Difference between revisions of "Glossary"

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Revision as of 20:41, 3 October 2013

Glossary:Access mode

acquisition rate
speed of learning, usually expressed in items memorized per year per minute. For example, if 20 minutes a day result in memorizing 10,000 items a year, the acquisition rate is 500 elements/year/min (10,000/20). In SuperMemo, the acquisition rate may vary from 30-1000 items/year/minute depending on the difficulty of the material, forgetting index and the stage of the process. Acquisition rate may decrease substantially in the first year only to stabilize asymptotically as years pass by. See formula
active recall
process in which pieces of information are actively retrieved from memory as opposed to passive review. For example, in passive review one might read that the highest divorce rate occurs in the 4th year of marriage. In active recall, you would have to retrieve this information from your memory: In which year of marriage are couples most likely to divorce? If you answer correctly, "4th year", then your memory stability will increase and so will the probability of recall in the future. In passive review, this increase is dramatically less pronounced. In literature, in various contexts, active recall may be referred to as practice at retrieval, active learning, learning based on a testing effect, retrieval practice, test-enhanced learning, active repetition, and more. Active recall may be or is not prompted with a specific question. It can then be called cued recall or free recall respectively.
A-Factor (absolute factor; AF)
number associated with every element in a collection. A-Factor determines how much intervals increase in the learning process. The higher the A-Factor, the faster the intervals increase. You can see A-Factors in the Element data window. For items, A-Factors reflect item difficulty. For topics, A-Factors modulate topic priority (by affecting the frequency of exposition). The higher the A-Factor the easier the item. The most difficult items have A-Factors equal to 1.2. For items, A-Factor is defined as the quotient of the second optimum interval and the first optimum interval used in repetitions (read more: SuperMemo Algorithm SM-15). For topics and tasks, A-Factor is interpreted as the number by which the current interval should be multiplied to get the value of the next interval (as it was the case with E-Factors in early versions of SuperMemo).
ancestor (ascendant)
element in the Contents window that is located one or more levels above the element which makes its descendant. All the elements at the same indentation in the knowledge tree are children of their single parent (they are siblings to each other) whereas descendants are all the elements below the level of their ancestors.
See also:
auto-postpone
option available with Learn : Postpone : Auto-postpone (from the main menu) that makes sure that excess repetitions are automatically postponed before the learning begins. Auto-postpone uses user-defined criteria in choosing elements that should be postponed. Most importantly, high priority material is protected from being postponed. Auto-postpone affects only the material that has been left outstanding from previous days. It does not postpone repetitions scheduled for the current day until the next day of learning.
auto-sort
option available with Learn : Sorting : Auto-sort repetitions (from the main menu) that makes sure that repetitions are sorted by priority (if it is checked)
back-retention
outdated term for consolidation in previous versions of SuperMemo
binary component (program component)
component that can hold, preview or execute a binary file stored in any format or written in any language (e.g. EXE, PDF, CHM, etc.). Binary components make it possible to extend the range of applications of SuperMemo into any imaginable area. To prevent the automatic execution of binary components, make sure that AutoPlay is unchecked on the element menu
branch
in the Contents window, an element in the knowledge tree with all its descendants (incl. its children). All elements in a branch can be processed with subset operations. For example, if you would like to review your physics material before an exam, you could select the Physics branch in the Contents window, and click Learn (Ctrl+L) at the bottom of the window. You can add new branches with Add and Insert (Ins) in the Contents window. A branch that is built automatically by adding elements to a concept is called a concept group. All concepts are associated with their own branches/groups. By analogy to Windows, when a branch has no content and is use solely to hold other branches or elements, it may be called a folder.
See also:
browser
window with a subset of elements. Browsers are mostly available from the View menu and provide a set of operations available from the browser menu. Read more: Browser window
burden
in the Statistics window, a number which estimates the average number of elements that have to be repeated daily (this statistic may overestimate the workload in collections where Postpone is used often):
burden = 1/I1+1/I2+ ... + 1/In
where:
category
predecessor of concepts in older SuperMemos. No longer used in SuperMemo 17. A category used to mean a named branch of the knowledge tree to which elements belonging to a given class of knowledge were added. For example, you might have kept categories such as: General Knowledge, Family, Internet, Job, etc. Now you can accomplish the same with concepts
child
element in the Contents window that is located one level below the element which makes its parent. All the elements at the same indentation in the knowledge tree are children of their single parent (they are siblings to each other). Descendants are all the elements below the ancestor level. In incremental learning all knowledge extracts and clozes are created as children of their source.
See also:

Glossary:ClipBox

cloze deletion (cloze question; cloze item)
item in the fill-in-the-blanks form. In cloze deletions, the question is replaced by three dots ([...]) and moved to the answer field. For example:

Q: The highest literacy rate in Africa has been reached in [...](country)(2009)?
A: Seychelles (93%)

Cloze items can effectively remedy knowledge complexity. If you have items that persistently cause recall problems, try using cloze deletion. SuperMemo simplifies creating cloze deletions by providing options such as:
Read more: Incremental reading
collection
learning material used in SuperMemo. A collection is made of single pieces of knowledge called elements. The simplest elements have the form of a question and an answer. A collection of a given name is stored in a folder/directory that bears the same name, and all its important statistical and learning data are stored in a file with the extension kno. In older SuperMemos, collections of elements were called knowledge systems (SuperMemo 8) or databases (SuperMemo 7 and earlier)
component
a container for objects placed within the visible field of an element. Components can contain texts, pictures, videos, PDF files, etc. They can also have a form of a shape, spell-pad, or script. You can add new components with Edit : Add components on the main menu, or by using the Compose toolbar at the bottom of the element window
consolidation
retention of material repeated on a given day D as measured on the days of successive repetitions of individual elements. Both retention and consolidation are displayed in Toolkit : Calendar under Retention. Calendar displays these values as <retention> -> <consolidation>. If you are sleepy or tired on the day D, your retention will be poor, even if your memories are strong. In other words, measured retention is not an ideal reflection of memory retrievability. Consolidation is not measured on a single day. The measurements are gradually added up on days on which successive repetitions of the material repeated on the day D take place. Consequently, consolidation is less dependent on the variability in your recall readiness. At the same time, being tired or sleepy on the day D can affect the consolidation of the material. It is retention that is less dependent on the variability in your consolidation readiness
Contents window
window that displays the hierarchical structure of knowledge in a collection. That structure is called the knowledge tree. It is available by clicking Contents in the element window. Read more: Contents

Glossary:Database

delay
degree of delay of an element in the learning process. For items, it equals the current interval divided by the optimum interval for the current requested forgetting index. For topics, delay is heuristically scaled to provide for comparable degree of delay in terms of the damage inflicted on the learning process
descendant
element in the Contents window that is located one or more levels below the element which makes its ancestor. All the elements at the same indentation in the knowledge tree are children of their single parent (they are siblings to each other) whereas descendants are all the elements below the ancestor level.
See also:
D-Factor
decline of O-Factors with successive repetitions can be approximated with a power curve that begins at O-Factor that equals A-Factor. D-Factors are no longer used in SuperMemo Algorithm. When a power regression is used to compute O-Factors on the basis of R-Factors for successive repetitions in a single A-Factor category, the decay constant of the resulting function is called a D-Factor. You can see individual D-Factors for all A-Factors in Toolkit : Statistics : Analysis : Graphs : D-Factor vs. A-Factor. The larger the D-Factor the faster the decline of O-Factors with each repetition. This means that large D-Factors imply more frequent repetitions in a given difficulty category. Naturally, over time, D-Factors tend to be lower for easy item categories (unless O-Factors hit their minimum value of 1.2 for very difficult items). D in D-Factor stands for decay (it is a decay constant of the negative power function)
difficulty
estimation of item's difficulty in SuperMemo. The three main measures of difficulty:
  1. current estimation of item's difficulty computed by Algorithm SM-18. This number ranges from 0 (for easy items) to 1 (for difficult items). It is displayed as Diff in the Element data window (see: details)
  2. current estimation of item's absolute difficulty estimated by Algorithm SM-15. This number ranges from 1.2 (for difficult items) to 6.9 (for easy items). It is represented by A-Factor and displayed as A-Factor in the Element data window. This value reflects bounded stabilization for first review executed at optimum interval
  3. heuristic measure of difficulty based on selected item data, and displayed in the Element data window as Old (this measure can be used to sort collections that are to be used by other users; starting with easy items first)
Dismiss
operation that removes an element from the learning process (compare with Forget and Remember). Dismiss leaves the element in the collection, however, it never shows up when using Learn

You can use Dismiss for the following purposes:

  • Removing parenting articles from incremental reading while keeping them as reference
  • Keeping searchable archive of knowledge that became outdated
  • Converting topics to tasks (e.g. for prioritized entry into incremental reading), etc.
dismissed element
element that is not memorized, is ignored in the learning process, and is not kept in the pending queue. A dismissed element can be re-memorized with Learning : Remember (Ctrl+M) on the element menu. Priority of dismissed elements is ignored (at Dismiss it is set to 100%).
dragging mode (drag&size mode)
state of an element/component, in which the component(s) can easily be resized or dragged to a new location in the element window. The other two basic modes are: presentation mode (components are displayed like during repetitions) and editing mode (components can easily be edited, e.g. by typing in new texts, etc.). Components in dragging mode are usually darker than in the other two modes. To enter the dragging mode, Alt+click the component or the element. You can also press Ctrl+E twice. To drag a component in the dragging mode, press the mouse button over the component, and, without releasing it, move it to a new location within the element
editing mode
state of an element/component, in which it can easily be edited (e.g. by modifying the texts). All components except for HTML components can also be resized in the editing mode. The other two basic modes are: presentation mode (components look the same way like during repetitions) and dragging mode (components can easily be dragged with the mouse). The easiest way to distinguish between presentation and editing modes is that in the latter the components are enclosed by a sizable rectangle (except for the HTML component, which may instead be marked by a bluish status border). To enter the editing mode, press Ctrl+E
E-Factor (easiness factor; EF)
number related to the difficulty of a given element in early versions of SuperMemo, up to and including SuperMemo 7. In the earliest versions of SuperMemo (up to and including SuperMemo 3), new inter-repetition interval was determined by multiplying the old interval by E-Factor. A-Factors associated with topics and tasks are used in the same way as early E-Factors, i.e. to determine the value of the new interval by multiplying the A-Factor by the old interval. To better understand the role of A-Factors in new versions of SuperMemo, see: Incremental reading
element
single page of information stored in SuperMemo (e.g. an article, a question-answer pair, etc.). All elements kept together are called a collection. Elements may have the form of topics (articles, extracts, summaries, etc.), items (testing material), concepts (general ideas used in semantic learning), or tasks (elements representing to-do jobs). A topic presents a larger part of the learning material, e.g. an article about the greenhouse effect. Items provide specific testing questions, e.g. How thick is the cerebral cortex? In the simplest case, topics have the form of a page of text while items are formulated as questions and answers (see: Topics vs. Items). Every element is represented in the Contents window as a single leaf or branch of the knowledge tree. The content of individual elements is displayed in the element window. Read more: Items, topics, concepts, and tasks
element browser
see browser
element subset
set of elements. Subsets are often saved into files with the default extension sub. You can create an element subset file by using the element browser (e.g. Subset : Save all or Select : Save selection in the browser menu). You can view an element subset file with View : Subset from the main menu. Read more: Using subsets
element window
window that displays a single element in a collection. In the default state this window displays buttons Contents, Search, History, etc. in its navigation bar along the top, as well as Learn, Add new, and the control bar at the bottom. Read more: Element window
filespace
system of folders for holding multiple files in SuperMemo. Folders in the filespace are organized using a complex algorithm that ensures a minimum folder nesting and minimum access time. Files in the filespace are named 1.*, 2.*, 3.*, etc. Folders and subfolders are named [1], [2], [3], etc. Individual files are placed in individual slots. All files have their extensions retained (e.g. *.htm, *.jpg, *.mp3, *.mp4, etc.). The filespace is held in the subfolder called [ELEMENTS]. When using individual files, SuperMemo usually opens them directly from the filespace. Some files may need to be modified before they are displayed in SuperMemo. Those files are copied to a temporary folder first. The formula for converting filespace slots to folder names is complex and it is easier to search files by their slot names. For example, to find the file in the slot #279310, search [ELEMENTS] for 279310.*. That particular slot falls in the following subfolder: <collection name>\ELEMENTS\30\30\30\ as ELEMENTS\30\30\30\279310.*. Filespace is used in all SuperMemos starting with version 8. In SuperMemo 17, the filespace is limited to 4 folder levels and to 8 million files (exactly: 8,379,310).
filespace slot
single place for a single file allocated in the filespace in the [ELEMENTS] subfolder. For example, when allocating space for 300,000 files, SuperMemo may place a JPEG image file #288846 in the following slot ELEMENTS\1\2\3\4\288846.jpg
final drill
last (optional) stage of the learning process on a given day, in which only items that scored a grade less than Good (4) are repeated as long as they continue scoring less than Good. On the next day, final drill queue is again shifted to the end of the learning day. The final drill stage is not executed if Toolkit : Options : Learning : Skip final drill is checked. Unused final drill queue is deleted after 3 days, and can also be deleted manually. To delete the final drill queue, use Learn : Cut drills from the main menu
flashcard (card)
term often used by users of SuperMemo to refer to an item or an element
Forget
operation that removes an element from the learning process and places it at the end of the pending queue (compare with Dismiss and Remember)
forgetting curve
SuperMemo: Toolkit : Statistics : Analysis : Forgetting Curves graphs for 20 repetition number categories multiplied by 20 A-Factor categories
describes the decline in the probability of recall over time. A forgetting curve graph in SuperMemo shows how fast the memorized information gets forgotten. A forgetting curve graph shows time on its X axis, and percent recall on its Y axis. It can be viewed with Toolkit : Statistics : Analysis : Forgetting Curves. SuperMemo collects 400 forgetting curves for 20 levels of knowledge difficulty and 20 levels of memory stability.
forgetting index
proportion of elements that are not remembered at repetitions (usually expressed as percentage). The forgetting index can be programmed to fall between 3% and 20%. This way, the speed vs. retention trade-off in learning can be controlled by the student. You can set the default forgetting index with Toolkit : Options : Learning : Forgetting index (default) and individual element forgetting indices with Forgetting index in the Element parameters dialog box. To understand the difference between the requested, measured, default, individual, expected and the estimated forgetting index, see: Forgetting index
free running sleep
sleep that is not artificially regulated. Free running sleep is a form of chronotherapy that can be used in curing a number of sleep disorders. Most of people in the industrial world cannot afford free-running sleep. Only a small proportion of population can sleep in a perfect 24 hours cycle and in synchrony with duties such as work and family. The most typical violation of the free-running sleep is the use of an alarm clock. Another violation is going to sleep too late in reference to one's natural bed-time hour. Going to sleep late in condition of little sleepiness does not violate the free-running sleep principles. Going to sleep too early (e.g. to force longer sleep before early arising) may also disturb the free-running sleep cycle. See also: Good sleep for good learning

Glossary:Full access mode

grade
number from 0 to 5, which you provide when scoring your performance in recalling an item in learning. If you have an excellent recall of the item, you will score your review at 5 (grade 5 is called Great by default). If you perform poorly, you will score 1 (called Bad by default). You can even issue a Null grade of 0 from the keyboard if you perform dismally.
Note that the term first grade refers to the grade issued at first repetition (i.e. Repetitions=2), not at memorizing (i.e. Repetitions=1). The first issued grade does not affect the learning process except for determining which items enter the final drill
graphic cloze deletion
see occlusion test
graphic deletion
see occlusion test
hierarchy
see knowledge tree (outdated term that might be found in some older documentation files)
hierarchy node/branch/leaf
see node, branch, or leaf (hierarchy is an outdated term that might be found in some older documentation files)
hint
message that makes it easy to understand the use of a given interface element in SuperMemo. To view hints pause the mouse pointer over a button or menu item. Hints are displayed on the status bar along the bottom of the screen (you can show the status bar with Window : Status bar from the main menu).
You can turn hints on/off by:
  1. checking Window : Hints, or
  2. double-clicking the hint panel on the status bar
hook node
place that determines where new elements are added in the Contents window (e.g. with Add new). A hook is a knowledge tree node to which new elements are added (as children). The hook node is either the same as the root node, or is a child of the root node, or is a descendant of the root node. Once the children limit of a hook is passed, a new hook is chosen. The newly chosen hook is always a descendant of the root of the current concept group. If SuperMemo runs out of branches that might become new hooks, it will restructure the concept branch and start a new level of branches under the root node with new space for new hooks and new elements.
hyperlink
connection established between a component and an element different than the element owning the component. Hyperlinks make it possible to navigate in knowledge hyperspace by clicking individual components or HTML links. You can set a hyperlink by using Links : Hyperlink on the component menu or Insert HTML Link : Element on the HTML component menu
incremental reading
reading technique pioneered by SuperMemo, in which you can read hundreds or thousands articles at the same time with substantial benefit to the speed of learning, and the quality of acquired knowledge. See: Incremental reading
incremental video
technique of watching and/or learning multiple YouTube and local videos at the same time. Incremental video is to video as incremental reading is to texts. See: Incremental video
interval (inter-repetition interval)
period of time between successive repetitions. In incremental reading, intervals are also periods between the review of topics. Initially, repetitions occur in intervals ranging from 1-15 days; however, with time, intervals can reach well into thousands (which corresponds to decades). Intervals in SuperMemo are measured in days. Occasionally they may be displayed as seconds (if they are very short), or years (if are very long), or with the use of other units
item
simple element, which often has a form of a question and an answer. Items ensure long-term recall of information. Items take part in active learning, which is opposed to passive review or reading (done with the help of topics). Items are often created by means of cloze deletion. See also: Topics vs items
knowledge tree
the tree structure in which particular elements of a SuperMemo collection are organized. The knowledge tree is presented in the Contents window. Particular nodes of the tree can hold up to a thousand children each, but for performance reasons it is recommended not to keep more than a hundred children elements in a single node. Some authors use the term knowledge hierarchy to refer to the knowledge tree.
See also:

Glossary:Knowledge system

lapse
memory lapse is a failure to recall an item. When we say "number of lapses", we mean the number of times an individual item has been forgotten, i.e. scored less than Pass (3) in repetitions
layout
position and size of windows and toolbars in SuperMemo. Layouts can be changed with Window : Layout menu. In particular, use Ctrl+Shift+F5 to save your favorite layout. 9 first-defined layouts are accessible through the Window menu. There is no need to save layouts for Contents and browser layouts as they are saved automatically. Find out more: Layouts.
Compare: Template
leaf
one childless element in the knowledge tree presented in the Contents window (an item, topic, concept or task in the collection). You can add new leaves with Add and Insert (Ins) at the bottom of the Contents window, or with options on the Edit submenu of the main menu.
See also:

Glossary:Learn-only mode

leech
particularly difficult item that causes problems in learning. The definition of a leech is specified by means of the Element filter dialog box used in View : Other : Leeches (Shift+F3) from the main menu. A semi-leech is an item that is not a leech but will become one once it is forgotten. See: Leeches
Leitner system
rudimentary method for spaced repetition used in a number of flashcard applications. The method has been proposed by Sebastian Leitner in the 1970s and can be considered a forerunner of SuperMemo
level
degree of complexity of SuperMemo exposed to users of different familiarity with the program. There are four levels with increasing complexity available from File : Level. These are: Beginner, Basic, Middle and Professional. Find out more: Levels
matrix smoothing
mathematical procedure that converts a matrix of numbers into a "smoother version" (e.g. by averaging the neighboring entries). For example, if the row of the matrix is 1, 2, 3, 4, 666, 6, 7, 8, smoothing might convert it to 1, 2, 3, 6, 99, 9, 8. For more, see: Smoothing
measured forgetting index
proportion of elements that are not remembered at repetitions. This is the forgetting index as actually measured during repetitions. See: Forgetting index
memorized element
element that takes part in the learning process (i.e. is repeated in intervals suggested by SuperMemo). A memorized element can be made a pending element with Forget (e.g. Learning : Forget in the element menu). It can also be made a dismissed element with Dismiss (e.g. Learning : Dimiss (Ctrl+D) from the element menu).
memory lapse
see lapse
minimum information principle
principle of effective learning which says that simple elements formulated for active recall bring much better learning results than complex elements even though one complex element may be equivalent to a large number of simpler elements.
Read more:
mnemonic hyperspace
extension of Tony Buzan's concept of mind maps by application of hyperlinks between the mind map components and mind map editability. Mind maps are considered an excellent form of representing knowledge for the purpose of learning. SuperMemo makes it possible to create simple mind maps that contain multimedia objects. It can also use mind maps generated with Mind Manager (via OLE in-place activation)
node
one element in the knowledge tree presented in the Contents window (a single item, topic, concept or task in the collection). You can add new nodes with Add and Insert (Ins) at the bottom of the Contents window, or with options on the Edit submenu of the main menu. If a node does not have children, it is called a leaf. If the node has children, it is called a branch. If a node is used as a container for other nodes, it may also be called a folder. The contents menu provides some operations on entire branches such as: Learn, Review all, Statistics, etc.
See also:
occlusion test
item that uses a picture whose part is deleted or occluded. During a repetition cycle, the occluded part is exposed at answer time. Occlusion tests can be used to learn geography, anatomy, mind maps, technical graphs, and other forms of knowledge that is presented in graphic form. Also called: graphic deletion test or cloze for pictures.
See also:
O-Factor (optimum factor; OF)
number which tells you how much intervals should increase to reach recall of 90%. O-Factors differ for different levels of memory stability and different item difficulty. They are normalized for the forgetting index of 10%. For the first repetition, i.e. there was no prior interval, O-Factor is assumed to be the same as the first interval (as if the prior interval was 1 day). For the first repetition, different O-Factors are computed for a different number of memory lapses. For example: if the O-Factor is 2.5, and the prior interval was 20 days, at repetition time, the new interval should be set to 2.5*20 days, i.e. 50 days.
optimum interval
in SuperMemo, an inter-repetition interval that is likely to result in the probability of forgetting equal to the requested forgetting index. In other words, the optimum interval is the best possible interval that will ensure the speed of learning chosen by the user
ordinal number
number assigned to each element indicating the designed ordinal position of the element in the collection. Ordinals are important when writing commercial collections. Instead of ordinals, users should use priorities in their own collections. Some collections are sorted by their ordinal numbers and this is the order in which they should usually be learned. Ordinal number comes with a collection, while the priority is set for each element by the user using his or her own criteria. By default, ordinal number is set to the number of elements in the current collection plus 10,000. This way, the first element you add will have the ordinal 10,002, second element will get 10,003, etc. Ordinal numbers are useful in sorting commercial collections or their subsets
outstanding element
element that is awaiting repetition (e.g. to satisfy the criteria of optimum interval). Each element in the learning process has its next repetition date determined by SuperMemo or by the user. On that scheduled review date and later on, the element is considered outstanding
outstanding material
all outstanding elements, i.e. elements whose next repetition date is less or equal today's date
overload
a situation when the student has more outstanding elements to review than they can handle. Few users can sustain more than 200 item repetitions per day (let alone thousands of topic in a heavily overloaded incremental reading process). When the Outstanding parameter (in the Statistics window) starts going above that number, overload is likely. Overload can best be handled with Auto-postpone. However, one-time big loads can be resolved efficiently with Postpone (delaying all elements) or Mercy (spreading all review in time)
passive review
process in which pieces of information are read passively without asking questions (as opposed to active recall). For example, in passive review, one might read that 50% of marriages in the US divorce. In active recall, you would have to retrieve this information from your memory: What proportion of marriages in the US divorce? Active recall is far more effective in learning than passive review. In incremental reading, you always begin with a passive review of the learning material, and then gradually (incrementally) convert its portions to questions and answers suitable for active recall
pending element
element that awaits memorization in the pending queue. To move an element to the end of the pending queue, you can do choose Learning : Remember and Learning : Forget from the element menu (in that sequence)
pending queue
queue of elements that are waiting to be memorized. Option Remember removes the current element from the pending queue while Forget adds a memorized element back to the end of the pending queue. Pending queue determines the order of learning new elements. You can forget all the elements in a given collection by choosing File : Tools : Reset collection. You can also make a subset of elements pending by using options of the browser menu
presentation mode (display mode)
state of an element/component, in which it looks as when seen by the user during browsing or learning the collection. The other two basic modes are: editing mode (components are ready for editing, e.g. deleting texts, etc.) and dragging mode (components can easily be dragged with the mouse)
priority
number that reflects the importance of an element in SuperMemo. Most important elements have the priority 0%, while the least important elements have the priority 100%. Priority can be changed with Priority : Modify (Alt+P) on the element menu. For more, see: Priority queue
priority queue
queue of elements ordered by their priority. Use priority queue to always start from learning the material that is most important for you. Do not despair if you do not finish learning for a day. With priority queue, you know you did your best and only lower priority material was left behind. Remember to use Auto-sort and Auto-postpone to make the most of the priority queue. See: Priority queue
primary storage
place on the user's hard disk where the current collection is located. Compare: secondary storage
Q&A format
format of text files with questions and answers that can be imported to various versions of SuperMemo. See: File : Import : Q&A text
reading list
prioritized list of articles imported to SuperMemo and scheduled for reading in the sequence of priority. A reading list is a form of a tasklist in which each task is an article to read. In new SuperMemos, reading lists have been largely made obsolete by incremental reading

Glossary:Read-only mode

recognition
ability to passively recognize a memory. For example, you may not remember the answer to What is the capital of Sierra Leone?, however, you may recognize Freetown as the capital once you hear the name. Or you can say I knew that once someone tells you that Freetown is the capital of Sierra Leone
Remember
operation that introduces an element to repetitions. Compare: Dismiss and Forget
registry
sorted set of named objects (called registry members) that are used in creating elements in SuperMemo. Objects stored in registries may have the form of text, HTML file, image, sound, video, font, executable program, DLL, PDF file, etc. You can link particular objects with components in elements by means of Links : Registry member (Shift+Ctrl+K) on the component menu. Upon choosing the appropriate object name in the registry, choose Accept and the object will appear within the selected component. Important! Registries in SuperMemo have nothing to do with the Windows registry (SuperMemo have been using registries before the release of Windows 95)! Read more: Registries
registry index
ordinal number of a given member in the sorted order of registry members in a given registry. For example, the lexicon registry might start with aardvark at the registry index 1 and end with Zoloft at the registry index 23293. Registry index can be inspected at the bottom of the registry window. See: registry position
registry member
one of the objects stored in a registry (e.g. a picture in the image registry or a word in the lexicon registry)
registry object
file or a record associated with a registry member. For example, 12363.jpg may hold the picture of the president for the member of the image registry named Barack Obama. Arial 16p may be a member in the font registry that holds the record of properties of a font used in the collection
registry position
number corresponding with the physical position of a given registry member in a registry. This number can be seen at the bottom of the registry window. See: registry index
registry subset
set of registry members saved in a file. Registry subsets are mostly used in search operations. For example, in a registry window, you could use Search : Find texts (Ctrl+S) on the registry menu to find all texts containing the word virus. Those will be displayed as a registry subset in the text registry window. You could use Ctrl+S again to search for the word AIDS and generate a narrower subset that would contain both the words virus and AIDS. Finally, you can use View : Browse selected (Ctrl+Shift+B) on the registry menu to display a browser with all elements that use the members of the selected registry subset
registry window
any of the several windows that display the contents of individual registries. These windows are available on the Search menu (e.g. Search : Texts, Search : Images, Search : Other registries : Font, etc.). Read more: Registry window
repetition
act in which a given item is rehearsed by going through the following stages:
  1. show the question (or the stimulus)
  2. respond to the question (or react to the stimulus)
  3. compare the response with the correct answer and grade yourself (or be graded by the program for your reaction to the stimulus)
Note that all repetitions take place on a date selected by SuperMemo by using the spaced repetition algorithm (see: SuperMemo Algorithm)
repetition category
number that represents the repetition number corresponding to a given interval in the theoretical learning process in which the current status of the OF matrix is used. If you make many repetitions in short intervals (e.g. as a result of mid-interval review), you may have a large repetition number for a short interval. Such repetition number cannot be used in the SuperMemo Algorithm. Instead, SuperMemo will look at the optimum interval and see how many times an item would need to be repeated to reach that interval. That number is called the repetition category
repetition spacing
see spaced repetition
requested forgetting index
proportion of items that you accept not to be remembered at repetition. This is your planned/desired value of the forgetting index. Your actual measured forgetting index depends on systematic work and the formulation of knowledge in learning. See: Forgetting index
retention
proportion of knowledge retained in memory at any given time. Retention is greater than 100% minus the forgetting index. The forgetting index refers to the probability of forgetting at the moment of a repetition while retention refers to the average recall probability between the last and the next repetition. For an exact formula linking the forgetting index and the retention see: Theoretical aspects of SuperMemo. Retention equals 100% minus the forgetting index only when measured on items repeated on a single day (e.g. as displayed in Toolkit : Calendar)
retrievability
one of the two variables describing memory traces in learning (the other is stability). Retrievability is most often expressed as the probability of recall. Retrievability is subject to negatively exponential decline whose speed depends on memory stability. Stability is often expressed as the optimum interval for the forgetting index equal to 10%. This term was proposed by Wozniak, Gorzelanczyk, and Murakowski (1995) to help differentiate memory stability from the imprecise and all-encompassing term memory strength. See: Two components of long-term memory
review
process in which the learning material is reviewed. In SuperMemo, the review may be active (items) or passive (topics). Usually, passive review means reading, while active review means recalling of information from memory with grading (repetitions). See also: Subset review
R-Factor (retention factor; RF)
the number which says at which U-Factor (i.e. the measure of interval increase) the measured forgetting index (i.e. the measure of forgetting) is approximated to be 10%. This number is unique for different item difficulties and for different repetition categories (i.e. the measure of memory stability). R-Factors can be seen as a vertical green line on forgetting curve graphs in SuperMemo
RF matrix
a matrix that holds all R-Factor values, both measured and theoretical (i.e. those that could not be measured yet). R-Factors are arranged in rows of repetition category (i.e. the measure of memory stability) and columns of A-Factor (i.e. the measure of item difficulty). You can see your RF matrix with Toolkit : Statistics : Analysis : Matrices : RF matrix
root node
root is a branch in the Contents window that keeps all elements of a given concept group. For example, a node named Chemistry might be a root node of all elements related to chemistry.
The root node determines how deep SuperMemo can interfere into the structure of the tree when working with a concept group. All elements under the root are subject to restructuring. All elements above the root are protected from changes.
The root is a node that keeps the hook that parents all newly added elements in the concept group.
The root of the whole collection is the root of the knowledge tree. This master root has a physical position of 1 in the collection (Element #1)
search&review
in SuperMemo, 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 of all those elements (e.g. with Ctrl+Shift+L)
The review may include all searched for elements (e.g. Learning : Review all in the browser with Ctrl+Shift+L), or only the outstanding elements (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, etc.
Compare: Neural review
secondary storage
place where multimedia files of a collection are stored. For example, in very large collections, multimedia files can be stored on CD-ROM (secondary storage), while all the frequently accessed or modified files are stored on the user's hard disk (primary storage). When you first create your collection, the primary storage equals the secondary storage. Secondary storage can be inspected or modified with Toolkit : Options : Access : Secondary storage
sibling
element in the Contents window that is located on the same level of the knowledge tree as the element in question.
See also:
spaced repetition (repetition spacing; expanded rehearsal)
technique of optimizing the learning process by computing optimum intervals that should separate repetitions of individual pieces of knowledge. Those pieces of knowledge are called elements in SuperMemo. SuperMemo pioneered the use of optimization methods in spaced repetition (first implemented in 1987) and has gained acclaim through its impact on the effectiveness of learning. See also: computational spaced repetition
spacing effect
property of memory which makes us remember things better if they are repeated in a spaced manner rather than condensed or cumulative manner (e.g. 7 x 10 min. learning daily as opposed to 70 min. on the weekend). Spacing effect is the basis of spaced repetition in learning. SuperMemo uses the spacing effect by trying to keep intervals as long as possible before forgetting increases beyond a selected threshold called the forgetting index
splitmark
boundary mark by which a large article will be split into smaller portions for faster loading and processing in SuperMemo. It can be a short text (e.g. ###SplitMark### or any custom string), an HTML tag (e.g. HR (also called splitline), H1 through H6, DIV) or a Wiki headline. You can quickly insert a splitmark by choosing Reading : Split : Insert splitline (Shift+Alt+H) from the HTML component menu
stability
one of the two variables describing memory traces in learning (the other is retrievability). Stability determines the speed of the negatively exponential decline of memory traces. Stability can be expressed, for example, by the optimum interval in spaced repetition (often normalized for the forgetting index equal to 10%). This term was proposed by Wozniak, Gorzelanczyk, and Murakowski (1995) to help differentiate from the imprecise and all-encompassing term memory strength (see: Two components of long-term memory). At each repetition, stability increases along the Stabilization function.
subset
  1. element subset: set of elements saved in a file, or
  2. registry subset: set of registry members saved in a file.
You can create an element subset by using the element browser (e.g. Subset : Save all or Select : Save selection on the browser menu). You can view an element subset with View : Subset from the main menu.
Registry subsets are mostly used in search and sort operations. For example, you could use Ctrl+S to find all texts containing the word virus. Those will be displayed as a registry subset in the text registry window. You could use Ctrl+S again to search for the word AIDS and generate a narrower subset that would contain both words virus and AIDS
subset review
review of elements in a subset. Subset review may, for example, review all items related to geology, or all elements related to Nuclear power in the United States. Subset review may be based on a variety of subsets. For example, it may have a form of search&review, neural review, branch review, and more
SuperMemo
  1. method of fast learning based on computing optimum intervals between repetitions
  2. computer program implementing the SuperMemo method
See: Introduction to SuperMemo
task
element that represents a to-do task. For example, a task may have a form of an article that is waiting for reading on a prioritized tasklist called a reading list.
See also:
tasklist
form of to-do list used in SuperMemo. Tasklists are made of a set of tasks (each corresponds with a single element in SuperMemo). Tasks in a tasklist are sorted by their priority. Task priorities in SuperMemo are determined by the Value/Time ratio. See: Tasklist manager
template
a reusable definition of an element's appearance. It may define the type and properties of individual components such as size, color, font, image files, alignment, etc. All templates used in a given collection are kept in the template registry available with Search : Templates from the main menu. Read more: Using templates
topic
element that presents a synthetic overview of knowledge (e.g. an article to read). Knowledge stored in topics is gradually converted into items (e.g. in the process of incremental reading). Optimally, topics introduce you to the learned knowledge by providing a synthetic overview. You later keep the knowledge in your memory by only reviewing items. In a well-structured collection, topics will always be parents to items derived from their contents. Each time a student loses the sense of context during repetition, he or she can press Ctrl+Up to view the parent of the current element. This way a quick review of the synthetic material in the topic is possible. See also: Topics vs items
U-Factor
number associated with each memorized element. It equals to the ratio of the current interval and the previously used interval. If the element has not been repeated yet, i.e. the previous interval is not defined, U-Factor equals the first interval. The greater the U-Factor the greater the increase of the interval between repetitions. For items, U-Factors are determined by SuperMemo Algorithm. For topics, U-Factors are determined by A-Factors. For topics that have already been reviewed at least once, that have not been subject to postpones, U-Factors equal A-Factors. U in U-Factor stands for used interval increase
visual browser
SuperMemo browser in a mode that shows pictorial snapshots of individual elements. For pictures, see: Visual browser
visual learning
equivalent of incremental reading applied to pictures as well as texts stored as pictures. For details see: Visual learning