I would be interested in participating in the scheduler experiment.
Hopefully the alternate scheduler is implemented as a Plug-In, in a
manner similar to the cramming scheduler?
David Schuler
[email protected]
On Sat, 27 Feb 2016 06:29:51 +0100, Peter Bienstman
wrote:
These are the people from the scheduler experiment I was talking about.
Peter
On 26 February 2016 22:33:41 CET, Gwern Branwen wrote:
"Unbounded Human Learning: Optimal Scheduling for Spaced Repetition",
Reddy et al 2016 http://arxiv.org/pdf/1602.07032.pdf
In the study of human learning, there is broad evidence that our
ability to retain a piece of information improves with repeated
exposure, and that it decays with delay since the last exposure. This
plays a crucial role in the design of educational software, leading to
a trade-off between teaching new material and reviewing what has
already been taught. A common way to balance this trade-off is via
spaced repetition - using periodic review of content to improve
long-term retention. Though widely used in practice, there is little
formal understanding of the design of these systems. This paper
addresses this gap. First, we mine log data from a spaced repet ition
system [Mnemosyne] to establish the functional dependence of retention
on reinforcement and delay. Second, based on this memory model, we
develop a mathematical framework for spaced repetition systems using a
queueing-network approach. This model formalizes the popular Leitner
Heuristic for spaced repetition, providing the first rigorous and
computationally tractable means of optimizing the review schedule.
Finally, we empirically confirm the validity of our formal model via a
Mechanical Turk experiment. In particular, we verify a key qualitative
insight and prediction of our model - the existence of a sharp phase
transition in learning outcomes upon increasing the rate of new item
introduction
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