Optimization of Learning:
Summary
(from P.A.Wozniak, Optimization of
Learning, updated and
corrected May 20, 1997)
Here is the list of the most important points
of the thesis (terminology given in boldface was included in the
Glossary):
- The SuperMemo method used
in repetition spacing was presented
(Chapter 3). The following elements of the method marked
the most significant steps in its development:
- application of the recall
principle (Chapter 3.1)
- application of the minimum
information principle (Chapters 2 and
3.1)
- application of the optimum
repetition spacing principle (Chapters 2
and 3.1)
- introducing E-factors
(Chapter 3.2)
- introducing the function
of optimum intervals (Chapter 3.3 and
3.4)
- application of interval
dispersing (Chapter 3.5)
- application of the
propagation of changes in the matrix of optimal
intervals (Chapter 3.7)
- Software implementation of the SuperMemo
method was described (Chapter 4)
- SuperMemo on paper was described (Chapter
7)
- The function of optimum intervals was
found by means of three methods:
- specially designed experiment
(p.16)
- univalent matrices of
optimal factors in the Algorithm
SM-5 (Chapter 3.6)
- model of intermittent
learning (Chapter 11.4)
- A comprehensive analysis of the SuperMemo
learning process was presented:
- an accurate simulation model of
the SuperMemo process was constructed (Chapter 5)
- function of the acquisition rate
was found (p.68)
- all-life, maximum acquisition
rate was predicted to be about 230
item/year/min (this value may be substantially
lower in case of ill-structured SuperMemo databases,
or, possibly, higher in case of further
development of the knowledge structuring techniques)
(p.68)
- the all-life capacity of the human
brain was estimated to be about several million SuperMemo
items (p. 72)
- long-term acquisition of knowledge
with the use of the SuperMemo method was
shown to be close to linear (p.69)
- workload function
was found (p. 65)
- reducing the forgetting
index was found as of little value for
the speed and quality of learning
- eliminating items characterized
by low E-factors was
demonstrated to be crucial for the speed of
learning (p. 68)
- it was found that only 5% of the
learning process can be spent on acquisition of
knew knowledge, the rest is consumed by
repetitions of the old material
- forgetting rate in
case of the cessation of repetitions was found to
be much higher than the acquisition rate (e.g.
after 5 years of the process, 60% of knowledge is
lost in the first year after the cessation) (p.
70)
- burden parameter
was proposed as a very accurate measure of the
learning progress in SuperMemo (p.53)
- model of intermittent
learning was constructed (Chapter 11)
- relationship between the forgetting
index and knowledge retention was
found to be close to linear. For the index equal
to 10%, as in the Algorithm SM-5,
the long-term retention was predicted to be 94%
(the presently reported retention reaches 96%)
(p. 154)
- the increase of the stability
of memories was found to be the greatest
if the intervals are twice as long as the optimal
intervals (it corresponds to the
forgetting index equal to 20%) (p. 156)
- the function of the workload-retention
trade-off was found (p. 155)
- the function of the workload-retention
trade-off was used to determine
that the desirable value of the forgetting
index falls in the rage 5% to 10% (p.
155)
- Method-independent prerequisites of the
successful application of SuperMemo were formulated
(Chapter 6)
- Results of a questionnaire collecting
opinions of SuperMemo students were presented (Chapter 8)
- Biological aspects of learning in the
light of the SuperMemo method were analyzed:
- distinction between stochastic
and deterministic learning was
proposed (Chapter 10.2)
- optimum repetition spacing in
stochastic learning was found to be possibly less
dense than that of deterministic learning (p. 95)
- illustrative, hypothetical models
of neural circuitry involved in stochastic
and deterministic learning were
described (p. 106)
- arguments for the presynaptic
character of the facilitation in case of stochastic
learning were listed as well as
arguments for heterosynaptic facilitation in deterministic
learning (Chapter 10.2)
- discussion of the nature of
short-term and long-term memory was included
(Chapter 10.1 and 10.3)
- new arguments for the postsynaptic
membrane as the location of long-term memory were
put forward (Chapter 10.3)
- E-factors were
proposed as a reflection of the number of
synapses involved in remembering particular items
(Chapter 10.4.1)
- existence of at least two
components of memory was postulated and
demonstrated: retrievability and
stability (Chapter 10.4.2)
- phosphorylation of proteins was
considered as possibly responsible for retrievability
(Chapter 10.4.3)
- the number of postsynaptic
receptors was considered as possibly responsible
for stability (Chapter 10.4.3)
- Possible future applications of SuperMemo
were outlined (Chapter 12). As an illustration, software
supervising a touch typing training was described (p.
87). A simple method for using SuperMemo in learning to
play musical instruments was presented (p. 92). Universal
nature of learning based on repetition spacing was
suggested (p. 165).
- The mere existence of the SuperMemo METHOD
refutes or calls in question a pretty large number of
common sense conceptions and dogmas of the psychology of
learning. The most prominent examples are listed below:
- opposition of memorization to
logical thinking is pointless. Memorization (or
according to my terminology deterministic
learning) lays ground for the refinement
of the circuitry of the brain which is later on
used in the process of thinking (p. 167)
- ever-lasting memory acquired by a
single learning act is unlikely. Cases of
supernatural memory refer to either short-term
memory, mutant individuals or must be otherwise
seriously reconsidered [Luria, 73] (p. 168)
- time necessary to learn a given
material is proportional to the first, not second
power of the size of the material. This refers
only to long-term memory and properly spaced
repetition process (p. 169)
- forgetting has a biochemical
nature (trace-decay theory) and is only partially
caused by interference (interference theory).
Proper application of the minimum
information principle, principle
of univocality, mnemonic techniques etc.
allows to one to reduce interference to a
negligible level (Chapter 10.4)
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