5 Matching Annotations
  1. Sep 2024
    1. (~19:20)

      According to Huberman, there is a positive causal relationship between caffeine and reduced reaction time, increasing both speed and accuracy of recall. Thus useful to take in a certain amount of caffeine 30-60 minutes before an important exam or test.

  2. May 2024
  3. Sep 2022
    1. After looking at various studies fromthe 1960s until the early 1980s, Barry S. Stein et al. summarises:“The results of several recent studies support the hypothesis that

      retention is facilitated by acquisition conditions that prompt people to elaborate information in a way that increases the distinctiveness of their memory representations.” (Stein et al. 1984, 522)

      Want to read this paper.

      Isn't this a major portion of what many mnemotechniques attempt to do? "increase distinctiveness of memory representations"? And didn't he just wholly dismiss the entirety of mnemotechniques as "tricks" a few paragraphs back? (see: https://hypothes.is/a/dwktfDiuEe2sxaePuVIECg)

      How can one build or design this into a pedagogical system? How is this potentially related to Andy Matuschak's mnemonic medium research?

  4. Nov 2018
    1. LESSLEARNING,MORE OFTEN:THE IMPACT OF SPACINGEFFECTINAN ADULTE-LEARNINGENVIRONMENTl

      Spacing effect. of training explores the retention of learning over short and long intervals of learning, particularly in hybrid and distance learning.<br> The study was based on prior studies regarding training and retention and integrated data from the learning management system used by the participants. The study resulted in finding that smaller , more frequent learning over time appears to be more effective than the traditional presentation of mass learning. The study also concluded that much of the time participants spent in learning pertained to language acquisition of foreign language learners and/or new vocabulary.<br> It is also noted that the participants were engaged in learning to support workplace goals, which leads to highly motivated participants.

      RATING 10/10

  5. Nov 2017
    1. Mount St. Mary’s use of predictive analytics to encourage at-risk students to drop out to elevate the retention rate reveals how analytics can be abused without student knowledge and consent

      Wow. Not that we need such an extreme case to shed light on the perverse incentives at stake in Learning Analytics, but this surely made readers react. On the other hand, there’s a lot more to be said about retention policies. People often act as though they were essential to learning. Retention is important to the institution but are we treating drop-outs as escapees? One learner in my class (whose major is criminology) was describing the similarities between schools and prisons. It can be hard to dissipate this notion when leaving an institution is perceived as a big failure of that institution. (Plus, Learning Analytics can really feel like the Panopticon.) Some comments about drop-outs make it sound like they got no learning done. Meanwhile, some entrepreneurs are encouraging students to leave institutions or to not enroll in the first place. Going back to that important question by @sarahfr: why do people go to university?