SuperMemo is a learning method and software package developed by SuperMemo World and SuperMemo R&D with Piotr Woźniak in Poland from 1985 to the present. It is based on research into long-term memory, is a practical application of the spaced repetition learning method, proposed for efficient instruction by a number of psychologists as early as in the 1930s. According to the developers of SuperMemo and some other proponents of spaced repetition learning, the process can optimize long-term knowledge acquisition; the method is available as a computer program for Windows, Windows CE, Windows Mobile, iPhone, iPad, iPod Touch, Palm OS, etc. It can be used in a web browser or without a computer; the desktop version of SuperMemo supports incremental reading. The SuperMemo program stores a database of answers constructed by the user; when reviewing information saved in the database, the program uses the SuperMemo algorithm to decide what questions to show the user. The user answers the question and rates their recall - did they answer the question with hesitation, not at all, so on - and their rating is used to calculate how soon they should be shown the question again.
While the exact algorithm varies with the version of SuperMemo, in general, items that are harder to remember show up more frequently. Besides simple text questions and answers, the latest version of SuperMemo supports images, HTML questions and answers; the specific algorithms SuperMemo uses have been published, re-implemented in other programs. Different algorithms have been used. Subsequent versions of the software have further optimized the algorithm; as of June 2016, the latest version of the SuperMemo algorithm is SM-17, released in 2016. The SM-2 algorithm uses the performance on a card to schedule only that card, while SM-3 and newer algorithms use card performance to schedule that card and similar cards; the additional optimizations sometimes yield perverse results – answering "hard" on a card may yield an interval longer than answering "easy" on a card – and are criticized as reducing the robustness of the algorithm, making it more sensitive to variations – non-uniform difficulty of cards, inconsistencies in studying, so forth.
Woźniak disagreed with the criticism, but noted that in practice the other factors affecting study make it not important. Some of the algorithms have been reimplemented in other free programs such as Anki and Emacs Org-mode's Org-drill. See full list of flashcard software; the SM-2 algorithm has proven most popular in other applications, is used in Anki and Mnemosyne, among others. Org-drill implements SM-5 by default, optionally other algorithms such as SM-2. ArticlesTomasz P. Szynalski: Use spaced-repetition software – An introduction to spaced-repetition and SuperMemo Pawel Kowalczyk: Learn English with SuperMemo – How SuperMemo can help learn English Patrick Kenny: Memory Software: SuperMemo – A guide to using SuperMemo to study Japanese
Part of speech
In traditional grammar, a part of speech' is a category of words which have similar grammatical properties. Words that are assigned to the same part of speech display similar behavior in terms of syntax—they play similar roles within the grammatical structure of sentences—and sometimes in terms of morphology, in that they undergo inflection for similar properties. Listed English parts of speech are noun, adjective, pronoun, conjunction and sometimes numeral, article, or determiner. Other Indo-European languages have all these word classes. Beyond the Indo-European family, such other European languages as Hungarian and Finnish, both of which belong to the Uralic family lack prepositions or have only few of them. Other terms than part of speech—particularly in modern linguistic classifications, which make more precise distinctions than the traditional scheme does—include word class, lexical class, lexical category; some authors restrict the term lexical category to refer only to a particular type of syntactic category.
The term form class is used, although this has various conflicting definitions. Word classes may be classified as open or closed: open classes acquire new members while closed classes acquire new members infrequently, if at all. All languages have the word classes noun and verb, but beyond these two there are significant variations among different languages. For example, Japanese has as many as three classes of adjectives; because of such variation in the number of categories and their identifying properties, analysis of parts of speech must be done for each individual language. The labels for each category are assigned on the basis of universal criteria; the classification of words into lexical categories is found from the earliest moments in the history of linguistics. In the Nirukta, written in the 5th or 6th century BC, the Sanskrit grammarian Yāska defined four main categories of words: नाम nāma – noun आख्यात ākhyāta – verb उपसर्ग upasarga – pre-verb or prefix निपात nipāta – particle, invariant word These four were grouped into two larger classes: inflectable and uninflectable.
The ancient work on the grammar of the Tamil language, Tolkāppiyam, argued to have been written around 2,500 years ago, classifies Tamil words as peyar, vinai and uri. A century or two after the work of Nirukta, the Greek scholar Plato wrote in his Cratylus dialog that "... sentences are, I conceive, a combination of verbs and nouns ". Aristotle added another class, "conjunction", which included not only the words known today as conjunctions, but other parts. By the end of the 2nd century BC grammarians had expanded this classification scheme into eight categories, seen in the Art of Grammar, attributed to Dionysius Thrax: Noun: a part of speech inflected for case, signifying a concrete or abstract entity Verb: a part of speech without case inflection, but inflected for tense and number, signifying an activity or process performed or undergone Participle: a part of speech sharing features of the verb and the noun Article: a declinable part of speech, taken to include the definite article, but the basic relative pronoun Pronoun: a part of speech substitutable for a noun and marked for a person Preposition: a part of speech placed before other words in composition and in syntax Adverb: a part of speech without inflection, in modification of or in addition to a verb, clause, sentence, or other adverb Conjunction: a part of speech binding together the discourse and filling gaps in its interpretationIt can be seen that these parts of speech are defined by morphological and semantic criteria.
The Latin grammarian Priscian modified the above eightfold system, excluding "article", but adding "interjection". The Latin names for the parts of speech, from which the corresponding modern English terms derive, were nomen, participium, praepositio, adverbium and interjectio; the category nomen included substantives and numerals. This is reflected in the older English terminology noun substantive, noun adjective and noun numeral; the adjective became a separate class, as did the numerals, the English word noun came to be applied to substantives only. Works of English grammar follow the pattern of the European tradition as described above, except that participles are now regarded as forms of
Memory is the faculty of the brain by which information is encoded and retrieved when needed. Memory is vital to experiences, it is the retention of information over time for the purpose of influencing future action. If we could not remember past events, we could not learn or develop language, relationships, or personal identity. Memory is understood as an informational processing system with explicit and implicit functioning, made up of a sensory processor, short-term memory, long-term memory; this can be related to the neuron. The sensory processor allows information from the outside world to be sensed in the form of chemical and physical stimuli and attended to various levels of focus and intent. Working memory serves as an encoding and retrieval processor. Information in the form of stimuli is encoded in accordance with explicit or implicit functions by the working memory processor; the working memory retrieves information from stored material. The function of long-term memory is to store data through various categorical models or systems.
Explicit and implicit functions of memory are known as declarative and non-declarative systems. These systems lack thereof. Declarative, or explicit, memory is the conscious recollection of data. Under declarative memory resides episodic memory. Semantic memory refers to memory, encoded with specific meaning, while episodic memory refers to information, encoded along a spatial and temporal plane. Declarative memory is the primary process thought of when referencing memory. Non-declarative, or implicit, memory is the unconscious recollection of information. An example of a non-declarative process would be the unconscious learning or retrieval of information by way of procedural memory, or a priming phenomenon. Priming is the process of subliminally arousing specific responses from memory and shows that not all memory is consciously activated, whereas procedural memory is the slow and gradual learning of skills that occurs without conscious attention to learning. Memory is not a perfect processor, is affected by many factors.
The ways by which information is encoded and retrieved can all be corrupted. The amount of attention given new stimuli can diminish the amount of information that becomes encoded for storage; the storage process can become corrupted by physical damage to areas of the brain that are associated with memory storage, such as the hippocampus. The retrieval of information from long-term memory can be disrupted because of decay within long-term memory. Normal functioning, decay over time, brain damage all affect the accuracy and capacity of the memory. Memory loss is described as forgetfulness or amnesia. Sensory memory holds sensory information less than one second; the ability to look at an item and remember what it looked like with just a split second of observation, or memorization, is the example of sensory memory. It is an automatic response. With short presentations, participants report that they seem to "see" more than they can report; the first experiments exploring this form of sensory memory were conducted by George Sperling using the "partial report paradigm".
Subjects were presented with a grid of 12 letters, arranged into three rows of four. After a brief presentation, subjects were played either a high, medium or low tone, cuing them which of the rows to report. Based on these partial report experiments, Sperling was able to show that the capacity of sensory memory was 12 items, but that it degraded quickly; because this form of memory degrades so participants would see the display but be unable to report all of the items before they decayed. This type of memory cannot be prolonged via rehearsal. Three types of sensory memories exist. Iconic memory is a fast decaying store of visual information. Echoic memory is a fast decaying store of auditory information, another type of sensory memory that stores sounds that have been perceived for short durations. Haptic memory is a type of sensory memory. Short-term memory is known as working memory. Short-term memory allows recall for a period of several seconds to a minute without rehearsal, its capacity is very limited: George A. Miller, when working at Bell Laboratories, conducted experiments showing that the store of short-term memory was 7±2 items.
Modern estimates of the capacity of short-term memory are lower of the order of 4–5 items. For example, in recalling a ten-digit telephone number, a person could chunk the digits into three groups: first, the area code a three-digit chunk and lastly a four-digit chunk; this method of remembering telephone numbers is far more effective than attempting to remember a string of 10 digits. This may be reflected in some countries in the tendency to display telephone numbers as several chunks of two to four numbers. Short-term memory is believed to rely on an acoustic code for storing information, to a lesser extent a visual code. Conrad found that test subjects had more difficulty recalling collections of letters that were acoustically similar (e.g. E
Memrise is a language platform which uses flashcards as memory aids, but offers user-generated content on a wide range of other subjects. Memrise has official courses in its combinations; the app has over 35 million registered users. Memrise has been profitable since late 2016. Memrise was founded by Ed Cooke, a Grand Master of Memory, Greg Detre, a Princeton neuroscientist specializing in the science of memory and forgetting; the website launched in private beta after winning the Princeton Entrepreneurship Club 2009 TigerLaunch competition. On October 1, 2012, 100 users were allowed to sign up to test a non-beta version of the website called Memrise 1.0. As of May 2013, a Memrise app has been available for download on both Google Play. In July 2010, Memrise was named as one of the winners of the London Mini-Seedcamp competition. In November 2010, the site was named as one of the finalists for the 2010 TechCrunch Europas Start-up of the Year. In March 2011, it was selected as one of the Techstars Boston startups.
In May 2017, Memrise was named as one of Best App winner of the second edition of the Google Play awards. Starting in late February 2019, Memrise has been the subject of much recent criticism due to an announcement that user-created content will be moving to a different web-based platform, it was announced that this new website would not have an app and that users would be unable to access their material offline. In response, the Memrise forums were bombarded with posts criticizing this as a slap in the face to Memrise's users and content-creators; this criticism has followed onto Reddit with many users calling for a migration to rival platforms. In late September 2012, the leaderboard on the website was temporarily suspended due to "extensive cheating". Specific users had been using bots and non-intensive mechanisms, such as celebrity photo memory courses, to achieve atypical scores that were not reflective of actual learning. In response, the administrators established a new leaderboard after revising the scoring loopholes.
Anki ChineseSkill – A similar app intended to teach Mandarin Computer-assisted language learning Duolingo Fluenz Lang-8 Language education Language pedagogy List of flashcard software List of language self-study programs Rosetta Stone Official website iTunes App Store Google Play
International Standard Serial Number
An International Standard Serial Number is an eight-digit serial number used to uniquely identify a serial publication, such as a magazine. The ISSN is helpful in distinguishing between serials with the same title. ISSN are used in ordering, interlibrary loans, other practices in connection with serial literature; the ISSN system was first drafted as an International Organization for Standardization international standard in 1971 and published as ISO 3297 in 1975. ISO subcommittee TC 46/SC 9 is responsible for maintaining the standard; when a serial with the same content is published in more than one media type, a different ISSN is assigned to each media type. For example, many serials are published both in electronic media; the ISSN system refers to these types as electronic ISSN, respectively. Conversely, as defined in ISO 3297:2007, every serial in the ISSN system is assigned a linking ISSN the same as the ISSN assigned to the serial in its first published medium, which links together all ISSNs assigned to the serial in every medium.
The format of the ISSN is an eight digit code, divided by a hyphen into two four-digit numbers. As an integer number, it can be represented by the first seven digits; the last code digit, which may be 0-9 or an X, is a check digit. Formally, the general form of the ISSN code can be expressed as follows: NNNN-NNNC where N is in the set, a digit character, C is in; the ISSN of the journal Hearing Research, for example, is 0378-5955, where the final 5 is the check digit, C=5. To calculate the check digit, the following algorithm may be used: Calculate the sum of the first seven digits of the ISSN multiplied by its position in the number, counting from the right—that is, 8, 7, 6, 5, 4, 3, 2, respectively: 0 ⋅ 8 + 3 ⋅ 7 + 7 ⋅ 6 + 8 ⋅ 5 + 5 ⋅ 4 + 9 ⋅ 3 + 5 ⋅ 2 = 0 + 21 + 42 + 40 + 20 + 27 + 10 = 160 The modulus 11 of this sum is calculated. For calculations, an upper case X in the check digit position indicates a check digit of 10. To confirm the check digit, calculate the sum of all eight digits of the ISSN multiplied by its position in the number, counting from the right.
The modulus 11 of the sum must be 0. There is an online ISSN checker. ISSN codes are assigned by a network of ISSN National Centres located at national libraries and coordinated by the ISSN International Centre based in Paris; the International Centre is an intergovernmental organization created in 1974 through an agreement between UNESCO and the French government. The International Centre maintains a database of all ISSNs assigned worldwide, the ISDS Register otherwise known as the ISSN Register. At the end of 2016, the ISSN Register contained records for 1,943,572 items. ISSN and ISBN codes are similar in concept. An ISBN might be assigned for particular issues of a serial, in addition to the ISSN code for the serial as a whole. An ISSN, unlike the ISBN code, is an anonymous identifier associated with a serial title, containing no information as to the publisher or its location. For this reason a new ISSN is assigned to a serial each time it undergoes a major title change. Since the ISSN applies to an entire serial a new identifier, the Serial Item and Contribution Identifier, was built on top of it to allow references to specific volumes, articles, or other identifiable components.
Separate ISSNs are needed for serials in different media. Thus, the print and electronic media versions of a serial need separate ISSNs. A CD-ROM version and a web version of a serial require different ISSNs since two different media are involved. However, the same ISSN can be used for different file formats of the same online serial; this "media-oriented identification" of serials made sense in the 1970s. In the 1990s and onward, with personal computers, better screens, the Web, it makes sense to consider only content, independent of media; this "content-oriented identification" of serials was a repressed demand during a decade, but no ISSN update or initiative occurred. A natural extension for ISSN, the unique-identification of the articles in the serials, was the main demand application. An alternative serials' contents model arrived with the indecs Content Model and its application, the digital object identifier, as ISSN-independent initiative, consolidated in the 2000s. Only in 2007, ISSN-L was defined in the
Pleco is an English & Chinese Dictionary application for iOS and Android devices. The Pleco Software company was founded in May 2000 by Michael Love. Pleco allows different ways of input, including Pinyin input method, English words and through optical character recognition, It has many sets of dictionaries, audio recordings from two different native speakers, has flashcards functions and document reader which looks up words in a document. Pleco is a free application with additional functions and large dictionaries. Application was first launched on the Palm Pilot in 2001. In 2013 Pleco had one of the major upgrades. Pleco Chinese Dictionary 3.0 was released for iOS users. In November 2017, Endymion Wilkinson's Chinese History: A New Manual was added. Pleco requires an iPhone 3GS or an iPad 2 or or a Retina-display-equipped iPod Touch; the Android version requires Android 2.3 or and is available outside of Google Play for users in China or with non-Google Android devices like the Amazon Kindle Fire.
An iPhone version was released in 2008. List of flashcard software Chinese language
Incremental reading is a software-assisted method for learning and retaining information from reading, helping with the creation of flashcards out of electronic articles read in portions inside a prioritized reading list. It is targeted to people who are trying to learn for life a large amount of information if that information comes from various sources. "Incremental reading" means "reading in portions". Instead of a linear reading of articles one at a time, the method works by keeping a large reading list of electronic articles or books and reading parts of several articles in each session. Articles in the reading list are prioritized by the user. In the course of reading, key points of articles are broken up into flashcards, which are learned and reviewed over an extended period of time with the help of a spaced repetition algorithm; this use of flashcards at stages of the process is based on psychological principles of long-term memory storage and retrieval, in particular the spacing effect and the testing effect.
The method itself is credited to the Polish software developer Piotr Wozniak. He implemented the first version of incremental reading in 1999 in SuperMemo 99, providing the essential tools of the method: a prioritized reading list, the possibility to extract portions of articles and to create cloze deletions; the term "incremental reading" itself appeared the next year with SuperMemo 2000. SuperMemo programmes subsequently enhanced the tools and techniques involved, such as webpage imports, material overload handling, etc. Limited incremental reading support for the text editor Emacs appeared in 2007. An Anki add-on for incremental reading was published in 2011. Incremental reading was the first of a series of related concepts invented by Piotr Wozniak: incremental image learning, incremental video, incremental audio, incremental mail processing, incremental problem solving, incremental writing. "Incremental learning" is the term. When reading an electronic article, the user extracts the most important parts and distills them into flashcards.
Flashcards are information presented in a question-answer format. Cloze deletions are used in incremental reading, as they are easy to create out of text. Both extracts and flashcards are scheduled independently from the original article. With time and reviews, articles are supposed to be converted into extracts, extracts into flashcards. Hence, incremental reading is a method of breaking down information from electronic articles into sets of flashcards. Contrary to extracts, flashcards are reviewed with active recall; this means that extracts such as "George Washington was the first U. S. President" must be converted into questions such as "Who was the first U. S. President?", or "Who was George Washington?", etc. or cloze deletions such as " was the first U. S. President", "George Washington was ", etc; this flashcard creation process is semi-automated – the reader chooses which material to learn and edits the precise wording of the questions, while the software assists in prioritizing articles and making the flashcards, does the scheduling: it calculates the ideal time for the reader to review each chunk, according to the rules of spaced repetition.
This means. Individual articles are read in portions proportional to the attention span, which depends on the user, their mood, the article, etc; this allows according to Piotr Wozniak. Without the use of spaced repetition, the reader would get lost in the glut of information when studying dozens of subjects in parallel. However, spaced repetition makes it possible to retain traces of the processed material in memory. Kevin Purdy, Use Incremental Reading to Memorize Large Batches of Data