15 Matching Annotations
  1. Jun 2016
    1. Should faculty (and even students) have a greater say in which tools the university chooses instead of constantly finding themselves as consumers of those forced upon them by the institution?

      The answer here is clearly yes. But what forums exist or might be imagined to enable this dialogue. I know at h we are lucky (if I might say so myself) to have an educator on staff and we work closely with faculty on our product. What more could we do though? And how could an indie ed tech community more broadly nurture these conversations?...

  2. Mar 2016
    1. if someone is willing to commit to talking through hip hop

      I got this...

    2. like the personal API

      I need to learn more about this movement...

    1. They are tools like SPLOT, Wikity, Reclaim Hosting, Known, Github, and Hypothes.is to name a few.

      Word!

    1. At least on dating apps everyone can agree that everyone on the app has the same desired goal: a relationship.

      Interesting distinction. So we don't have the same goals in the algorithm of, say, an adaptive learning program?...

    1. You can listen to the “I Love My Label” playlist on Spotify, but you should support artists by buying their music. Unless it's Metallica. Then share freely.

      Badass.

    2. counterintuitively perhaps less “personalized.”

      But isn't the point that is is more (or more actually) "personalized"?

    3. “Personalization” might sound like it’s designed especially for us; but “personalization” is an algorithm based on a profile, on a category, on a label.

      This is a powerful argument. But could a proliferation of labels, enabled by computational power, better approach personalization?

      I've been thinking about a similar idea in relation to the music industry/algorithm while reading the above: are Spotify/Netflix recommendations looking for the hit? Or are they looking for musical/filmic suggestions that will keep me individually as a customer? I'm much more compelled by that model than what's offered on top 40 radio or the megaplex.

    4. Algorithms and analytics will “personalize” our world, we’re told. The problem, of course, is that the algorithms and the analytics also make everything sound the same.

      I'd love to just accept this argument, but want there to be more evidence. No doubt there are more radical forms of self-education, but isn't it true to some degree that there is personalization in, say, adaptive learning programs?

    5. What happens in the face of an algorithmic education to intellectual curiosity?

      Fair enough, but is it either/or or both/and. I'm happy to be recommended a new band by Spotify, but ultimately will make the call if I like it or not, perhaps even clicking a reaction so that the algorithm gets better? Or is that a fantasy?...I'm also not going to be deaf to my friends recommendations, etc. that might also direct my musical curiosity.

    6. I call myself a “serial dropout,”

    7. Little by little the subversive features of the computer were eroded away: Instead of cutting across and so challenging the very idea of subject boundaries, the computer now defined a new subject; instead of changing the emphasis from impersonal curriculum to excited live exploration by students, the computer was now used to reinforce School’s ways. What had started as a subversive instrument of change was neutralized by the system and converted into an instrument of consolidation.

      Wow, This is a great quote, and so apt in this new context of the rise of the LMS.

    8. Once something sells, than we hear it and echoes of it again and again and again and again.

      Love this sequence of slides:

    9. No one – well, except my parents, I guess – knew how many times I played that 45 of Autograph’s “Turn Up the Radio,” how many times I rewound the cassette to replay Guns & Roses’ “Welcome to the Jungle.” But now the software knows

      This seems empowering to me (or potentially so)...

    10. predict hit songs

      Different from predicting what songs I might like.