[Parley-devel] Features in next version of Parley

Anša Vernerová ansa211 at gmail.com
Thu Aug 28 00:13:46 UTC 2014


> You mean your confidence levels. :) Anyway, real testing by a dedicated
> learner would be worth a lot. Can you build Parley from the sources?

I will give it a try (during the weekend).

> Not sure what you mean with 'translation' here. All of the other 4
> variations are translations of different kind. What we have discussed is to
> generalise the confidence concept so that you can set separate confidences
> between the same words but using different training methods - recognizing a
> spoken word vs being able to write and spell it is a simple example.

I understand it so that the confidence levels are assigned to an item
in the target language L2 under the following scenarios (L1 being the
known language and L2 and L3 target languages):

reading:             L2.text -> image/L1
      the learner understands the intended meaning from text, but
possibly cannot pronounce it nor express in L3
listening:            L2.sound -> image/L1
     the learner understand the intended meaning from sound, but
possibly cannot correctly spell it
writing:              image/L1 -> L2.text
    the learner can write down the word corresponding to a given
meaning, but possibly not pronounce it correctly
speaking:           image/L1 -> L2.sound
    the learner can produce the correct sound for a given meaning, but
possibly not write it down

So far, these can be seen as "passive" and "active" grades for the
different aspects of a vocabulary entry (reading = "L2.text.passive",
listening = "L2.sound.passive", writing = "L2.text.active",...) Not
sure about "translation" either.

In the following scenarios, in case of a failure to produce the right
answer, the learner has to indicate which confidence level should be
L2.text/L2.sound -> L3.text/L3.sound     (the problem may be both on
the L2 and on the L3 side, user clarification is necessary, then the
confidence levels for the passive skill of L2 and the active skill of
L3 can be updated)

At an initial stage of learning, the learner might also want to
practice just the following two scenarios. Should they have their own
dictation:            L2.sound -> L2.text
      the learner knows how to capture the sound in writing, but
possibly does not know what it means
pronunciation:     L2.text -> L2.sound
      the learner remembers how to pronounce the word, but possibly
not its meaning

>> Pregrades are currently 6 Leitner levels below the first visible one
>> in the user interface. They have testing intervals from 3.5 minutes
>> up to 8 hours. Inge implemented them.
> Yeah... The original Leitner system had an interval of 1 day until next time
> training a word once you got it right the first time. That was much too long
> so you forgot almost every word until it was time to train it again.

Oh! I have parley set up so that the blocking threshold of Level 1 is
just 4 hours, not 1 day :-) But what you are saying is that the
Blocking threshold for Level 1 has been replaced by hard-coded
implementation of pregrades.

If I am right that pregrades are applied below/at Level 1, then
getting the word right the first time still skips the pregrade part
(an unknown word marked as right on the first occasion I see it goes
to level 2). Which I suppose is the kind of behaviour that one would
want. (No need to get extra practice for a word which was answered
correctly.) It definitely sounds much more intriguing than the "three
consecutive right answers" version.

> I have been searching for some research about the optimal timer intervals.
> Like you I have a feeling that the current ones are too short, especially
> the higher levels. But I have found nothing to indicate any better values.
> Do you know of any?

No, just the 80-95% rule of thumb, and the experience that I often
reach those levels even if I skip practice for a long time and then
come back to my collection. (Obviously, this does not hold for the low

>> As you also noted compound structures are a very effective way to
>> reinforce multiple words in one training event. I would like to track
>> the words individually within such constructions. For example for writing
>> the sentence, "The dog chased the cat", the student should get credit
>> for: the, dog, cat, to chase, past tense conjugation and SVO order. I
>> would
>> like to see lesson plans with a threshold, that once crossed starts
>> presenting the user with more complicated compound structures
>> while they still see their performance improve on the basics individual
>> words.

> This is a whole new ballpark, though. It's a very intriguing thought but I
> would like to read a little research about it before we get it into Parley.
> There is a risk that it becomes too complex.

Yes, I have also been pondering this idea of tracking individual words
and bits of grammar but practicing full sentences. I always came to
the conclusion that, as a parley user, I prefer wasting some time by
not optimizing, than wasting a lot of time by tagging each sentence
with a list of words and grammar points that it contains.

I think this would be a great idea for an innovative commercial
product. After all, Computational Linguistics provides tools (at least
for some languages) that could do the tagging for the user. But what
about users who are learning uncommon languages? (I am not fond of
automatically generated content in language learning. It is fine for
sentences like "I am Jane/Mary/John/Adam/..." But even just for
sentences like "John entered the car/bus/train.", one has to have some
kind of ontology telling them that "car", "bus" and "train" are
vehicles and that "PEOPLE enter VEHICLES", something like
http://en.wikipedia.org/wiki/WordNet#Knowledge_structure and
http://www.pdev.org.uk/ ... To put it simply, computers are not good
enough in speaking human languages (yet) for producing sensible output
that students could learn from.)

BTW, do you know how often people use some of the more complex
features of parley? E.g., how many of the files uploaded to the common
repositories have word types, inflection, synonyms etc. filled in?
This could give some estimate of how many users would actually use
some more complex feature such as you are describing.


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