Практика Shadowing: Explaining how AI is killing the PhD in less than 10 minutes - Изучайте разговорный английский по видео

Выберите режим практики

Каждый режим открывает полноэкранную комнату практики.

97 предложений

Если предложения слишком короткие или длинные, нажмите Edit, чтобы их изменить.

The PhD, or Doctorate of Philosophy, is one of the most privileged and honorable degrees obtained today.

About 2 -3 % of adults actually have a doctorate degree, according to U .S.

Census data.

While there are many types of PhDs that one can earn,

the degree is well known for its long length of research and robust processes within the field of higher education.

Additionally, a PhD focuses on theory and using future research from other studies to guide the next.

Most individuals earn PhDs because they have goals to work in higher paying jobs that have large impacts on society.

While there are multiple other reasons why individuals go for their doctor degrees, some jobs include leadership, industry research, and higher education at universities.

But one of the biggest misconceptions about earning a PhD is that you're finished once when you get it.

However, earning the degree simply signifies that you are now ready for the next big step, which in some cases means more research.

Eventually, those with PhDs may have the opportunity to get their studies published in a journal article, and the more prestigious the journal article,

the greater the reward in some cases, meaning money and status within the academia world.

While going for a PhD is hard, and post -doctorate life can also be a challenge, why not use AI to make things easier?

Well, after all, ever since the launch of ChatGBT, generative AI has the ability to find, synthesize, and even write the most robust components of research.

AI has the potential to eliminate hours upon hours of grunt work that consume a researcher's time,

which can be a lot for a doctoral candidate or somebody who tries to go for their PhD.

But sometimes the cure can be worse than the disease,

because before we explain why AI can potentially harm the process of earning a PhD in ethical future work,

we need to explore the history of the dissertation process and how writers conducted research.

Before computers, dissertations were a manual labor of intellect.

Advisors were the central gatekeepers, and their approval determined the structured tone and even the acceptability of your ideas.

The work was deeply theoretical, focused on philosophy, frameworks, and peer knowledge.

Practical application was rare, and access to information was limited to what could be found in physical libraries or archives.

Research meant travel, note cards, and long hours in dim reading rooms.

This was an era where the dissertation was a momentum and not just a project.

Once when the 1990s arrived, the dissertation changed rapidly.

The arrival of computers revolutionized everything.

Word processors like

Microsoft Word replaced typewriters, making revision and formatting far much easier.

Digital databases such as JSTOR, ProQuest, and EBSCO opened the doors to global research at the click of a button.

Standardized formatting became non -negotiable and templates for APA, MLA, and Chicago style ensured every dissertation looked and felt uniform.

Committees became more specialized, demanding stronger methodological rigor, and new approaches like mixed methods began merging qualitative and quantitative traditions.

The dissertation was no longer just theoretical, it was evolving into something measurable, structured, and data -driven.

By the 2010s, the computer had completely changed the dissertation forever, and submissions were electronic, archived in PDF format for online access.

Collaborations became global, and students worked across time zones using tools like Mendeley, Google Docs, and Zotero.

Research grew interdisciplinary, weaving together education, technology, psychology, and even business.

Universities began emphasizing real -world impact.

In fact, open access publishing and institutional repositories brought dissertations into public view, signaling a move toward democratized knowledge.

The dissertation process has gone from a tedious process of handling library cards to a much more simple,

stay at home process if you owned a computer.

However, just when the dissertation process felt like it had changed so rapidly, another wave of change was about to hit.

AI tools like ChatGBT, Elicit, and Cite began assisting students in organizing, summarizing, and synthesizing vast amounts of literature.

What once took months of reading could now be mapped in hours.

But this power came with responsibility.

Universities introduced AI use declarations requiring transparency about how these tools were used.

Ethical guidelines emphasized maintaining authorship, integrity, and providing that the ideas were still the students' own.

Data -driven dissertations became the norm.

Machine learning, analytics, and digital ethnography redefined what counts as research.

At the same time, the students' voice became more important than ever.

Institutions began expecting reflexivity, the ability to demonstrate authenticity, originality, and scholarly judgment.

even with AI support.

Peer review was also affected.

AI -assisted editors like Grammarly, Trinka, and ChatGPT joined human advisors in collaborative feedback loops.

Some universities even began accepting multi -model submissions, interactive dashboards, digital appendices, and visual models alongside the written text.

Research is showing that businesses are requiring their workers to learn more about AI.

Otherwise, workers are going to get left behind.

And if that's not enough, we need to talk about the big elephant in the room.

Plagiarism.

AI has made research faster, but not necessarily better.

Some doctoral students are beginning to rely too heavy on artificial intelligence to write their papers, summarize literature, or even generate arguments that they barely understand.

When this happens, the line between researcher and algorithm begins to blur.

If a machine does the synthesis, where does the scholarly's originality come from?

Well, universities are struggling to find that balance.

Jared Henderson created a video titled

Everyone is Cheating, Even the Professors, which is about the rising trend of AI usage in academia.

The video analyzes how AI creates more opportunities for students and professors to cheat by using AI.

Henderson cites that universities are struggling to innovate meaningful policy that combat AI.

Instead, he cites that Ohio State has drafted a policy that attempts to coexist with AI because AI is here to stay.

So, where's the balance?

AI tools can misrepresent sources, fabricate citations, and subtly shift the meaning of ideas.

They can make writing look more polished than the student's true comprehension allows, and, in doing so, they create a new kind of inequality.

Those who know how to use AI strategically appear more capable than those who don't, even if their understanding is the same.

There's also a deeper, quieter issue, which is the loss of intellectual struggle.

For generations, the challenge of writing a dissertation was what shaped a scholar's identity.

It was through the long, messy process of writing, revising, and defending ideas that true expertise was formed.

All those hours late in the library looking up research

and being the detective has since been turned into writing a prompt through an AI site and getting everything you ever wanted.

If AI shortcuts that process, what happens to the depth of our thinking?

Are we producing scholars or simply managers of machine -generated ideas?

That's the question universities, advisors, and students are now forced to confront.

PhD students' reliance on AI for writing papers raises ethical concerns and may undermine critical thinking and analytical skills.

A balanced use of AI is recommended to maintain academic integrity and intellectual rigor.

Additionally, AI has very mixed feelings amongst professors.

Some professors fear that their advisees may be relying too much on AI.

In the case of some universities, comprehensible exams that require weeks' worth of writing have been permanently canceled due to the rise of AI.

So, where do we go from here?

AI is rewriting the rules of research, and with it, the very soul of the dissertation.

For centuries, earning a PhD meant proving your endurance, your originality, and your ability to push the boundaries of human knowledge,

which is true to this day still.

But in 2025, we're standing at a crossroads where speed, convenience, and technology challenge what it means to think deeply.

Artificial intelligence has given scholars the ability to analyze faster, write clearer, and publish sooner.

But it also tempts us to skip the struggle that once defined academic excellence.

Now isn't whether AI belongs in research, it's how far we're willing to let it go.

Will the next generation of schools use AI to expand the human mind, or allow it to quietly replace the hard work that makes discovery meaningful?

Because in the end, a dissertation is about using one's own voice to examine the gaps within the literature.

It's an understatement to say that this conversation is just getting started.

If you want to see where AI is taking the future of academia, subscribe for more content.

Скачать приложение

Всё для свободной речи

ИИ-оценка произношенияОценка каждой фразы

Практика IPAОсвойте каждый звук

СловарьСоберите свой словарный запас

Игра со словамиУчитесь играя

Сканировать QR

Download on theApp Store Get it onGoogle Play

FOR YOU

Лексика и советы по произношению к этому уроку

Этот урок разговорной практики построен на видео «Explaining how AI is killing the PhD in less than 10 minutes». Чаще всего повторяются слова: dissertation, Phd, universities, students, process. В этом видео 97 предложений и 1426 слов для шедоуинга. Речь длится 8:40. Говорящий говорит в естественном темпе, около 165 слов в минуту, близком к повседневной речи. Только 74% слов входят в 3000 самых частых слов английского языка, поэтому лексика сложная.

Ключевая лексика этого видео

15 слов из видео, которые стоит выучить, с произношением и значением:

Слово	Произношение	Значение
dissertation существительное	/ˌdɪsəˈteɪʃən/	диссерта́ция, тракта́т
earn глагол	/ɝn/	зараба́тывать, зарабо́тать
format существительное	/ˈfɔːɹ.mæt/	форма́т
ethical прилагательное	/ˈɛθɪkəl/	эти́ческий
advisor существительное	/ædˈvaɪ.zə(ɹ)/	консульта́нт, консульта́нтка
deeply наречие	/ˈdi(ː)pli/	глубоко́
assist глагол	/əˈsɪst/	помога́ть, помо́чь
rapidly наречие	/ˈɹæpɪdli/	бы́стро
intellectual прилагательное	/ˌɪntəˈlɛkt͡ʃʊəl/	интеллектуа́льный, у́мственный
rely глагол	/ɹɪˈlaɪ/	полага́ться, положи́ться
artificial прилагательное	/ˌɑː.tɪˈfɪʃ.əl/	иску́сственный
generate глагол	/ˈd͡ʒɛn.ə.ɹeɪt/	порожда́ть, производи́ть
integrity существительное	/ɪnˈtɛɡɹəti/	че́стность
additionally наречие		дополни́тельно, кро́ме того́
meaningful прилагательное	/ˈmiː.nɪŋ.fl̩/	зна́чимый

Фразовые глаголы, которые вы услышите

Слово	Произношение	Значение
leave behind глагол		оставля́ть, оста́вить
look up глагол	/ˌlʊk ˈʌp/	улучша́ться

Грамматика в этом видео

Конструкции, которые говорящий использует чаще всего, с точными словами из видео:

Конструкция	В видео
Пассивный залог be + причастие прошедшего времени — важно, что происходит, а не кто это делает	could be found · be mapped · were used
Present Perfect have/has + причастие прошедшего времени — прошлое действие, важное сейчас	has gone · has made · has drafted
Придаточные определительные who / which + предложение — уточнение о человеке или предмете	somebody who tries · Professors, which is · Those who know

Произношение, на которое стоит обратить внимание

Говорящий использует 5 сокращённых и редуцированных форм, например we're, don't, isn't. Произносите их коротко, так, как слышите.

Звуки «th»: ethical /ˈɛθɪkəl/, theoretical /ˌθi.əˈɹɛt.ɪ.kəl/, algorithm /ˈælɡəɹɪðm̩/, synthesis /ˈsɪnθəsɪs/, authenticity /ɑθɛnˈtɪsɪti/
Звуки «sh» и «zh»: dissertation /ˌdɪsəˈteɪʃən/, artificial /ˌɑː.tɪˈfɪʃ.əl/, publish /ˈpʌblɪʃ/, submission /səbˈmɪʃən/, potentially /pəˈtɛnʃ(ə)li/
Длинные слова — следите за ударением: dissertation /ˌdɪsəˈteɪʃən/, academia /ˌæk.əˈdi.mi.ə/, intellectual /ˌɪntəˈlɛkt͡ʃʊəl/, artificial /ˌɑː.tɪˈfɪʃ.əl/, integrity /ɪnˈtɛɡɹəti/

Звуки, трудные для русскоязычных:

/w/ — губы округлены, это не /v/: reward /ɹɪˈwɔɹd/, framework /ˈfɹeɪm.wɜːk/, quietly /ˈkwaɪ.ɪt.li/, inequality /ˌɪn.ɪˈkwɑ.lɪ.ti/, quantitative /ˈkwɑn.təˌteɪ.tɪv/
/h/ — лёгкий выдох, а не русское «х»: harm /hɑːm/, comprehension /ˌkɑmpɹɪˈhɛnʃn̩/, comprehensible /kɒmpɹəˈhɛnsɪbəl/
Звонкие согласные в конце слова — не оглушайте их: archive /ˈɑɹˌkaɪv/, analyze /ˈæn.əˌlaɪz/, emphasize /ˈɛm.fə.saɪz/, defend /dɪˈfɪnd/, alongside /əˌlɔŋˈsaɪd/

Как заниматься с этим видео

Прослушайте всё видео один раз молча и выпишите незнакомые слова.
Начните со скорости 0,75×, повторяйте предложение за предложением и вернитесь к обычной скорости, когда станет легко.
Запишите себя и сравните с оригиналом, обращая внимание на такие слова, как dissertation, earn, format.

Что такое техника Shadowing?

Shadowing — это научно обоснованная техника изучения языка, изначально разработанная для подготовки профессиональных переводчиков и популяризированная полиглотом доктором Александром Аргуэльесом. Метод прост, но эффективен: вы слушаете аудио на английском от носителей языка и немедленно повторяете вслух — как тень, следующая за говорящим с задержкой в 1–2 секунды. В отличие от пассивного прослушивания или грамматических упражнений, Shadowing заставляет мозг и мышцы рта одновременно обрабатывать и воспроизводить реальные речевые паттерны. Исследования показывают, что это значительно улучшает точность произношения, интонацию, ритм, связную речь, понимание на слух и беглость речи — что делает его одним из самых эффективных методов для подготовки к IELTS Speaking и реального общения на английском.

Техника шедоуинга: читать полное пошаговое руководство →

Практика Shadowing: Explaining how AI is killing the PhD in less than 10 minutes - Изучайте разговорный английский по видео

Выберите режим практики

Скачать приложение

Рекомендуемое видео

Harvard AI Professor: The People Most at Risk From AI Aren’t Who You Think

AI Designed Viruses That Never Existed Before

Virtual love - How dangerous are AI relationships? | DW Documentary

AI Will End Philosophy, Physicist Claims

We Let $200 GPT-Pro Think for 7 Days on Unsolved Math

How I use AI to learn engineering (anti brain rot studying)

Discussing My Beliefs.. (Nihilism)

It’s not just you

3 Ways AI Will Completely Change Your Life by 2029

What Is AI? | Artificial Intelligence | What is Artificial Intelligence? | AI In 5 Mins |Simplilearn

AI Slop Is Destroying The Internet

What AI can (and can't) currently do in a real lab | Jennifer Doudna