Subset learning

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Revision as of 11:27, 26 October 2013 by SuperMemoHelp (talk | contribs) (Review modes: Wikification)
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Subset review is a review of a portion of the learning material (e.g. before an exam). The portion may be identified with search, by branch selection in Contents, by category, and other means that determine a subset of elements. The reviewed subset material may be sorted by its sequence in the knowledge tree (Contents), priority, difficulty, interval, retention, recency, etc.

Review types

Search and review

Search and review in SuperMemo is a review of a subset of elements that contain a given search phrase. For example, before an exam in microbiology, a student may wish to review all his knowledge of viruses using the following method:

  1. search for all elements containing the phrase virus (e.g. with Ctrl+F)
  2. review all those elements (e.g. with Ctrl+Shift+L)

The review may include all subset elements (e.g. Learning : Review all in the browser with Ctrl+Shift+L), or only the elements that are outstanding for review on that particular day (e.g. Learning : Learn in the browser with Ctrl+L). Before you execute the review, you can randomize the review material (Ctrl+Shift+F11), sort it by priority, by recency, by interval, by size, by age (in the learning process), etc. You can also apply your default sorting criteria with Ctrl+S in the browser. All forms of review run on all elements except for (1) dismissed elements and (2) those elements that have already been processed on this particular day. The latter condition makes sure that you can do a comprehensive review in various subsets without duplicating your work on a given day. You can overcome the block of double review on a given day by using Add to outstanding (see below).

Search : Find elements makes it possible to define OR-searches and to save search definitions. This way you can, for example, choose a set of terms that define your "diabetes" subset and use them each time you want to review your "diabetes" material.

The parameter Subset in the Statistics window indicates the progress of repetitions in subset learning. This field displays the number of items, the number of topics, and the number of pending elements in subset learning. The name in the parentheses describes the currently processed subset.

Branch review

In the simplest case of branch review, the button Learn at the bottom of the contents window can be used to execute outstanding repetitions on a selected branch of the knowledge tree. For example, to make repetitions in the Medical Sciences branch, click that branch and then click Learn. Using Learn in the contents window is like using Learn in the element window, except only elements belonging to the selected branch will be considered in making repetitions.

To thoroughly review a branch of knowledge (including non-outstanding elements), do the following:

  1. Select the branch in Contents
  2. Choose Learning : Review all on the Process branch> menu (Ctrl+Shift+L)

Random review

To randomly review a branch or a subset:

  1. open the branch or subset in the browser
  2. randomize the content of the browser (Ctrl+Shift+F11)
  3. execute a review (e.g. Learning : Review all on the browser processing menu)

Review modes

In a browser subset, in a contents branch, or in the entire collection, there are 3 main ways of executing subset review:

  • review only the outstanding material: Learn (Ctrl+L) will execute only the outstanding repetitions, i.e. the elements that have been scheduled for review today or before today
  • review all the material: Review all (Shift+Ctrl+L) will execute all outstanding repetitions as well as force mid-interval repetitions on all elements in a subset (except those elements that have already been reviewed today). Review of non-outstanding elements is equivalent to Learning : Execute repetition (Shift+Ctrl+R) available from the element menu
  • review all topics: Review topics works like Review all but it does not include items, i.e. it forces a review of all topics in a subset (except topics that have already been reviewed today). Each time you do subset review on a set of items, you add some extra time to the total cost of learning of that portion of the material. This is why you may wish to exclude items from a review that occurs often

All the above options are available on Process branch> : Learning submenu of the contents menu, or Process browser> : Learning submenu of the browser menu.

Adding elements to the learning queue

Instead of spending your time on a thorough review of a branch or

subset, you may prefer to intersperse the review material in your standard learning process. You can do it with Add to outstanding.

Add to outstanding
is a rationalization

upon two extremes:
  1. well-timed incremental learning (or classical spaced repetition)
  2. subset review (e.g. before an exam)
On one hand you can

proceed with your outstanding queue, on the other, you can smuggle some subset review in between. For example, you might learn about the superiority of "intermittent fasting" over "fasting". You will want to investigate the subject to perhaps employ it in your lifestyle. However, you do not want the subject to be buried in thousands of articles you keep reading. Nor do you want it to monopolize your learning time on a given day. You can import several articles on intermittent fasting and spread them sparsely in your outstanding queue with Add to outstanding. By the end of the day, you will have a peek at all those articles, have them all well prioritized, and integrated with the learning process (in proportion to the value of the newly discovered content).

An alternative to Add to Outstanding is to use Spread priorities, however, it has two flaws:

  • you will not get the instant gratification from the instant review of a hot topic
  • you risk that new imports will displace the articles of interest before you manage to give them a preview
In other words, Add to

outstanding is a more extreme version of Spread priorities, but not as radical as Learning : Spread in the browser (irreversible

rescheduling), or subset review (reversible review).

Repeating items before topics

If you ever neglect learning, you may wish to unload your

item backlog ahead of your topic backlog. You can optimally do it with a change to your sorting criteria. However, you can also start your day from

100% item repetitions:

  1. Choose View : Outstanding
  2. Sort repetitions by type (items first), or choose Child : Items
  3. Choose Learn on the browser menu to make repetitions (or Tools
    Save repetitions on the same menu to make the sorting

Ideally, in incremental reading, you should have items and topics mixed up. This will help you achieve balance between retention of the old material and the inflow of the new material. By working with items first, you risk slowing down learning by working on high retention. That's a step back to classical SuperMemo.

Semantic review

If you want to semantically connect a group of elements related to a single subject in incremental reading, you can use subset review based on the elements tree structure created in the incremental learning process. This way you can quickly review all elements related to a topic whose "big picture" became hazy.

  1. go to any element that makes a part of the knowledge structure related to given problem
  2. use the reference link button on the navigation bar to get to the original article
  3. use Contents to find a relevant subbranch (or stay at the root of the article to review it all)
  4. browse the selected branch (Ctrl+Space)
  5. choose Learning : Review all to review all elements in the logical/semantic sequence (the sequence of branches reflects the order of processing of individual paragraphs in the article)

You can also choose Learning : <a title="Element menu" href="" target="_blank">Learn branch</a> on the <a title="Element menu" href="" target="_blank">element menu</a> to begin branch learning for one of the ancestors of the currently displayed element. You can use this method if you encounter interesting material that you would like to refresh more thoroughly before you proceed with your standard learning process.


Advance is not a form of review. However, it makes it possible to shorten the intervals and speed up the review. For example, if your exam comes in 100 days, you can shorten all intervals in a subset to less than 100 days with Advance.

The Advance operation will not work on two kinds of topics:

  • those whose interval is shorter than the advance interval
  • those who have been repeated today (use Add to oustanding if you need to go around this limitation)


Example 1

If you would like to review the material related to Auguste

Comte (1798-1857) do as follows:

  1. Press Ctrl+F and paste Auguste Comte in the search box
  2. Press Enter or click Find (this will search your collection and open a browser with the results)
  3. Choose one of the subset learning options:
    • to prevent forgetting: press Ctrl+L or choose Process browser : Learning : Learn to review only the outstanding material. This will help you review only the items that are most likely to be forgotten and a portion of topics that have been scheduled for review for today
    • to learn new things: choose Process browser : Learning : Review topics to review all topics related to Auguste Comte
    • to maximize the review (e.g. before an important deadline): choose Process browser : Learning : Review all to review all topics and to force a repetition on all items related to Auguste Comte. Remember that premature review of items may paradoxically slow down your long-term learning

Example 2

If your history exam is approaching and you cannot cope with all

repetitions in the collection, make sure that at least your daily portion of history is thoroughly reviewed:

  1. Select History branch in the <a title="Contents window" href="" target="_blank">contents window</a>
  2. Click Learn at the bottom of the contents window


the procedure daily. However, in the last 3-5 days, you could follow that yet with Process branch : Learning : Review all to protectively refresh the material that would optimally be scheduled after the exam. Important! This strategy is not recommended for long-term learning! It departs from the optimum timing for review to consolidate memories. It should only be reserved for situation when burning school

situation forces you to neglect your long-term planning.

If you have final drill enabled, remember that subset learning does not keep a separate final drill queue and elements that score less than Good (4) are put to the global final drill queue.