done during the school day there was no homework. So it was up to the individual students to make those decisions.

The teachers I spoke to explained that they had been trained to do lesson planning, lectures to large groups of students and classroom management -- none of which they were now doing. They explained that the adjustment was difficult. Training has not been built into the formal teacher training system for programs like this, and few are really thinking about it at the moment. Now, the teacher is still doing teaching or tutoring when pulling students out into small groups for project-based work, but instead of this being determined by a pacing guide, this is now being determined by where the students are in their learning. What was so interesting was that in this model, teachers were able to do the tutoring and value enrichment work that teachers really like to do but don't always get time to do in a classroom. One of the challenges the teachers mentioned was staying on top of scheduling. How do you keep track when you have students at different places in the curriculum? Those were tough decisions for teachers to make and they were, as you say, learning on the job.

When students own their learning, they feel responsible for it and motivated to do it. What they also appreciated was that the teacher was no longer there to "punish them" or "grade them down". Instead the teacher was there to help them reach their goal. This is much more of an environment built around success and motivation versus failure.

the knowledge developed during the course does not pre-exist the course. Second, since the knowledge of the course does not exist before the course (because you and the students develop the knowledge during the course), your chief challenge is to manage the process of knowledge discovery.

Now, because learning resources and opportunities are infinite, make the move: Don’t just tell students the key knowledge in your field, but help them discover it through problem-based active learning. Change your curriculum from a list of what you will say to a list of essential problems (or questions) that students will address, with your guidance, throughout the semester.

It may well be better to re-state learning outcomes in terms of essential problems and the research associated with those essential problems, and build rubrics based on the problems within a problem-based learning structure.

Successful technology integration only produces amplified results when in its integration agency is given to the learner, when it becomes a tool to help learners learn, not teachers teach.

I would also like to add that that old belief about teaching and learning has been around for a very long time now and part of that belief, the part about the teacher possessing the knowledge and imparting it to kids, is in direct threat when faced with technology. A teacher who has been taught to believe that they are needed for the knowledge they have and that that knowledge gives them authority in the classroom is threatened by technology. That threat needs to be approached lightly. If one speaks the truth too harshly the faithful will simply label them a blasphemer and ignore the truth in their message.

et me start by saying that I consider teaching among the most important professions on earth, but just as doctors need to be current on medical technology, teachers MUST be current on information and communication technologies. Those are the tools of the trade.

“Since then we have had two million views on 1700 images but for us it goes beyond the views; it is the connection we have made with this audience.”

According to Bray, the connection with audience has paid off with the Powerhouse’s community now volunteering to conduct research work that now adds to the museum’s knowledge of its own collection.

“They have been tagging, commenting, researching, identifying locations, doing incredible images because they are allowed to use them for free and with no restrictions,” Bray says. “It allows the audience to do citizen curation.”

Grand narratives – such as provide us with a large umbrella that we can use to make sense of the world – have been besieged over the last several decades. Grand narratives in the form of newspapers, newscasts, and books are now augmented by blogs and YouTube videos.

an attempt to provide or create some type of a narrative – namely, a narrative of coherence.

In a traditional course, the educator hacks the trails to complex information landscapes. The educator’s bias influences what is included and excluded.

ouTube, Google, Stanford, Berkeley, and the California School for the Deaf (CSD) are about to speak on YouTube and accessibility.

Now the Google Speech Technology team is speaking about the challenges they faced to get auto-captioning operational. Their vision was to create accurate captions for all videos in all languages, but had to deal with huge vocabularies, background noise, poor recordings, accent variability, and distinguishing between song and speech.- Google’s approach is to deliver captions from the cloud, given them the ability to rapidly iterate and model at a large scale.

You can only caption your own videos — you can’t just caption someone else’s videos.