9 Matching Annotations
  1. May 2022
    1. The highlights you made in FreeTime are preserved in My Clippings.txt, but you can’t see them on the Kindle unless you are in FreeTime mode. Progress between FreeTime and regular mode are tracked separately, too. I now pretty much only use my Kindle in FreeTime mode so that my reading statistics are tracked. If you are a data nerd and want to crunch the data on your own, it is stored in a SQLite file on your device under system > freetime > freetime.db.

      FreeTime mode on the Amazon Kindle will provide you with reading statistics. You can find the raw data as an SQLite file under system > freetime > freetime.db.

    1. A 20-year age difference (for example, from 20 to 40, or from 30 to 50 years old) will, on average, correspond to reading 30 WPM slower, meaning that a 50-year old user will need about 11% more time than a 30-year old user to read the same text.
    2. Users’ age had a strong impact on their reading speed, which dropped by 1.5 WPM for each year of age.
  2. May 2019
  3. Oct 2018
  4. Sep 2017
    1. Textbook maker Pearson is also getting in on the action by developing adaptive learning software and launching virtual tutors for students as they “read” through digital textbook resources.

      Ok, here I'm getting a bit more worried. It's not that I don't think this is helpful. But I do think it's skipping some possible better, more human solutions.

      One concern: the premise here is that comprehension struggles are mostly questions requiring answers rather than discursive situations requiring more interaction. A second related concern: is the ultimate goal of "learning" to get the answer or to acquire facility with that discursive process? (Answer: the latter.)

      I think simple social annotation, perhaps backed by some AI, could go a long way here. Allow students to ask questions, answer each others questions, and surface those questions and answers in a useful way to teachers...

  5. May 2017
  6. Jul 2016
    1. p. 6

      Retrieval methods designed for small databases decline rapidly in effectiveness as collections grow...

      This is an interesting point that is missed in the Distant reading controversies: its all very well to say that you prefer close reading, but close reading doesn't scale--or rather the methodologies used to decide what to close read were developed when big data didn't exist. How to you combine that when you can read everything. I.e. You close read Dickins because he's what survived the 19th C as being worth reading. But now, if we could recover everything from the 19th C how do you justify methodologically not looking more widely?