English—is one of the most incredible, flavorfully-complex melting pots of linguistic ingredients from other countries. These linguistic ingredients are called loanwords that have been borrowed and incorporated into English. The loanwords are oftentimes so common now, the foreign flavor has been completely lost.
Which Words Did English Take From Other Languages?
English is a more varied (and delicious) melting pot than you think …
English—is one of the most incredible, flavorfully-complex melting pots of linguistic ingredients from other countries that’s been left to simmer for (in some cases) centuries. These linguistic ingredients are called loanwords that have been borrowed and incorporated into English. The loanwords are oftentimes so common now, the foreign flavor has been completely lost on speakers.
What usually happens is that English speakers find a word in another language to describe something they don’t yet have a word for. So they “borrow” that word. Forever. That said, loanwords fall into two categories: popular loanwords and learned loanwords. Learned loanwords tend to come from scholarly or specialized fields, like medicine or law. It’s usually easier to see what language these words came from. English, for example, draws from Latin for a lot of medical and legal terms.
It’s not always that cut and dried, though. Sometimes it’s harder to see the line between popular and learned loanwords. The word ballet, for example, comes from French, and the terms for the different positions and steps in ballet have retained their original French names. In this case, ballet is a popular loanword. Most English speakers recognize the word as referring to a type of dance. However, the specialized terms in ballet could also be considered learned loanwords because they’re familiar to dancers and choreographers (who are skilled professionals), but largely unknown to people outside the field.
Loanwords make up 80% of English
What this means is that there is no such thing as pure English. English is a delectable, slow-cooked language of languages. As lexicographer Kory Stamper explains, “English has been borrowing words from other languages since its infancy.” As many as 350 other languages are represented and their linguistic contributions actually make up about 80% of English!
Ranking from most influential to least, English is composed of words from: Latin, French, German, Italian, Spanish, Dutch, Scandinavian, Japanese, Arabic, Portuguese, Sanskrit, Russian, Maori, Hindi, Hebrew, Persian, Malay, Urdu, Irish, Afrikaans, Yiddish, Chinese, Turkish, Norwegian, Zulu, and Swahili. And, that’s not even 10% of the 350 languages in the English melting pot.
DUOLINGO DISCUSSIONS
Taking a less charitable tack to describe the multilingual aspect of English, the writer James Nicoll said, “English doesn’t borrow from other languages. English follows other languages down dark alleys, knocks them over and goes through their pockets for loose grammar.” That’s certainly a grimmer view, but it’s a metaphor that when looking at certain periods of the history of English, especially during episodes of colonization by English-speakers around the world, rings true.
War is actually a way a lot of loanwords have come into English. Viking invasions of England during the Old English period brought Old Norse words like war and ugly. In 1066, the Normans (basically the French), led by William the Conqueror, invaded and took over the British Isles. That made French the language of the English court for hundreds of years. As many as 10,000 loanwords resulted from that period of English history. Interestingly, a lot of war-related words are loanwords.
Looking at the sheer multilingual complexity of English gives great insight into how richly flavored and inclusive the language really is. We’re sharing just a dash of some of the international linguistic ingredients that make English so special. Just know that the true recipe for English would fill countless volumes, and what we’ve got here is a pretty flavorless oversimplification by comparison!
Borrowing & loaning—like money?
Before we divulge some of the secret global ingredients of English, though, what exactly does borrowing and loaning mean when it comes to languages? These terms make it seem like a word is taken from one language by another for only a brief time and then returned to the lender (with interest?).
Obviously, this isn’t what happens. Using banking terminology may not be the best way to describe the exchange; influencing is probably a better way to conceptualize it. Nevertheless, linguists have been employing words like borrow and loan as metaphors to describe what amounts to be a very complicated and abstract process of exchanging words across cultures.
How does loaning words work?
Borrowing and lending of words happens because of cultural contact between two communities that speak different languages. Often, the dominant culture (or the culture perceived to have more prestige) lends more words than it borrows, so the process of exchange is usually asymmetrical.
A lot of the words that end up being loaned are part of the material culture of the dominant group. Food, plants, animals, and tools migrate with the groups that use them, and, of course, so do the words that describe those things. So, when other cultures come into contact with those new people and their objects and words, it’s no surprise that physical and linguistic exchanges take place. Because those objects already have names, the borrowing culture tends to adopt those names instead of inventing their own words.
The new loanwords that the receiving language incorporates into its lexicon usually start off sounding foreign and might only be used in certain pockets of the community until they gradually spread to more speakers over time. Pronunciation differences happen too, as the foreign word is phonologically reshaped so that it’s easier to say in the language that borrowed it through a process called naturalization or assimilation.
IMGFLIP
If a loanword is spoken by a large majority of people on a regular basis and its meaning no longer needs to be explained, then the word has been conventionalized. Loanwords can retain vestiges of their former selves (they can still be perceived as foreign in some way), or they can completely melt into the new language. Once the word no longer seems foreign, it is, in fact, a loanword.
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The yummy English melting pot (fast food version)
Popular loanwords are everyday words. You might not even realize that some of them came from another language. Most popular loanwords are the result of cultural contact. Many of them describe food, the arts, and entertainment. You probably know sushi comes from Japanese, and taco comes from Spanish, by way of Mexico. But some other food-related loanwords you might have forgotten are pizza from Italian, lemon from Arabic, and tart from French (the French spell it tarte).
There are so many ways to showcase the global ingredients of English, but to really do it justice would take as many years as it took English to get to the rich stew it is now. So, the table below is our “fast food” version of the melting pot. It’s a super-simplified ingredient list with a smattering of words in English that have been borrowed from the different languages we listed above.
Keep in mind that because of this presentation format, we’re not able to tell the intricate stories of how and when these words were introduced into the English lexicon. That involves slow-cooking that we just don’t have time for! But, at the end, we list some great suggestions for where to find a fuller recipe.
(Following the order of most-to-least contributing languages):
Rank Language Examples 1 Latin agriculture, language, justice, science, forum, circus, opium, dominatrix, religion, apostle, city, master, paper 2 French art, dance, jewel, painting, ballet, government, salon, brigade, infantry, grenade, quiche, beef, salmon 2 Greek phobia, academy, siren, lexicon, muse, odyssey, democracy, psyche, atlas, platonic, biology, comedy, tragedy, history, data 3 German blitz, strudel, kindergarten, flak, schadenfreude, schnitzel, zeitgeist, poodle, noodle, pretzel, sauerkraut, lager, zeppelin, delicatessen 4 Italian opera, soprano, piano, broccoli, fresco, spaghetti, prima donna, parmesan, pesto, viola, pizza, cappuccino, latte 5 Spanish canyon, tornado, tortilla, barricade, guitar, alligator, burrito, coyote, junta 6 Dutch buoy, cruise, dock, avast, freight, dyke, yacht, easel, landscape, sketch, booze, coleslaw, cookie, gin 7 Scandinavian smorgasbord, ski, fjord, saga, sauna, maelstrom, slalom 8 Japanese karaoke, samurai, kimono, sushi, tsunami, kamikaze, geisha, judo, jujitsu, soy 9 Arabic alcohol, bedouin, harem, lute, algebra, zero, zenith, giraffe, gazelle, sultan, caravan, mosque 10 Portuguese albino, dodo, emu, fetish, tempura 11 Sanskrit avatar, karma, mahatma, swastika, yoga 12 Russian borscht, czar/tsar, icon, vodka, glasnost (a term from the Soviet Union for “open government”) 13 Maori kiwi, mana, moa, waka (common Maori words used in New Zealand English) 14 Hindi bandanna, bangle, bungalow, juggernaut, jungle, loot, pajamas, punch (drink), shampoo 15 Hebrew sapphire, babble, brouhaha, maven, abacus, behemoth, cherub, jubilee, sabbatical, sabbath, amen 16 Persian chess, checkmate, check 17 Malay ketchup, amok 18 Urdu chintz, bungalow, cheroot, cot, many overlaps with Hindi 19 Irish boycott, brogues, clock, dig (slang), hooligan 20 Afrikaans apartheid, commando, trek, aardvark, meerkat, wildebeest 21 Yiddish Chanukkah (Hanukkah), chutzpah, kosher, lox, pastrami, schlep, klutz, oy vey, schmuck 22 Chinese dim sum, chow mein, tea, kowtow, tai chi, kung fu 23 Turkish baklava, coffee, kiosk, ottoman 24 Norwegian berserk, gun, ransack, slaughter, hell, husband, skill, bug, reindeer, dirt 25 African origins banana, bongo, banjo, cola, jazz, chimpanzee, goober, gumbo, impala, jumbo, mamba, zebra, zombie
As you’d imagine, learning about English’s loanwords from other languages is linked with the history of the English language itself. Because of its status as a global lingua franca, English is now much more of a lender than a borrower, but the ways in which English has contributed to other languages around the world is a recipe for another day. Though at a decreasing rate, English continues to borrow words in the 21st-century. Popular recent loanwords include Sudoku (the Japanese number puzzle appearing in the daily paper), wiki (a Hawaiian word describing a user-controlled website, i.e., Wikipedia), and latte (that Italian coffee drink with frothy milk that you need every morning so you can see straight).
If you want to explore these and many other global linguistic ingredients according to roughly when they were added to the melting pot (and what condition the world ‘kitchen’ was in, so to speak), check out Philip Durkin’s detailed analysis, Borrowed Words: A History of Loanwords in English. Durkin is the Deputy Chief Editor of the Oxford English Dictionary and his exploration describes the intricacies of loanwords in terms of the historical and linguistic landscape of English from its earliest stages to the present day. In a Slate article summarizing his findings, Durkin includes a fascinating timeline of all the lending-languages that have influenced English over the centuries. You can click across to view the different periods of English and the proportions of each linguistic ingredient added during that time.
For another accessible summary of major periods of borrowing in English, take a look at Rice University’s outline on loanwords.
And, the next time you encounter someone who claims English is pure and wants to keep it that way, tell them they have absolutely no idea what they’re talking about. In fact, now you have all the ingredients to back up your observation of how “tasteless” their statement is!
Also, if you want to see how English has influenced some other languages … like French … read through this piece: France And The Battle Of Mots De Prêt (Loanwords)
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Harnessing AI to Preserve the World’s Endangered Languages
Tapan Gohil, 19 hours ago
Introduction
The world’s linguistic diversity is under threat. According to UNESCO, over 40% of the approximately 7,000 languages spoken globally are endangered, with many at risk of disappearing forever. As globalization and the dominance of major world languages like English, Mandarin, and Spanish continue to grow, the race is on to preserve the unique cultural treasures embodied in these minority tongues before they are lost to future generations.
Fortunately, advances in artificial intelligence (AI) and machine learning are providing powerful new tools in the fight to save endangered languages. From high-tech documentation efforts to community-driven language revitalization programs, AI is playing a critical role in reversing the tide of linguistic extinction. In this article, we’ll explore some of the innovative ways that AI is being leveraged to preserve the world’s endangered languages.
The Power of AI in Language Preservation
At the heart of the endangered language crisis is a lack of comprehensive data. Many minority and indigenous languages have never been thoroughly documented, with no written grammars, dictionaries, or recorded oral histories available. This lack of linguistic data makes it extremely challenging to develop the educational resources, language-learning tools, and computational applications needed to support language revitalization efforts.
This is where artificial intelligence is creating a significant transformation. Advanced speech recognition, natural language processing, and machine learning algorithms are enabling the rapid digitization and documentation of endangered language materials at unprecedented scales. Researchers are deploying AI-powered audio and video recording devices to capture spoken language data from fluent elders, while AI-assisted transcription and translation tools are allowing this data to be efficiently processed and annotated.
One pioneering example is the Endangered Languages Documentation Programme (ELDP) at SOAS University of London. This initiative has used AI-powered recording devices and transcription software to build a vast digital archive of endangered language materials, including over 4,000 hours of audio and video recordings in more than 300 languages. By automating the data collection and processing workflow, the ELDP has been able to significantly accelerate the documentation of these at-risk tongues.
Similarly, the Wikitongues project has leveraged AI-powered speech recognition to create an online repository of crowdsourced video recordings of people speaking over 1,000 different languages. This growing digital library allows linguists, educators, and community members to access authentic language data and collaborate on preserving their linguistic heritage.
Revitalizing Endangered Languages with AI
Beyond just documenting endangered languages, AI is also playing a crucial role in revitalizing them. Intelligent language-learning chatbots, for instance, are being developed to provide interactive, conversational practice for endangered language speakers, particularly younger generations who may not have had the opportunity to learn from fluent elders. These AI assistants can be customized with culturally relevant content and designed to encourage frequent use, helping to foster intergenerational transmission of endangered languages.
In New Zealand, the Te Hiku Media organization has created an AI-powered language app called “Te Reo Hāpai” that teaches conversational Māori through interactive games and lessons. Similarly, in Canada, the FirstVoices initiative has developed a suite of mobile apps powered by AI speech recognition that allow Indigenous language learners to practice their skills through voice-enabled activities.
Multilingual AI systems are also proving useful for language preservation, as they can facilitate communication and collaboration between speakers of different endangered languages. For example, the Universal Dependencies project is using AI-driven multilingual natural language processing to create vast datasets of syntactically annotated text in over 100 languages, including many at-risk minority tongues. This linguistic data can then be leveraged to build machine translation systems, educational resources, and other computational tools to support endangered language communities.
Ethical Considerations
Of course, the integration of AI into language preservation efforts also raises important ethical and practical considerations. There are valid concerns about data privacy, intellectual property rights, and the potential for AI-powered tools to be misused or to inadvertently cause harm to vulnerable language communities. Careful design, rigorous testing, and close collaboration with local stakeholders are essential to ensure that AI is deployed responsibly and equitably in this domain.
Conclusion
The urgent need to preserve the world’s endangered languages has never been more pressing. With over 40% of the approximately 7,000 languages spoken globally now classified as at-risk, the race is on to document, revitalize, and transmit these vital cultural artifacts to future generations before they disappear forever.
Fortunately, the rapid advancement of artificial intelligence (AI) and machine learning technologies is providing powerful new tools to aid in this critical effort. From automated language documentation and digitization to interactive AI-powered language learning apps, the integration of AI into language preservation initiatives is transforming the landscape of endangered language conservation.
As we continue to explore the remarkable potential of AI to support endangered language communities, it will be essential to do so in a responsible and ethical manner – one that prioritizes the needs, rights, and cultural autonomy of these vulnerable linguistic groups. Only then can we truly harness the full power of AI to safeguard the rich diversity of human expression and ensure that no language is left behind.
You may also like: AI and the Revival of Extinct Languages
FAQ
Q1. What is AI’s role in endangered language preservation?
A1. AI is revolutionizing endangered language preservation through technologies like automated language documentation, AI-powered language learning apps, and multilingual AI systems that facilitate communication and collaboration between speakers of different minority languages.
Q2. What are some examples of AI-powered language preservation initiatives?
A2. Examples include the Endangered Languages Documentation Programmed at SOAS University of London, the Wikitongues project, the Te Reo Hāpai Māori language app in New Zealand, and the First Voices initiative in Canada.
Q3. What ethical considerations arise with using AI for language preservation?
A3. Key concerns include data privacy, intellectual property rights, and the potential for AI tools to be misused or cause unintended harm to vulnerable language communities. Careful design, rigorous testing, and close collaboration with local stakeholders are essential.
Q4. How can AI help reverse the tide of linguistic extinction?
A4. By automating and streamlining the documentation, revitalization, and transmission of endangered languages, AI technologies are providing new hope for safeguarding the rich cultural diversity embodied in the world’s minority tongues.
Q5. What is the current state of endangered language preservation globally?
A5. According to UNESCO, over 40% of the approximately 7,000 languages spoken globally are currently endangered, with many at serious risk of disappearing forever due to factors like globalization and the dominance of major world languages.
The world’s linguistic diversity is under threat. According to UNESCO, over 40% of the approximately 7,000 languages spoken globally are endangered, with many at risk of disappearing forever. As globalization and the dominance of major world languages like English, Mandarin, and Spanish continue to grow, the race is on to preserve the unique cultural treasures embodied in these minority tongues before they are lost to future generations.
Fortunately, advances in artificial intelligence (AI) and machine learning are providing powerful new tools in the fight to save endangered languages. From high-tech documentation efforts to community-driven language revitalization programs, AI is playing a critical role in reversing the tide of linguistic extinction. In this article, we’ll explore some of the innovative ways that AI is being leveraged to preserve the world’s endangered languages.
The Power of AI in Language Preservation
At the heart of the endangered language crisis is a lack of comprehensive data. Many minority and indigenous languages have never been thoroughly documented, with no written grammars, dictionaries, or recorded oral histories available. This lack of linguistic data makes it extremely challenging to develop the educational resources, language-learning tools, and computational applications needed to support language revitalization efforts.
This is where artificial intelligence is creating a significant transformation. Advanced speech recognition, natural language processing, and machine learning algorithms are enabling the rapid digitization and documentation of endangered language materials at unprecedented scales. Researchers are deploying AI-powered audio and video recording devices to capture spoken language data from fluent elders, while AI-assisted transcription and translation tools are allowing this data to be efficiently processed and annotated.
One pioneering example is the Endangered Languages Documentation Programme (ELDP) at SOAS University of London. This initiative has used AI-powered recording devices and transcription software to build a vast digital archive of endangered language materials, including over 4,000 hours of audio and video recordings in more than 300 languages. By automating the data collection and processing workflow, the ELDP has been able to significantly accelerate the documentation of these at-risk tongues.
Similarly, the Wikitongues project has leveraged AI-powered speech recognition to create an online repository of crowdsourced video recordings of people speaking over 1,000 different languages. This growing digital library allows linguists, educators, and community members to access authentic language data and collaborate on preserving their linguistic heritage.
Revitalizing Endangered Languages with AI
Beyond just documenting endangered languages, AI is also playing a crucial role in revitalizing them. Intelligent language-learning chatbots, for instance, are being developed to provide interactive, conversational practice for endangered language speakers, particularly younger generations who may not have had the opportunity to learn from fluent elders. These AI assistants can be customized with culturally relevant content and designed to encourage frequent use, helping to foster intergenerational transmission of endangered languages.
In New Zealand, the Te Hiku Media organization has created an AI-powered language app called “Te Reo Hāpai” that teaches conversational Māori through interactive games and lessons. Similarly, in Canada, the FirstVoices initiative has developed a suite of mobile apps powered by AI speech recognition that allow Indigenous language learners to practice their skills through voice-enabled activities.
Multilingual AI systems are also proving useful for language preservation, as they can facilitate communication and collaboration between speakers of different endangered languages. For example, the Universal Dependencies project is using AI-driven multilingual natural language processing to create vast datasets of syntactically annotated text in over 100 languages, including many at-risk minority tongues. This linguistic data can then be leveraged to build machine translation systems, educational resources, and other computational tools to support endangered language communities.
Ethical Considerations
Of course, the integration of AI into language preservation efforts also raises important ethical and practical considerations. There are valid concerns about data privacy, intellectual property rights, and the potential for AI-powered tools to be misused or to inadvertently cause harm to vulnerable language communities. Careful design, rigorous testing, and close collaboration with local stakeholders are essential to ensure that AI is deployed responsibly and equitably in this domain.
Conclusion
The urgent need to preserve the world’s endangered languages has never been more pressing. With over 40% of the approximately 7,000 languages spoken globally now classified as at-risk, the race is on to document, revitalize, and transmit these vital cultural artifacts to future generations before they disappear forever.
Fortunately, the rapid advancement of artificial intelligence (AI) and machine learning technologies is providing powerful new tools to aid in this critical effort. From automated language documentation and digitization to interactive AI-powered language learning apps, the integration of AI into language preservation initiatives is transforming the landscape of endangered language conservation.
As we continue to explore the remarkable potential of AI to support endangered language communities, it will be essential to do so in a responsible and ethical manner – one that prioritizes the needs, rights, and cultural autonomy of these vulnerable linguistic groups. Only then can we truly harness the full power of AI to safeguard the rich diversity of human expression and ensure that no language is left behind.
Q1. What is AI’s role in endangered language preservation?
A1. AI is revolutionizing endangered language preservation through technologies like automated language documentation, AI-powered language learning apps, and multilingual AI systems that facilitate communication and collaboration between speakers of different minority languages.
Q2. What are some examples of AI-powered language preservation initiatives?
A2. Examples include the Endangered Languages Documentation Programmed at SOAS University of London, the Wikitongues project, the Te Reo Hāpai Māori language app in New Zealand, and the First Voices initiative in Canada.
Q3. What ethical considerations arise with using AI for language preservation?
A3. Key concerns include data privacy, intellectual property rights, and the potential for AI tools to be misused or cause unintended harm to vulnerable language communities. Careful design, rigorous testing, and close collaboration with local stakeholders are essential.
Q4. How can AI help reverse the tide of linguistic extinction?
A4. By automating and streamlining the documentation, revitalization, and transmission of endangered languages, AI technologies are providing new hope for safeguarding the rich cultural diversity embodied in the world’s minority tongues.
Q5. What is the current state of endangered language preservation globally?
A5. According to UNESCO, over 40% of the approximately 7,000 languages spoken globally are currently endangered, with many at serious risk of disappearing forever due to factors like globalization and the dominance of major world languages."
MRI data from large sample shows increased whole-brain connectivity in people with a second language Neuroplasticity is the brain’s ability to build connections within itself, adapting to the surrounding environment. The brain is most plastic in childhood, forming new pathways in reaction to stimuli such as language. Past research has shown that learning a second language may positively affect attention, healthy aging and even recovery after brain injury. A new study from The Neuro (Montreal Neurological Institute-Hospital) of McGill university, the University of Ottawa and the University of Zaragoza in Spain elaborates on bilingualism’s role in cognition, showing increased efficiency of communication between brain regions. Scientists recruited 151 participants who either spoke French, English, or both languages, and recorded the age at which they learned their second language. The participants were scanned using resting state functional magnetic resonance imaging (fMRI) to record whole-brain connectivity, rather than focusing on specific regions as was done in previous bilingualism studies. fMRI scans revealed that bilingual participants had increased connectivity between brain regions than monolingual participants, and this connectivity was stronger in those who learned their second language at a younger age. This effect was particularly strong between the cerebellum and the left frontal cortex. The results mirror previous studies which have shown that brain regions do not work in isolation, but interact with others to understand and produce language. Research has also shown that whole-brain efficiency aids cognitive performance. This latest study reveals more about how bilingualism influences the brain connections we use to think, communicate and experience the world around us. “Our work suggests learning a second language during childhood helps build a more efficient brain organization in terms of functional connectivity,” says Zeus Gracia Tabuenca, the paper’s first author. “The results indicate that the earlier the second language experience, the broader extent of brain areas involved in neuroplasticity. That's why we are observing higher connectivity of the cerebellum with the cortex in earlier exposures to a second language.” The research was published in the journal Communications Biology on Oct. 10, 2024. It was funded with the support of the Natural Sciences and Engineering Research Council of Canada, the Blema and Arnold Steinberg Family Foundation, The Centre for Research on Brain, Language and Music via the Fonds de recherche du Québec, Brain Canada, the Canada Research Chair program, the European Union's NextGeneration programme and the Spanish Ministry of Universities’ Margarita Salas Program. About The Neuro The Neuro – The Montreal Neurological Institute-Hospital – is a bilingual, world-leading destination for brain research and advanced patient care. Since its founding in 1934 by renowned neurosurgeon Dr. Wilder Penfield, it has grown to be the largest specialized neuroscience research and clinical center in Canada, and one of the largest in the world. The seamless integration of research, patient care, and training of the world’s top minds make The Neuro uniquely positioned to have a significant impact on the understanding and treatment of nervous system disorders. It was the first academic institute in the world to fully adopt Open Science, to help accelerate the generation of knowledge and discovery of novel effective treatments for brain disorders. The Neuro is a McGill University research and teaching institute and part of the Neuroscience Mission of the McGill University Health Centre. For more information, please visit www.theneuro.ca
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Teaching grammar in isolation is not only ineffective, it can actually make student writing worse. So when students make mistakes, what should teachers do?
Shutterstock Multilingualism and Linguistic diversity Information and knowledge are key determinants of wealth creation, social transformation, and human development. Language enables the delivery of information and knowledge coded in different sociocultural, political, and economic contexts.
For language enthusiasts and prospective learners, the question of whether German is a challenging language to master often looms large. In this blog post, we will demystify the perceived difficulty of learning German, exploring various aspects that contribute to its reputation and shedding light on strategies to navigate potential challenges. In what follows, we will answer the question whether mastering the German language poses a formidable challenge or an achievable goal. Let's delve into th
English podcasts are a great way to learn a language. Find a list of the best ones for beginners, advanced learners and tips to get the most out of them.
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