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How autopostpone affects the learning process.

August 9, 2009
  • Autopostpone should always be on – with conservative options set.

  • Using autopostpone intermittently will make huge deleterious effects on your collection.

Faithful to the GTD management I’ve been trying to develop since a couple of months, a recurring theme about postponing and management of overload came to my focus of interest again.

I’ve always mistrusted leaving my learning processes on absolute autopilot by auto-postponing them, hence I’ve written about this issue before. Today I have a new understanding about what to do and not to ever do when dealing with auto-postpone (postpone for individual branches or subsets is not taken into account in this post).

In order to acknowledge the influence of auto-postpone in the items intervals by supermemo and excel table was constructed. At first I wanted to see a whole lot of combinations of parameters. But for simplicity sake, a single example table is showed  here.

AutoPostpone intervals by number of postpones

AutoPostpone intervals by number of postpones

The individual intervals and delay factor will of course be different if other parameters are set, in any case I’ll be showing the intervals used in my collection.

Rows show in dark brown the intervals set by supermemo in each postpone (columns), light brown shows the degree of delay (used/optimal interval).

A delay of 2.0 means that the interval set is double of the ideal, 3.0 means triple long interval, etc.

Supermemo establishes the recall probability for each item during repetitions, and this recall probability is directly proportional to the degree of delay, but is influenced by the forgetting index, so this makes comparisons of the probability of recall also relative to preffered parameters.

For a Forgetting index of 20%. A delay of about 2.0 has a recall probability of 84%, and 3.0 has 73% probability, and 4.0 has 64%. So a higher index of delay means, you have to go back to square one on the learning process of the items at hand.

Before, I had autpospone turn off, mainly because I didn’t understand how the postpone parameters affected my learning process by modifying the intervals for the outstanding items and topics. This is no longer a limitations, and in fact I would recommend turning on autpostpone and living it that way afterwards.

Using autopostpone for a couple of weeks or months and the turning it of for another interval of time, and going back again to autopostone will make huge deleterous effects on your collection. Let me show you what I mean.

Lets start by setting a postpone factor of 1.1, max delay of 10, max postpones to 8, and starting optimal interval of 4. Autopostpone will set higher intervals if you do manage to make the repetitions until the item is opstponed 5 times or more.

Optimal Interval = 4
1º postponed interval = 5
2º postponed interval = 6
3º postponed interval = 7
4º postponed interval = 8
5º postponed interval = 9
6º postponed interval = 10
7º postponed interval = 12 (Intervals are set to next whole number, ea. 1.2 = 2)
8º postponed interval = 14 (Intervals are set to next whole number)

Here an item will have an interval of 14 on the 8th postpone, then it will not be postpone any further, here will assume that 4 weeks after 14th day, you finally make a repetition on this item taking an interval of 42 days (14+28).

If you turned of the autopostpone after the 2th postpone, but still don’t make a repetition on this item and before the 42th day you turn on the autopostpone, and by then you would normally (like in the first case) make the a repetition on this item, but because of having turned off before autopospone it will get postpone (until 8 postpones are made, in this example) according to the folowing values.

Optimal Interval = 4
1º postponed interval = 5
2º postponed interval = 6
42th day: autopostpone turned on
3º postponed interval = 42+4.2=47
4º postponed interval = 47+4.7=52
5º postponed interval = 52+5.2=58
6º postponed interval = 58+5.8=64
7º postponed interval = 64+6.4=71
8º postponed interval = 71+7.1=79

Then by not using autopostpone all the time, when you finally get to make a repetition on this item, its interval has gone up to a delay of 19.75 (79/4). Having autopostpone set all the time you get delay of 10.25, still high but not as harmful to your probability of recall as when you use autopospone intermitently. When autopostpone is set on and off more then once the effects are even larger.

How on earth did I got intersted in finding out about this postpone issue. Obviously because I did turn on and off autopostpone as I learned how to set the correct parameters (for my own requirements), only to find out it did make things worst. I started to check if there where items which had last repetition dated more then 30 days ago and that had one repetition (recently entered to the learning process, or mistaken on the last repetition) or two (meaning not yet consolidated). To my surprise many items where repeated more then 400 days ago, with only one repetitions done, and most importantly those where valuable data.

Botton line – Don’t mess with autopostopone use it all the time or never.
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