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• 40 Useful Words and Phrases for Top-Notch Essays

To be truly brilliant, an essay needs to utilise the right language. You could make a great point, but if it’s not intelligently articulated, you almost needn’t have bothered.

Developing the language skills to build an argument and to write persuasively is crucial if you’re to write outstanding essays every time. In this article, we’re going to equip you with the words and phrases you need to write a top-notch essay, along with examples of how to utilise them.

It’s by no means an exhaustive list, and there will often be other ways of using the words and phrases we describe that we won’t have room to include, but there should be more than enough below to help you make an instant improvement to your essay-writing skills.

If you’re interested in developing your language and persuasive skills, Oxford Royale offers summer courses at its Oxford Summer School , Cambridge Summer School , London Summer School , San Francisco Summer School and Yale Summer School . You can study courses to learn english , prepare for careers in law , medicine , business , engineering and leadership.

General explaining

Let’s start by looking at language for general explanations of complex points.

1. In order to

Usage: “In order to” can be used to introduce an explanation for the purpose of an argument. Example: “In order to understand X, we need first to understand Y.”

2. In other words

Usage: Use “in other words” when you want to express something in a different way (more simply), to make it easier to understand, or to emphasise or expand on a point. Example: “Frogs are amphibians. In other words, they live on the land and in the water.”

3. To put it another way

Usage: This phrase is another way of saying “in other words”, and can be used in particularly complex points, when you feel that an alternative way of wording a problem may help the reader achieve a better understanding of its significance. Example: “Plants rely on photosynthesis. To put it another way, they will die without the sun.”

4. That is to say

Usage: “That is” and “that is to say” can be used to add further detail to your explanation, or to be more precise. Example: “Whales are mammals. That is to say, they must breathe air.”

5. To that end

Usage: Use “to that end” or “to this end” in a similar way to “in order to” or “so”. Example: “Zoologists have long sought to understand how animals communicate with each other. To that end, a new study has been launched that looks at elephant sounds and their possible meanings.”

Adding additional information to support a point

Students often make the mistake of using synonyms of “and” each time they want to add further information in support of a point they’re making, or to build an argument . Here are some cleverer ways of doing this.

6. Moreover

Usage: Employ “moreover” at the start of a sentence to add extra information in support of a point you’re making. Example: “Moreover, the results of a recent piece of research provide compelling evidence in support of…”

7. Furthermore

Usage:This is also generally used at the start of a sentence, to add extra information. Example: “Furthermore, there is evidence to suggest that…”

8. What’s more

Usage: This is used in the same way as “moreover” and “furthermore”. Example: “What’s more, this isn’t the only evidence that supports this hypothesis.”

9. Likewise

Usage: Use “likewise” when you want to talk about something that agrees with what you’ve just mentioned. Example: “Scholar A believes X. Likewise, Scholar B argues compellingly in favour of this point of view.”

10. Similarly

Usage: Use “similarly” in the same way as “likewise”. Example: “Audiences at the time reacted with shock to Beethoven’s new work, because it was very different to what they were used to. Similarly, we have a tendency to react with surprise to the unfamiliar.”

11. Another key thing to remember

Usage: Use the phrase “another key point to remember” or “another key fact to remember” to introduce additional facts without using the word “also”. Example: “As a Romantic, Blake was a proponent of a closer relationship between humans and nature. Another key point to remember is that Blake was writing during the Industrial Revolution, which had a major impact on the world around him.”

12. As well as

Usage: Use “as well as” instead of “also” or “and”. Example: “Scholar A argued that this was due to X, as well as Y.”

13. Not only… but also

Usage: This wording is used to add an extra piece of information, often something that’s in some way more surprising or unexpected than the first piece of information. Example: “Not only did Edmund Hillary have the honour of being the first to reach the summit of Everest, but he was also appointed Knight Commander of the Order of the British Empire.”

14. Coupled with

Usage: Used when considering two or more arguments at a time. Example: “Coupled with the literary evidence, the statistics paint a compelling view of…”

15. Firstly, secondly, thirdly…

Usage: This can be used to structure an argument, presenting facts clearly one after the other. Example: “There are many points in support of this view. Firstly, X. Secondly, Y. And thirdly, Z.

16. Not to mention/to say nothing of

Usage: “Not to mention” and “to say nothing of” can be used to add extra information with a bit of emphasis. Example: “The war caused unprecedented suffering to millions of people, not to mention its impact on the country’s economy.”

Words and phrases for demonstrating contrast

When you’re developing an argument, you will often need to present contrasting or opposing opinions or evidence – “it could show this, but it could also show this”, or “X says this, but Y disagrees”. This section covers words you can use instead of the “but” in these examples, to make your writing sound more intelligent and interesting.

17. However

Usage: Use “however” to introduce a point that disagrees with what you’ve just said. Example: “Scholar A thinks this. However, Scholar B reached a different conclusion.”

18. On the other hand

Usage: Usage of this phrase includes introducing a contrasting interpretation of the same piece of evidence, a different piece of evidence that suggests something else, or an opposing opinion. Example: “The historical evidence appears to suggest a clear-cut situation. On the other hand, the archaeological evidence presents a somewhat less straightforward picture of what happened that day.”

19. Having said that

Usage: Used in a similar manner to “on the other hand” or “but”. Example: “The historians are unanimous in telling us X, an agreement that suggests that this version of events must be an accurate account. Having said that, the archaeology tells a different story.”

20. By contrast/in comparison

Usage: Use “by contrast” or “in comparison” when you’re comparing and contrasting pieces of evidence. Example: “Scholar A’s opinion, then, is based on insufficient evidence. By contrast, Scholar B’s opinion seems more plausible.”

21. Then again

Usage: Use this to cast doubt on an assertion. Example: “Writer A asserts that this was the reason for what happened. Then again, it’s possible that he was being paid to say this.”

22. That said

Usage: This is used in the same way as “then again”. Example: “The evidence ostensibly appears to point to this conclusion. That said, much of the evidence is unreliable at best.”

Usage: Use this when you want to introduce a contrasting idea. Example: “Much of scholarship has focused on this evidence. Yet not everyone agrees that this is the most important aspect of the situation.”

Adding a proviso or acknowledging reservations

Sometimes, you may need to acknowledge a shortfalling in a piece of evidence, or add a proviso. Here are some ways of doing so.

24. Despite this

Usage: Use “despite this” or “in spite of this” when you want to outline a point that stands regardless of a shortfalling in the evidence. Example: “The sample size was small, but the results were important despite this.”

25. With this in mind

Usage: Use this when you want your reader to consider a point in the knowledge of something else. Example: “We’ve seen that the methods used in the 19th century study did not always live up to the rigorous standards expected in scientific research today, which makes it difficult to draw definite conclusions. With this in mind, let’s look at a more recent study to see how the results compare.”

26. Provided that

Usage: This means “on condition that”. You can also say “providing that” or just “providing” to mean the same thing. Example: “We may use this as evidence to support our argument, provided that we bear in mind the limitations of the methods used to obtain it.”

27. In view of/in light of

Usage: These phrases are used when something has shed light on something else. Example: “In light of the evidence from the 2013 study, we have a better understanding of…”

28. Nonetheless

Usage: This is similar to “despite this”. Example: “The study had its limitations, but it was nonetheless groundbreaking for its day.”

29. Nevertheless

Usage: This is the same as “nonetheless”. Example: “The study was flawed, but it was important nevertheless.”

30. Notwithstanding

Usage: This is another way of saying “nonetheless”. Example: “Notwithstanding the limitations of the methodology used, it was an important study in the development of how we view the workings of the human mind.”

Giving examples

Good essays always back up points with examples, but it’s going to get boring if you use the expression “for example” every time. Here are a couple of other ways of saying the same thing.

31. For instance

Example: “Some birds migrate to avoid harsher winter climates. Swallows, for instance, leave the UK in early winter and fly south…”

32. To give an illustration

Example: “To give an illustration of what I mean, let’s look at the case of…”

Signifying importance

When you want to demonstrate that a point is particularly important, there are several ways of highlighting it as such.

33. Significantly

Usage: Used to introduce a point that is loaded with meaning that might not be immediately apparent. Example: “Significantly, Tacitus omits to tell us the kind of gossip prevalent in Suetonius’ accounts of the same period.”

34. Notably

Usage: This can be used to mean “significantly” (as above), and it can also be used interchangeably with “in particular” (the example below demonstrates the first of these ways of using it). Example: “Actual figures are notably absent from Scholar A’s analysis.”

35. Importantly

Usage: Use “importantly” interchangeably with “significantly”. Example: “Importantly, Scholar A was being employed by X when he wrote this work, and was presumably therefore under pressure to portray the situation more favourably than he perhaps might otherwise have done.”

Summarising

You’ve almost made it to the end of the essay, but your work isn’t over yet. You need to end by wrapping up everything you’ve talked about, showing that you’ve considered the arguments on both sides and reached the most likely conclusion. Here are some words and phrases to help you.

36. In conclusion

Usage: Typically used to introduce the concluding paragraph or sentence of an essay, summarising what you’ve discussed in a broad overview. Example: “In conclusion, the evidence points almost exclusively to Argument A.”

37. Above all

Usage: Used to signify what you believe to be the most significant point, and the main takeaway from the essay. Example: “Above all, it seems pertinent to remember that…”

38. Persuasive

Usage: This is a useful word to use when summarising which argument you find most convincing. Example: “Scholar A’s point – that Constanze Mozart was motivated by financial gain – seems to me to be the most persuasive argument for her actions following Mozart’s death.”

39. Compelling

Usage: Use in the same way as “persuasive” above. Example: “The most compelling argument is presented by Scholar A.”

40. All things considered

Usage: This means “taking everything into account”. Example: “All things considered, it seems reasonable to assume that…”

How many of these words and phrases will you get into your next essay? And are any of your favourite essay terms missing from our list? Let us know in the comments below, or get in touch here to find out more about courses that can help you with your essays.

At Oxford Royale Academy, we offer a number of  summer school courses for young people who are keen to improve their essay writing skills. Click here to apply for one of our courses today, including law , business , medicine  and engineering .

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Words to Use in an Essay: 300 Essay Words

Hannah Yang

Table of Contents

Words to use in the essay introduction, words to use in the body of the essay, words to use in your essay conclusion, how to improve your essay writing vocabulary.

It’s not easy to write an academic essay .

Many students struggle to word their arguments in a logical and concise way.

To make matters worse, academic essays need to adhere to a certain level of formality, so we can’t always use the same word choices in essay writing that we would use in daily life.

If you’re struggling to choose the right words for your essay, don’t worry—you’ve come to the right place!

In this article, we’ve compiled a list of over 300 words and phrases to use in the introduction, body, and conclusion of your essay.

The introduction is one of the hardest parts of an essay to write.

You have only one chance to make a first impression, and you want to hook your reader. If the introduction isn’t effective, the reader might not even bother to read the rest of the essay.

That’s why it’s important to be thoughtful and deliberate with the words you choose at the beginning of your essay.

Many students use a quote in the introductory paragraph to establish credibility and set the tone for the rest of the essay.

When you’re referencing another author or speaker, try using some of these phrases:

To use the words of X

According to X

As X states

Example: To use the words of Hillary Clinton, “You cannot have maternal health without reproductive health.”

Near the end of the introduction, you should state the thesis to explain the central point of your paper.

If you’re not sure how to introduce your thesis, try using some of these phrases:

In this essay, I will…

The purpose of this essay…

This essay discusses…

In this paper, I put forward the claim that…

There are three main arguments for…

Example: In this essay, I will explain why dress codes in public schools are detrimental to students.

After you’ve stated your thesis, it’s time to start presenting the arguments you’ll use to back up that central idea.

When you’re introducing the first of a series of arguments, you can use the following words:

First and foremost

First of all

To begin with

Example: First , consider the effects that this new social security policy would have on low-income taxpayers.

All these words and phrases will help you create a more successful introduction and convince your audience to read on.

The body of your essay is where you’ll explain your core arguments and present your evidence.

It’s important to choose words and phrases for the body of your essay that will help the reader understand your position and convince them you’ve done your research.

Let’s look at some different types of words and phrases that you can use in the body of your essay, as well as some examples of what these words look like in a sentence.

Transition Words and Phrases

Transitioning from one argument to another is crucial for a good essay.

It’s important to guide your reader from one idea to the next so they don’t get lost or feel like you’re jumping around at random.

Transition phrases and linking words show your reader you’re about to move from one argument to the next, smoothing out their reading experience. They also make your writing look more professional.

The simplest transition involves moving from one idea to a separate one that supports the same overall argument. Try using these phrases when you want to introduce a second correlating idea:

Additionally

In addition

Furthermore

Another key thing to remember

In the same way

Correspondingly

Example: Additionally , public parks increase property value because home buyers prefer houses that are located close to green, open spaces.

Another type of transition involves restating. It’s often useful to restate complex ideas in simpler terms to help the reader digest them. When you’re restating an idea, you can use the following words:

In other words

To put it another way

That is to say

To put it more simply

Example: “The research showed that 53% of students surveyed expressed a mild or strong preference for more on-campus housing. In other words , over half the students wanted more dormitory options.”

Often, you’ll need to provide examples to illustrate your point more clearly for the reader. When you’re about to give an example of something you just said, you can use the following words:

For instance

To give an illustration of

To exemplify

To demonstrate

As evidence

Example: Humans have long tried to exert control over our natural environment. For instance , engineers reversed the Chicago River in 1900, causing it to permanently flow backward.

Sometimes, you’ll need to explain the impact or consequence of something you’ve just said.

When you’re drawing a conclusion from evidence you’ve presented, try using the following words:

As a result

Accordingly

As you can see

This suggests that

It follows that

It can be seen that

For this reason

For all of those reasons

Consequently

Example: “There wasn’t enough government funding to support the rest of the physics experiment. Thus , the team was forced to shut down their experiment in 1996.”

When introducing an idea that bolsters one you’ve already stated, or adds another important aspect to that same argument, you can use the following words:

What’s more

Not only…but also

Not to mention

To say nothing of

Another key point

Example: The volcanic eruption disrupted hundreds of thousands of people. Moreover , it impacted the local flora and fauna as well, causing nearly a hundred species to go extinct.

Often, you'll want to present two sides of the same argument. When you need to compare and contrast ideas, you can use the following words:

On the one hand / on the other hand

Alternatively

In contrast to

On the contrary

By contrast

In comparison

Example: On the one hand , the Black Death was undoubtedly a tragedy because it killed millions of Europeans. On the other hand , it created better living conditions for the peasants who survived.

Finally, when you’re introducing a new angle that contradicts your previous idea, you can use the following phrases:

Having said that

Differing from

In spite of

With this in mind

Provided that

Nevertheless

Nonetheless

Notwithstanding

Example: Shakespearean plays are classic works of literature that have stood the test of time. Having said that , I would argue that Shakespeare isn’t the most accessible form of literature to teach students in the twenty-first century.

Good essays include multiple types of logic. You can use a combination of the transitions above to create a strong, clear structure throughout the body of your essay.

Strong Verbs for Academic Writing

Verbs are especially important for writing clear essays. Often, you can convey a nuanced meaning simply by choosing the right verb.

You should use strong verbs that are precise and dynamic. Whenever possible, you should use an unambiguous verb, rather than a generic verb.

For example, alter and fluctuate are stronger verbs than change , because they give the reader more descriptive detail.

Here are some useful verbs that will help make your essay shine.

Verbs that show change:

Accommodate

Verbs that relate to causing or impacting something:

Verbs that show increase:

Verbs that show decrease:

Deteriorate

Verbs that relate to parts of a whole:

Comprises of

Is composed of

Constitutes

Encompasses

Incorporates

Verbs that show a negative stance:

Misconstrue

Verbs that show a positive stance:

Substantiate

Verbs that relate to drawing conclusions from evidence:

Corroborate

Demonstrate

Verbs that relate to thinking and analysis:

Contemplate

Hypothesize

Investigate

Verbs that relate to showing information in a visual format:

Useful Adjectives and Adverbs for Academic Essays

You should use adjectives and adverbs more sparingly than verbs when writing essays, since they sometimes add unnecessary fluff to sentences.

However, choosing the right adjectives and adverbs can help add detail and sophistication to your essay.

Sometimes you'll need to use an adjective to show that a finding or argument is useful and should be taken seriously. Here are some adjectives that create positive emphasis:

Significant

Other times, you'll need to use an adjective to show that a finding or argument is harmful or ineffective. Here are some adjectives that create a negative emphasis:

Controversial

Insignificant

Questionable

Unnecessary

Unrealistic

Finally, you might need to use an adverb to lend nuance to a sentence, or to express a specific degree of certainty. Here are some examples of adverbs that are often used in essays:

Comprehensively

Exhaustively

Extensively

Respectively

Surprisingly

Using these words will help you successfully convey the key points you want to express. Once you’ve nailed the body of your essay, it’s time to move on to the conclusion.

The conclusion of your paper is important for synthesizing the arguments you’ve laid out and restating your thesis.

In your concluding paragraph, try using some of these essay words:

In conclusion

To summarize

In a nutshell

Given the above

As described

All things considered

Example: In conclusion , it’s imperative that we take action to address climate change before we lose our coral reefs forever.

In addition to simply summarizing the key points from the body of your essay, you should also add some final takeaways. Give the reader your final opinion and a bit of a food for thought.

To place emphasis on a certain point or a key fact, use these essay words:

Unquestionably

Undoubtedly

Particularly

Importantly

Conclusively

It should be noted

On the whole

Example: Ada Lovelace is unquestionably a powerful role model for young girls around the world, and more of our public school curricula should include her as a historical figure.

These concluding phrases will help you finish writing your essay in a strong, confident way.

There are many useful essay words out there that we didn't include in this article, because they are specific to certain topics.

If you're writing about biology, for example, you will need to use different terminology than if you're writing about literature.

So how do you improve your vocabulary skills?

The vocabulary you use in your academic writing is a toolkit you can build up over time, as long as you take the time to learn new words.

One way to increase your vocabulary is by looking up words you don’t know when you’re reading.

Try reading more books and academic articles in the field you’re writing about and jotting down all the new words you find. You can use these words to bolster your own essays.

You can also consult a dictionary or a thesaurus. When you’re using a word you’re not confident about, researching its meaning and common synonyms can help you make sure it belongs in your essay.

Don't be afraid of using simpler words. Good essay writing boils down to choosing the best word to convey what you need to say, not the fanciest word possible.

Finally, you can use ProWritingAid’s synonym tool or essay checker to find more precise and sophisticated vocabulary. Click on weak words in your essay to find stronger alternatives.

There you have it: our compilation of the best words and phrases to use in your next essay . Good luck!

Good writing = better grades

ProWritingAid will help you improve the style, strength, and clarity of all your assignments.

Hannah Yang is a speculative fiction writer who writes about all things strange and surreal. Her work has appeared in Analog Science Fiction, Apex Magazine, The Dark, and elsewhere, and two of her stories have been finalists for the Locus Award. Her favorite hobbies include watercolor painting, playing guitar, and rock climbing. You can follow her work on hannahyang.com, or subscribe to her newsletter for publication updates.

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300+ Words To Use In An Essay

Here is our top list of essay words you can add to your writing.

Any student or academic will tell you writing academic papers requires patience, thorough research, and appropriate words to relay ideas effectively. Below, we have prepared a list of essay words for your essay or academic piece’s introduction, body, and conclusion.

What Are Essay Words?

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Along with a paper’s arguments, format, and structure, essay words are used to adequately explain the subject in a formal but clear manner. Picking the correct phrases and words helps your audience realize your key point and persuade them to follow your thinking.

Plus, applying suitable words to introduce and expound ideas convinces your readers that you’ve done your research correctly. These English essay words are also helpful if you spend time paraphrasing the ideas of other writers and academics. If you need more help, consider using a good essay checker .

Good Vocabulary Words to Use in Essays

Here are some common essay words you can use:

Most academic essays require a formal writing style because using informal writing makes it hard to edit and grade based on a standard the school or university gives. Even personal and narrative essays must stay formal. These are the words to create and enhance your introduction without losing the sense of formality in academic writing.

According to the most recent data, more employees prefer working at home than in the office.

This essay will address the issue of gender inequality in the workforce.

In this essay, we will analyze the various factors that contribute to climate change.

The approach we’ll use in discussing this topic involves a combination of qualitative and quantitative analysis.

Some experts argue that human activities are the major contributors to global warming.

The author asserts that the lack of early education is one of the main drivers of economic inequality.

Let’s assume for a moment that we’ve already optimized all renewable energy sources.

Before we begin analyzing the effects of the problem, we must first know the root of it.

This essay takes a broad look at the implications of global warming on agricultural productivity.

• Challenging

Drug addiction is the most challenging global problem every government must solve.

Mental illness is a topic with many complex issues.

We will consider both sides of the argument before drawing conclusions.

• Significance

What is the significance of following rules?

In the context of this discussion, “productivity” refers to the output of a worker per hour.

Mental health is a sensitive topic affecting people of all ages.

There is a debate about the effectiveness of the new tax policy in reducing income disparity.

This essay will detail the causes and effects of deforestation.

Our task is to determine the causes of the rise in mental health issues among college students.

We will discuss the ethical implications of genetic engineering in this essay.

This essay will elaborate on the role of social movements in bringing about societal change.

In the next section, the researchers will enumerate the benefits of adopting a plant-based diet.

We will evaluate the impact of climate change on biodiversity.

This essay will explore the important aspect of artificial intelligence in modern healthcare.

To understand the subject better, we will first discuss its history.

First and foremost , it’s essential to understand that not all politicians are bad.

We can learn a lot from the book “ The Little Prince ,” such as about the fundamental nature of love.

The essay will highlight the importance of community participation in local governance.

This essay will illuminate the effects of screen time on children’s development.

This essay will introduce the concept of sustainable development and its significance.

The main goal of this essay is to discuss the value of justice in our lives.

There’s a myriad of factors that affect a country’s tourism.

The objective of this essay is to spread awareness about the violence women and children face daily. 

An overview of the current state of renewable energy technologies will be provided in this essay.

We will present an argument in favor of implementing more stringent environmental regulations.

Lack of knowledge in managing finances is a prevalent problem today.

A good speaker delivers their speech without referring to notes.

In this essay, we will review studies related to the impact of social media on teenagers.

Let’s shed some light on the impact of fast fashion on the environment in this essay.

The youth’s mental state today has been disturbed by societal pressures, such as the impossible beauty standards they see on social media. 

Research suggests that adolescent mental health can be severely affected by excessive screen time.

• To that end

To that end , this essay aims to challenge conventional thinking and inspire more inclusive practices in our communities.

This essay will touch on the issue of gender disparity in corporate leadership.

We will unpack the factors contributing to the rapid development of technology.

My essay aims to validate the hypothesis that a healthier diet can significantly reduce the risk of heart disease.

This essay will weigh the pros and cons of genetic modification in agriculture.

We’ll zoom in on the specific impacts of pollution on marine ecosystems in this essay.

Essays need examples to present arguments and illustrate cases. Examples support claims offer evidence, make complex concepts easier for readers, and usually lead to higher grades! Knowing several essay words for giving examples is vital to avoid the repetition of similar words or phrases. 

Akin to the effects of climate change, deforestation also leads to a significant increase in greenhouse gas emissions.

To analogize, the effect of deforestation on our planet is like removing the lungs from a living organism.

It appears from recent studies that regular exercise can improve mental health.

Our justice system’s flaws are apparent, such as in the case of O.J. Simpson , who was acquitted despite murdering his wife.

To clarify, this essay argues that renewable energy is more sustainable than fossil fuels.

This essay conveys the importance of cultivating empathy in a diverse society.

• Corroborate

Recent studies corroborate the theory that mindfulness meditation can reduce stress.

• Demonstrate

Statistics demonstrate a significant correlation between diet and heart disease.

This essay will depict the socio-economic impacts of the ongoing pandemic.

Current research discloses a worrying trend of increasing cyber threats.

The data displays a significant increase in the usage of renewable energy sources.

To elucidate, this essay aims to explore the intricate relationship between mental health and social media use.

The evidence suggests that pollution is a major factor contributing to global warming.

The effects of climate change exemplify the urgent need for environmental preservation.

The graphs below exhibit the significant impact of human activities on climate change.

• For example

For example, a diet rich in fruits and vegetables can significantly lower the risk of heart disease.

• For instance

For instance, aerobic exercises like running and swimming improve cardiovascular health.

• I.e. (Id est)

A healthy lifestyle, i.e., a balanced diet and regular exercise, can prevent numerous diseases.

This essay will illustrate how technology has transformed modern education.

Imagine if we could harness all the power from the sun; we would have an unlimited source of clean energy.

• In other words

In other words, this essay will deconstruct the complexities of artificial intelligence in layman’s terms.

The data indicates a steady decline in the population of bees worldwide.

Like a domino effect, one small change can trigger a series of events in an ecosystem.

This essay will outline the main strategies for maintaining mental wellness amid a pandemic.

This essay seeks to portray the various forms of discrimination prevalent in society.

• Pretend that

Pretend that each tree cut down is a breath of air taken away; perhaps then we’ll understand the severity of deforestation.

The melting polar ice caps are undeniable proof of global warming.

This essay proposes a holistic approach to dealing with the issue of cyberbullying.

Each data point represents a respondent’s opinion in the survey.

Recent studies reveal a direct correlation between screen time and sleep disorders.

The experts say that practicing mindfulness can help reduce anxiety.

The graphs show a significant increase in the global temperature over the past century.

Similar to how a car needs fuel to run, our bodies need a balanced diet for optimal performance.

The current situation with the global pandemic has underscored the importance of mental health.

• Substantiate

The studies substantiate the claim that smoking can lead to a multitude of health issues.

In this context, melting ice caps symbolize the urgent need for climate action.

The data tells us that stress levels have spiked during the pandemic.

The increasing global temperatures are a testament to the impact of human activities on climate change.

• To give an idea

To give an idea, think of the human brain as a super-computer, continuously processing and storing information.

The goal of this essay is to underline the importance of sustainable practices.

The findings verify the hypothesis that meditation can improve mental health.

These words appear throughout the essay but are mainly for the body. You can use these words to effectively show the importance of an argument and emphasize essential paragraphs in your essay.

Above all, it’s essential to maintain a balance between work and personal life for overall well-being.

• Acknowledge

We must acknowledge the crucial role of teachers in shaping the future of our society.

Environmentalists advocate for sustainable practices to mitigate climate change effects.

The research affirms the beneficial impact of regular exercise on mental health.

The government is taking measures to amplify the reach of digital literacy.

Adding evidence from credible sources can bolster your argument in an essay.

The author cites numerous studies to support his theory of human behavior.

• Conclusively

Conclusively, the findings suggest a strong correlation between diet and heart health.

The experiments confirm the effectiveness of the vaccine against the virus.

Some experts contend that implementing a carbon tax reduces greenhouse gas emissions.

These new findings contradict the previously held beliefs about the origins of the universe.

The president will declare a state of emergency in a few days.

Exercise can definitely improve your mood and energy levels.

The speaker emphasizes the need for more mental health services.

Many celebrities endorse the idea of adopting a plant-based diet for environmental reasons.

Children, especially, should be taught the value of resilience from an early age.

These viral scandals expose the corruption within the political system.

The law expressly forbids discrimination based on race or gender.

The situation is extremely concerning and requires immediate attention.

The fact is that climate change is a reality we must confront.

We should focus on adopting renewable sources of energy to mitigate climate change.

• Fundamentally

Fundamentally, equality is a basic human right that everyone deserves.

The data seems to imply a shift in consumer behavior towards sustainable products.

• Importantly

Importantly, regular check-ups are crucial for early detection of diseases.

• in light of

In light of recent research, it’s vital to re-examine the previous findings.

Regular exercise, indeed, has been proven to reduce the risk of chronic illnesses.

• Irrefutable

The damaging effects of plastic pollution on marine life are irrefutable .

We must maintain a commitment to practice sustainability in our daily lives.

• Make certain of

Before the researchers start any experiments, they must make certain of procedures and goals.

Several factors contribute to climate change, namely deforestation, industrial pollution, and urbanization.

It’s necessary to reduce our carbon footprint to protect the planet.

Notably, the use of renewable energy has been making significant progress in recent years.

Obviously, a balanced diet and regular exercise are key to maintaining a healthy lifestyle.

• On the whole

On the whole, implementing green practices can significantly improve our environmental impact.

• Particularly

Air pollution is a concern, particularly in densely populated cities.

The study points out the beneficial effects of meditation in reducing stress.

The organization is primarily focused on promoting gender equality.

The success stories reinforce the importance of perseverance and hard work.

I would like to reiterate the need for consistent efforts in maintaining mental health.

• Significantly

Regular physical activity can significantly decrease the risk of heart disease.

The project was singularly successful due to the dedicated efforts of the team.

• Specifically

The legislation specifically targets unfair practices in the industry.

Ultimately, the decision rests on the collective agreement of the team.

Alice in Wonderland syndrome, or AIWS , is undeniably one of the rarest diseases.

• Undoubtedly

Undoubtedly, regular reading considerably enhances vocabulary and comprehension skills.

• Unquestionably

Unquestionably, education plays a pivotal role in societal development.

These words show the order of events or progress in an essay. They are used to give examples to further expound on a point or introduce another concept. However, be careful that each paragraph should only focus on one idea.

After completing the coursework, the students began preparing for the final exams.

The team celebrated their victory, afterwards, they began to prepare for the next season.

He accepted the job, albeit with some reservations.

As soon as the rain stopped, we left for our hike.

Before the introduction of modern technology, tasks were manually done.

• Concurrently

The two events were happening concurrently, no wonder there was a scheduling conflict.

• Consecutively

She was late for work three days consecutively .

• Consequently

He forgot his wallet, consequently, he couldn’t pay for lunch.

• Continually

The organization is continually striving to improve its services.

She loves the beach. Conversely, he prefers the mountains.

The team is currently working on the new project.

During the conference, several new initiatives were announced.

Earlier in the day, we had discussed the pros and cons.

Eventually, she managed to finish her book.

Firstly, we need to identify the root of the problem.

Following the events yesterday, we decided to meet up today.

He was tired, hence he went to bed early.

Henceforth, all meetings will be held in the new conference room.

Hereafter, we must ensure that all protocols are strictly followed.

• Immediately

He left immediately after the meeting.

• In the interim

In the interim, we’ll continue with our current strategies.

• In the meantime

In the meantime, let’s clean up the workspace.

• Incidentally

Incidentally, I came across this book while cleaning my attic.

With the constant disagreements, the project inevitably failed.

She invariably arrives late for meetings.

We decided to postpone the discussion for later .

Latterly, there has been a surge in the use of online learning platforms.

He will cook dinner. Meanwhile, I will set the table.

• Momentarily

He was momentarily distracted by the noise.

Next, we need to review the project plan.

• Periodically

The software updates periodically to ensure optimal performance.

She is presently attending a conference in New York.

Previously, we discussed the risks involved in the project.

Prior to the event, we need to finalize all arrangements.

• Sequentially

The tasks must be completed sequentially .

• Simultaneously

We cannot handle multiple tasks simultaneously .

She will arrive soon .

• Subsequently

He completed his degree and subsequently found a job in the field.

The power suddenly went out.

He got promoted and thereafter received a substantial raise in salary.

Thereupon, he decided to retire and write a book.

Thus, we conclude our discussion.

Keep stirring until the sugar dissolves.

We will begin when everyone arrives.

Call me whenever you need help.

While she cooked the meal, he set the table.

No matter what type of essay you write, it should remain informative. Words used to add information create flow, expand arguments, and incorporate details that support your points.

She’s asking him about that project the boss wants them to do.

The results were not as bad as anticipated; actually, they were quite good.

This is a great product; in addition, it’s very affordable.

• Additionally

The car is economical; additionally, it’s environmentally friendly.

She tried again after failing the first time.

He worked alongside his colleagues to complete the project.

We will also need to consider the budget.

• Alternatively

If the plan fails, we could alternatively try a different approach.

She likes to read books and watch movies.

He is open to another perspective on the matter.

She will attend the meeting as well .

The project will assuredly be completed on time.

Besides the main dish, we also have a variety of desserts.

She will certainly appreciate the gesture.

The rules were clearly explained to everyone.

This is a problem commonly encountered in this field.

• Complementary

The two studies are complementary, providing a comprehensive understanding of the issue.

• Correspondingly

The workload increased, and correspondingly, the need for more staff became apparent.

The increased workload, coupled with tight deadlines, created a stressful atmosphere.

The team members contributed equally to the project.

The cake was delicious, and the icing made it even more enjoyable.

• Furthermore

He is qualified for the job; furthermore, he has relevant experience.

• In addition

She is a great leader; in addition, she is an excellent communicator.

• In contrast

He is outgoing; in contrast, his brother is quite shy.

She did not like the book; in fact, she found it boring.

• In particular

She loves flowers, roses in particular .

It appears simple; in reality, it’s quite complex.

• In the same way

He treats all his employees fairly, in the same way he would like to be treated.

He enjoys reading; likewise, his sister loves books.

• More importantly

She passed the exam; more importantly, she scored highest in the class.

The house is beautiful; moreover, it’s located in a great neighborhood.

• Not only… but also

He is not only a talented musician, but also a great teacher.

• On the one hand

On the one hand, he enjoys his current job; on the other, he aspires for a higher position.

• On top of that

The food was delicious; on top of that, the service was excellent.

She has impressive qualifications; plus, she has a lot of experience.

He was disheartened after failing the exam; similarly, she was upset after losing the match.

He woke up late, and then rushed to work.

He is a skilled programmer; to add, he has an exceptional understanding of user experience design.

• Together with

He completed the project together with his team.

She is tired, and she is hungry too .

• With this in mind

With this in mind, we should proceed cautiously.

These are words used to include information that confirms or disagrees with a point in your essay. Words that compare and contrast ideas are common in argumentative essays . It’s because this type demands a counterargument to fairly present other experts’ take on the issue.

He went to work although he was feeling unwell.

• Analogous to

The structure of an atom is analogous to our solar system.

• As opposed to

She prefers tea as opposed to coffee.

• By the same token

He is a great teacher; by the same token, he is a superb mentor.

• Comparatively

My new laptop works comparatively faster than the old one.

Upon comparison, his work proved far superior.

• Contrariwise

The day was hot; contrariwise, the night was chilly.

Contrary to his usual behavior, he arrived on time.

Her efforts are directly correlated to her success.

His words were counter to his actions.

Despite the rain, they continued the game.

• Different from

His opinion is different from mine.

Their views on the subject are disparate .

• Dissimilar to

His style of writing is dissimilar to that of his peers.

• Distinct from

Her dress is distinct from the others.

• Divergent from

His findings are divergent from the initial hypothesis.

• Equivalent to

His happiness was equivalent to that of a child.

He failed the test; however, he didn’t stop trying.

• In comparison

In comparison, his work is of a higher standard.

He gave a donation in lieu of flowers.

• In like manner

She dresses in like manner to her sister.

• In opposition to

He voted in opposition to the proposed bill.

• In spite of

In spite of the challenges, she never gave up.

• In the same vein

In the same vein, he continued his argument.

He chose to walk instead of taking the bus.

Just as Rome wasn’t built in a day, success doesn’t come overnight.

Much as I appreciate your help, I must do this on my own.

• Nevertheless

He was tired; nevertheless, he continued to work.

• Notwithstanding

Notwithstanding the difficulties, he completed the task on time.

• On the contrary

He is not lazy; on the contrary, he is a hard worker.

• Opposite of

Joy is the opposite of sorrow.

His life parallels that of his father.

• Rather than

She chose to laugh rather than cry.

• Regardless of

Regardless of the consequences, he went ahead with his plan.

His answer is the same as mine.

• Set side by side

When set side by side, the differences are clear.

Though he was late, he still got the job.

Unlike his brother, he is very outgoing.

It was a match of experience versus youth.

He is tall, whereas his brother is short.

He is rich, yet very humble.

The conclusion is an essential part of the essay. The concluding paragraph or section reiterates important points, leaves the readers with something to think about, and wraps up the essay nicely so it doesn’t end abruptly. 

• Accordingly

He performed well on the job; accordingly, he was promoted.

• After all is said and done

After all is said and done, it’s the kindness that counts.

All in all, the concert was a great success.

• All things considered

All things considered, I think we made the best decision.

The event, altogether, was a memorable one.

• As a final observation

As a final observation, her dedication to the project was commendable.

• As a final point

As a final point, the successes outweighed the failures.

• As a result

He worked hard; as a result, he achieved his goals.

His actions were inappropriate; as such, he was reprimanded.

• By and large

By and large, the feedback has been positive.

The event was, chiefly, a success.

In close, I must say the performance was extraordinary.

The evidence was compelling and led to his conviction.

• Effectively

The team effectively handled the project.

• Everything considered

Everything considered, the trip was beneficial.

Evidently, he was not involved in the crime.

Finally, she announced her decision.

• In a nutshell

In a nutshell, the plan was not effective.

• In conclusion

In conclusion, we need to strive for better communication.

• In drawing things to a close

In drawing things to a close, I’d like to thank everyone for their contributions.

In essence, we need to focus on quality, not quantity.

• In retrospect

In retrospect, our methodology was correct.

In summary, the event was a success.

In the end, hard work always pays off.

• In the final analysis

In the final analysis, the project was a success.

• Last but not the least

Last but not the least, we need to thank our sponsors.

Lastly, don’t forget to enjoy the process.

On balance, the benefits outweigh the drawbacks.

Overall, it was a productive meeting.

Summarily, we need to focus on our key strengths.

The report summarizes the main findings of the study.

Summing up, we made significant progress this year.

• Taking everything into account

Taking everything into account, it was a successful campaign.

He was ill; therefore, he couldn’t attend the meeting.

• To cap it all off

To cap it all off, we had a great time at the party.

To close, we need your continued support.

• To conclude

To conclude, let’s aim for higher targets next year.

To finish, remember that success comes to those who dare.

To sum up, we achieved our objectives.

• Without a doubt

Without a doubt, it was an unforgettable experience.

To wrap up, it was a journey worth taking.

Learning how to use the right essay words is just one of the many writing skills students and those writing in academia must develop. Others include a good knowledge of grammar and an ability to write an essay that’s readable and accurate. It just takes practice. Check out our guide packed with transition words for essays .

Some words that could be used to describe different kinds of essays include argumentative, persuasive, expository, narrative, descriptive, analytical, compare and contrast, cause and effect, reflective, and personal.

When writing an essay, it’s important to choose appropriate and effective words to express your ideas clearly and concisely. Here are some words you can use to enhance your essay writing: 1. First, secondly, third 2. Moreover, furthermore, additionally 3. In addition, also, likewise 4. However, nevertheless, yet 5. Although, despite, regardless

Here are some other words that can be used as alternatives for “you” in an essay: yourself, oneself, one, someone, somebody, anyone, everybody, people, individuals, persons, others, them, they, yourselves, thou, thee.

1. Narrative essays 2. Descriptive essays 3. Expository essays 4. Persuasive essays 5. Argumentative essay

Maria Caballero is a freelance writer who has been writing since high school. She believes that to be a writer doesn't only refer to excellent syntax and semantics but also knowing how to weave words together to communicate to any reader effectively.

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100+ Useful Words and Phrases to Write a Great Essay

By: Author Sophia

Posted on Last updated: October 25, 2023

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How to Write a Great Essay in English! This lesson provides 100+ useful words, transition words and expressions used in writing an essay. Let’s take a look!

The secret to a successful essay doesn’t just lie in the clever things you talk about and the way you structure your points.

Useful Words and Phrases to Write a Great Essay

Overview of an essay.

Useful Phrases for Proficiency Essays

Developing the argument

• The first aspect to point out is that…
• Let us start by considering the facts.
• The novel portrays, deals with, revolves around…
• Central to the novel is…
• The character of xxx embodies/ epitomizes…

The other side of the argument

• It would also be interesting to see…
• One should, nevertheless, consider the problem from another angle.
• Equally relevant to the issue are the questions of…
• The arguments we have presented… suggest that…/ prove that…/ would indicate that…
• From these arguments one must…/ could…/ might… conclude that…
• All of this points to the conclusion that…
• To conclude…

Ordering elements

• Firstly,…/ Secondly,…/ Finally,… (note the comma after all these introductory words.)
• As a final point…
• On the one hand, …. on the other hand…
• If on the one hand it can be said that… the same is not true for…
• The first argument suggests that… whilst the second suggests that…
• There are at least xxx points to highlight.

Adding elements

• Furthermore, one should not forget that…
• In addition to…
• Moreover…
• It is important to add that…

Accepting other points of view

• Nevertheless, one should accept that…
• However, we also agree that…

Personal opinion

• We/I personally believe that…
• Our/My own point of view is that…
• It is my contention that…
• I am convinced that…
• My own opinion is…

Others’ opinions

• According to some critics… Critics:
• believe that
• suggest that
• are convinced that
• point out that
• emphasize that
• contend that
• go as far as to say that
• argue for this

Introducing examples

• For example…
• For instance…
• To illustrate this point…

Introducing facts

• It is… true that…/ clear that…/ noticeable that…
• One should note here that…

Saying what you think is true

• This leads us to believe that…
• It is very possible that…
• In view of these facts, it is quite likely that…
• Doubtless,…
• One cannot deny that…
• It is (very) clear from these observations that…
• All the same, it is possible that…
• It is difficult to believe that…

Accepting other points to a certain degree

• One can agree up to a certain point with…
• Certainly,… However,…
• It cannot be denied that…

Emphasizing particular points

• The last example highlights the fact that…
• Not only… but also…
• We would even go so far as to say that…

Moderating, agreeing, disagreeing

• By and large…
• Perhaps we should also point out the fact that…
• It would be unfair not to mention the fact that…
• One must admit that…
• We cannot ignore the fact that…
• One cannot possibly accept the fact that…

Consequences

• From these facts, one may conclude that…
• That is why, in our opinion, …
• Which seems to confirm the idea that…
• Thus,…/ Therefore,…
• Some critics suggest…, whereas others…
• Compared to…
• On the one hand, there is the firm belief that… On the other hand, many people are convinced that…

How to Write a Great Essay | Image 1

How to Write a Great Essay | Image 2

Phrases For Balanced Arguments

Introduction

• It is often said that…
• It is undeniable that…
• It is a well-known fact that…
• One of the most striking features of this text is…
• The first thing that needs to be said is…
• First of all, let us try to analyze…
• One argument in support of…
• We must distinguish carefully between…
• The second reason for…
• An important aspect of the text is…
• It is worth stating at this point that…
• On the other hand, we can observe that…
• The other side of the coin is, however, that…
• Another way of looking at this question is to…
• What conclusions can be drawn from all this?
• The most satisfactory conclusion that we can come to is…
• To sum up… we are convinced that…/ …we believe that…/ …we have to accept that…

How to Write a Great Essay | Image 3

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Words To Use In Essays: Amplifying Your Academic Writing

Use this comprehensive list of words to use in essays to elevate your writing. Make an impression and score higher grades with this guide!

Words play a fundamental role in the domain of essay writing, as they have the power to shape ideas, influence readers, and convey messages with precision and impact. Choosing the right words to use in essays is not merely a matter of filling pages, but rather a deliberate process aimed at enhancing the quality of the writing and effectively communicating complex ideas. In this article, we will explore the importance of selecting appropriate words for essays and provide valuable insights into the types of words that can elevate the essay to new heights.

Words To Use In Essays

Using a wide range of words can make your essay stronger and more impressive. With the incorporation of carefully chosen words that communicate complex ideas with precision and eloquence, the writer can elevate the quality of their essay and captivate readers.

This list serves as an introduction to a range of impactful words that can be integrated into writing, enabling the writer to express thoughts with depth and clarity.

Significantly

Furthermore

Nonetheless

Nevertheless

Consequently

Accordingly

Subsequently

In contrast

Alternatively

Implications

Substantially

Transition Words And Phrases

Transition words and phrases are essential linguistic tools that connect ideas, sentences, and paragraphs within a text. They work like bridges, facilitating the transitions between different parts of an essay or any other written work. These transitional elements conduct the flow and coherence of the writing, making it easier for readers to follow the author’s train of thought.

Here are some examples of common transition words and phrases:

Furthermore: Additionally; moreover.

However: Nevertheless; on the other hand.

In contrast: On the contrary; conversely.

Therefore: Consequently; as a result.

Similarly: Likewise; in the same way.

Moreover: Furthermore; besides.

In addition: Additionally; also.

Nonetheless: Nevertheless; regardless.

Nevertheless: However; even so.

On the other hand: Conversely; in contrast.

These are just a few examples of the many transition words and phrases available. They help create coherence, improve the organization of ideas, and guide readers through the logical progression of the text. When used effectively, transition words and phrases can significantly guide clarity for writing.

Strong Verbs For Academic Writing

Strong verbs are an essential component of academic writing as they add precision, clarity, and impact to sentences. They convey actions, intentions, and outcomes in a more powerful and concise manner. Here are some examples of strong verbs commonly used in academic writing:

Analyze: Examine in detail to understand the components or structure.

Critique: Assess or evaluate the strengths and weaknesses.

Demonstrate: Show the evidence to support a claim or argument.

Illuminate: Clarify or make something clearer.

Explicate: Explain in detail a thorough interpretation.

Synthesize: Combine or integrate information to create a new understanding.

Propose: Put forward or suggest a theory, idea, or solution.

Refute: Disprove or argue against a claim or viewpoint.

Validate: Confirm or prove the accuracy or validity of something.

Advocate: Support or argue in favor of a particular position or viewpoint.

Adjectives And Adverbs For Academic Essays

Useful adjectives and adverbs are valuable tools in academic writing as they enhance the description, precision, and depth of arguments and analysis. They provide specific details, emphasize key points, and add nuance to writing. Here are some examples of useful adjectives and adverbs commonly used in academic essays:

Comprehensive: Covering all aspects or elements; thorough.

Crucial: Extremely important or essential.

Prominent: Well-known or widely recognized; notable.

Substantial: Considerable in size, extent, or importance.

Valid: Well-founded or logically sound; acceptable or authoritative.

Effectively: In a manner that produces the desired result or outcome.

Significantly: To a considerable extent or degree; notably.

Consequently: As a result or effect of something.

Precisely: Exactly or accurately; with great attention to detail.

Critically: In a careful and analytical manner; with careful evaluation or assessment.

Words To Use In The Essay Introduction

The words used in the essay introduction play a crucial role in capturing the reader’s attention and setting the tone for the rest of the essay. They should be engaging, informative, and persuasive. Here are some examples of words that can be effectively used in the essay introduction:

Intriguing: A word that sparks curiosity and captures the reader’s interest from the beginning.

Compelling: Conveys the idea that the topic is interesting and worth exploring further.

Provocative: Creates a sense of controversy or thought-provoking ideas.

Insightful: Suggests that the essay will produce valuable and thought-provoking insights.

Startling: Indicates that the essay will present surprising or unexpected information or perspectives.

Relevant: Emphasizes the significance of the topic and its connection to broader issues or current events.

Timely: Indicates that the essay addresses a subject of current relevance or importance.

Thoughtful: Implies that the essay will offer well-considered and carefully developed arguments.

Persuasive: Suggests that the essay will present compelling arguments to convince the reader.

Captivating: Indicates that the essay will hold the reader’s attention and be engaging throughout.

Words To Use In The Body Of The Essay

The words used in the body of the essay are essential for effectively conveying ideas, providing evidence, and developing arguments. They should be clear, precise, and demonstrate a strong command of the subject matter. Here are some examples of words that can be used in the body of the essay:

Evidence: When presenting supporting information or data, words such as “data,” “research,” “studies,” “findings,” “examples,” or “statistics” can be used to strengthen arguments.

Analysis: To discuss and interpret the evidence, words like “analyze,” “examine,” “explore,” “interpret,” or “assess” can be employed to demonstrate a critical evaluation of the topic.

Comparison: When drawing comparisons or making contrasts, words like “similarly,” “likewise,” “in contrast,” “on the other hand,” or “conversely” can be used to highlight similarities or differences.

Cause and effect: To explain the relationship between causes and consequences, words such as “because,” “due to,” “leads to,” “results in,” or “causes” can be utilized.

Sequence: When discussing a series of events or steps, words like “first,” “next,” “then,” “finally,” “subsequently,” or “consequently” can be used to indicate the order or progression.

Emphasis: To emphasize a particular point or idea, words such as “notably,” “significantly,” “crucially,” “importantly,” or “remarkably” can be employed.

Clarification: When providing further clarification or elaboration, words like “specifically,” “in other words,” “for instance,” “to illustrate,” or “to clarify” can be used.

Integration: To show the relationship between different ideas or concepts, words such as “moreover,” “furthermore,” “additionally,” “likewise,” or “similarly” can be utilized.

Conclusion: When summarizing or drawing conclusions, words like “in conclusion,” “to summarize,” “overall,” “in summary,” or “to conclude” can be employed to wrap up ideas.

Remember to use these words appropriately and contextually, ensuring they strengthen the coherence and flow of arguments. They should serve as effective transitions and connectors between ideas, enhancing the overall clarity and persuasiveness of the essay.

Words To Use In Essay Conclusion

The words used in the essay conclusion are crucial for effectively summarizing the main points, reinforcing arguments, and leaving a lasting impression on the reader. They should bring a sense of closure to the essay while highlighting the significance of ideas. Here are some examples of words that can be used in the essay conclusion:

Summary: To summarize the main points, these words can be used “in summary,” “to sum up,” “in conclusion,” “to recap,” or “overall.”

Reinforcement: To reinforce arguments and emphasize their importance, words such as “crucial,” “essential,” “significant,” “noteworthy,” or “compelling” can be employed.

Implication: To discuss the broader implications of ideas or findings, words like “consequently,” “therefore,” “thus,” “hence,” or “as a result” can be utilized.

Call to action: If applicable, words that encourage further action or reflection can be used, such as “we must,” “it is essential to,” “let us consider,” or “we should.”

Future perspective: To discuss future possibilities or developments related to the topic, words like “potential,” “future research,” “emerging trends,” or “further investigation” can be employed.

Reflection: To reflect on the significance or impact of arguments, words such as “profound,” “notable,” “thought-provoking,” “transformative,” or “perspective-shifting” can be used.

Final thought: To leave a lasting impression, words or phrases that summarize the main idea or evoke a sense of thoughtfulness can be used, such as “food for thought,” “in light of this,” “to ponder,” or “to consider.”

How To Improve Essay Writing Vocabulary

Improving essay writing vocabulary is essential for effectively expressing ideas, demonstrating a strong command of the language, and engaging readers. Here are some strategies to enhance the essay writing vocabulary:

• Read extensively: Reading a wide range of materials, such as books, articles, and essays, can give various writing styles, topics, and vocabulary. Pay attention to new words and their usage, and try incorporating them into the writing.
• Use a dictionary and thesaurus:  Look up unfamiliar words in a dictionary to understand their meanings and usage. Additionally, utilize a thesaurus to find synonyms and antonyms to expand word choices and avoid repetition.
• Create a word bank: To create a word bank, read extensively, write down unfamiliar or interesting words, and explore their meanings and usage. Organize them by categories or themes for easy reference, and practice incorporating them into writing to expand the vocabulary.
• Contextualize vocabulary: Simply memorizing new words won’t be sufficient; it’s crucial to understand their proper usage and context. Pay attention to how words are used in different contexts, sentence structures, and rhetorical devices. 

How To Add Additional Information To Support A Point

When writing an essay and wanting to add additional information to support a point, you can use various transitional words and phrases. Here are some examples:

Furthermore: Add more information or evidence to support the previous point.

Additionally: Indicates an additional supporting idea or evidence.

Moreover: Emphasizes the importance or significance of the added information.

In addition: Signals the inclusion of another supporting detail.

Furthermore, it is important to note: Introduces an additional aspect or consideration related to the topic.

Not only that, but also: Highlights an additional point that strengthens the argument.

Equally important: Emphasizes the equal significance of the added information.

Another key point: Introduces another important supporting idea.

It is worth noting: Draws attention to a noteworthy detail that supports the point being made.

Additionally, it is essential to consider: Indicates the need to consider another aspect or perspective.

Using these transitional words and phrases will help you seamlessly integrate additional information into your essay, enhancing the clarity and persuasiveness of your arguments.

Words And Phrases That Demonstrate Contrast

When crafting an essay, it is crucial to effectively showcase contrast, enabling the presentation of opposing ideas or the highlighting of differences between concepts. The adept use of suitable words and phrases allows for the clear communication of contrast, bolstering the strength of arguments. Consider the following examples of commonly employed words and phrases to illustrate the contrast in essays:

However: e.g., “The experiment yielded promising results; however, further analysis is needed to draw conclusive findings.”

On the other hand: e.g., “Some argue for stricter gun control laws, while others, on the other hand, advocate for individual rights to bear arms.”

Conversely: e.g., “While the study suggests a positive correlation between exercise and weight loss, conversely, other research indicates that diet plays a more significant role.”

Nevertheless: e.g., “The data shows a decline in crime rates; nevertheless, public safety remains a concern for many citizens.”

In contrast: e.g., “The economic policies of Country A focus on free-market principles. In contrast, Country B implements more interventionist measures.”

Despite: e.g., “Despite the initial setbacks, the team persevered and ultimately achieved success.”

Although: e.g., “Although the participants had varying levels of experience, they all completed the task successfully.”

While: e.g., “While some argue for stricter regulations, others contend that personal responsibility should prevail.”

Words To Use For Giving Examples

When writing an essay and providing examples to illustrate your points, you can use a variety of words and phrases to introduce those examples. Here are some examples:

For instance: Introduces a specific example to support or illustrate your point.

For example: Give an example to clarify or demonstrate your argument.

Such as: Indicates that you are providing a specific example or examples.

To illustrate: Signals that you are using an example to explain or emphasize your point.

One example is: Introduces a specific instance that exemplifies your argument.

In particular: Highlights a specific example that is especially relevant to your point.

As an illustration: Introduces an example that serves as a visual or concrete representation of your point.

A case in point: Highlights a specific example that serves as evidence or proof of your argument.

To demonstrate: Indicates that you are providing an example to show or prove your point.

To exemplify: Signals that you are using an example to illustrate or clarify your argument.

Using these words and phrases will help you effectively incorporate examples into your essay, making your arguments more persuasive and relatable. Remember to give clear and concise examples that directly support your main points.

Words To Signifying Importance

When writing an essay and wanting to signify the importance of a particular point or idea, you can use various words and phrases to convey this emphasis. Here are some examples:

Crucially: Indicates that the point being made is of critical importance.

Significantly: Highlights the importance or significance of the idea or information.

Importantly: Draws attention to the crucial nature of the point being discussed.

Notably: Emphasizes that the information or idea is particularly worthy of attention.

It is vital to note: Indicates that the point being made is essential and should be acknowledged.

It should be emphasized: Draws attention to the need to give special importance or focus to the point being made.

A key consideration is: Highlight that the particular idea or information is a central aspect of the discussion.

It is critical to recognize: Emphasizes that the understanding or acknowledgment of the point is crucial.

Using these words and phrases will help you convey the importance and significance of specific points or ideas in your essay, ensuring that readers recognize their significance and impact on the overall argument.

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Academic Phrasebank

• GENERAL LANGUAGE FUNCTIONS
• Being cautious
• Being critical
• Classifying and listing
• Compare and contrast
• Defining terms
• Describing trends
• Describing quantities
• Explaining causality
• Giving examples
• Signalling transition
• Writing about the past

The Academic Phrasebank is a general resource for academic writers. It aims to provide you with examples of some of the phraseological ‘nuts and bolts’ of writing organised according to the main sections of a research paper or dissertation (see the top menu ). Other phrases are listed under the more general communicative functions of academic writing (see the menu on the left). The resource should be particularly useful for writers who need to report their research work. The phrases, and the headings under which they are listed, can be used simply to assist you in thinking about the content and organisation of your own writing, or the phrases can be incorporated into your writing where this is appropriate. In most cases, a certain amount of creativity and adaptation will be necessary when a phrase is used. The items in the Academic Phrasebank are mostly content neutral and generic in nature; in using them, therefore, you are not stealing other people’s ideas and this does not constitute plagiarism. For some of the entries, specific content words have been included for illustrative purposes, and these should be substituted when the phrases are used. The resource was designed primarily for academic and scientific writers who are non-native speakers of English. However, native speaker writers may still find much of the material helpful. In fact, recent data suggest that the majority of users are native speakers of English. More about  Academic Phrasebank .

This site was created by  John Morley .  

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60 Useful Words and Phrases for Outstanding Essay Writing

General explaining.

Let’s start by looking at language for general explanations of complex points.

1. In order to

Usage : “In order to” can be used to introduce an explanation for the purpose of an argument.

Example : “In order to understand X, we need first to understand Y.”

2. In other words

Usage : Use “in other words” when you want to express something in a different way (more simply), to make it easier to understand, or to emphasise or expand on a point.

Example : “Frogs are amphibians. In other words, they live on the land and in the water.”

3. To put it another way

Usage : This phrase is another way of saying “in other words”, and can be used in particularly complex points, when you feel that an alternative way of wording a problem may help the reader achieve a better understanding of its significance.

Example : “Plants rely on photosynthesis. To put it another way, they will die without the sun.”

4. That is to say

Usage : “That is” and “that is to say” can be used to add further detail to your explanation, or to be more precise.

Example : “Whales are mammals. That is to say, they must breathe air.”

5. To that end

Usage : Use “to that end” or “to this end” in a similar way to “in order to” or “so”.

Example : “Zoologists have long sought to understand how animals communicate with each other. To that end, a new study has been launched that looks at elephant sounds and their possible meanings.”

Adding additional information to support a point

Students often make the mistake of using synonyms of “and” each time they want to add further information in support of a point they’re making, or to build an argument. Here are some cleverer ways of doing this.

6. Moreover

Usage : Employ “moreover” at the start of a sentence to add extra information in support of a point you’re making.

Example : “Moreover, the results of a recent piece of research provide compelling evidence in support of…”

7. Furthermore

Usage :This is also generally used at the start of a sentence, to add extra information.

Example : “Furthermore, there is evidence to suggest that…”

8. What’s more

Usage : This is used in the same way as “moreover” and “furthermore”.

Example : “What’s more, this isn’t the only evidence that supports this hypothesis.”

9. Likewise

Usage : Use “likewise” when you want to talk about something that agrees with what you’ve just mentioned.

Example : “Scholar A believes X. Likewise, Scholar B argues compellingly in favour of this point of view.”

10. Similarly

Usage : Use “similarly” in the same way as “likewise”.

Example : “Audiences at the time reacted with shock to Beethoven’s new work, because it was very different to what they were used to. Similarly, we have a tendency to react with surprise to the unfamiliar.”

11. Another key thing to remember

Usage : Use the phrase “another key point to remember” or “another key fact to remember” to introduce additional facts without using the word “also”.

Example : “As a Romantic, Blake was a proponent of a closer relationship between humans and nature. Another key point to remember is that Blake was writing during the Industrial Revolution, which had a major impact on the world around him.”

12. As well as

Usage : Use “as well as” instead of “also” or “and”.

Example : “Scholar A argued that this was due to X, as well as Y.”

13. Not only… but also

Usage : This wording is used to add an extra piece of information, often something that’s in some way more surprising or unexpected than the first piece of information.

Example : “Not only did Edmund Hillary have the honour of being the first to reach the summit of Everest, but he was also appointed Knight Commander of the Order of the British Empire.”

14. Coupled with

Usage : Used when considering two or more arguments at a time.

Example : “Coupled with the literary evidence, the statistics paint a compelling view of…”

15. Firstly, secondly, thirdly…

Usage : This can be used to structure an argument, presenting facts clearly one after the other.

Example : “There are many points in support of this view. Firstly, X. Secondly, Y. And thirdly, Z.

16. Not to mention/to say nothing of

Usage : “Not to mention” and “to say nothing of” can be used to add extra information with a bit of emphasis.

Example : “The war caused unprecedented suffering to millions of people, not to mention its impact on the country’s economy.”

Words and phrases for demonstrating contrast

When you’re developing an argument, you will often need to present contrasting or opposing opinions or evidence – “it could show this, but it could also show this”, or “X says this, but Y disagrees”. This section covers words you can use instead of the “but” in these examples, to make your writing sound more intelligent and interesting.

17. However

Usage : Use “however” to introduce a point that disagrees with what you’ve just said.

Example : “Scholar A thinks this. However, Scholar B reached a different conclusion.”

18. On the other hand

Usage : Usage of this phrase includes introducing a contrasting interpretation of the same piece of evidence, a different piece of evidence that suggests something else, or an opposing opinion.

Example: “The historical evidence appears to suggest a clear-cut situation. On the other hand, the archaeological evidence presents a somewhat less straightforward picture of what happened that day.”

19. Having said that

Usage : Used in a similar manner to “on the other hand” or “but”.

Example : “The historians are unanimous in telling us X, an agreement that suggests that this version of events must be an accurate account. Having said that, the archaeology tells a different story.”

20. By contrast/in comparison

Usage : Use “by contrast” or “in comparison” when you’re comparing and contrasting pieces of evidence.

Example : “Scholar A’s opinion, then, is based on insufficient evidence. By contrast, Scholar B’s opinion seems more plausible.”

21. Then again

Usage : Use this to cast doubt on an assertion.

Example : “Writer A asserts that this was the reason for what happened. Then again, it’s possible that he was being paid to say this.”

22. That said

Usage : This is used in the same way as “then again”.

Example : “The evidence ostensibly appears to point to this conclusion. That said, much of the evidence is unreliable at best.”

Usage : Use this when you want to introduce a contrasting idea.

Example : “Much of scholarship has focused on this evidence. Yet not everyone agrees that this is the most important aspect of the situation.”

Adding a proviso or acknowledging reservations

Sometimes, you may need to acknowledge a shortfalling in a piece of evidence, or add a proviso. Here are some ways of doing so.

24. Despite this

Usage : Use “despite this” or “in spite of this” when you want to outline a point that stands regardless of a shortfalling in the evidence.

Example : “The sample size was small, but the results were important despite this.”

25. With this in mind

Usage : Use this when you want your reader to consider a point in the knowledge of something else.

Example : “We’ve seen that the methods used in the 19th century study did not always live up to the rigorous standards expected in scientific research today, which makes it difficult to draw definite conclusions. With this in mind, let’s look at a more recent study to see how the results compare.”

26. Provided that

Usage : This means “on condition that”. You can also say “providing that” or just “providing” to mean the same thing.

Example : “We may use this as evidence to support our argument, provided that we bear in mind the limitations of the methods used to obtain it.”

27. In view of/in light of

Usage : These phrases are used when something has shed light on something else.

Example : “In light of the evidence from the 2013 study, we have a better understanding of…”

28. Nonetheless

Usage : This is similar to “despite this”.

Example : “The study had its limitations, but it was nonetheless groundbreaking for its day.”

29. Nevertheless

Usage : This is the same as “nonetheless”.

Example : “The study was flawed, but it was important nevertheless.”

30. Notwithstanding

Usage : This is another way of saying “nonetheless”.

Example : “Notwithstanding the limitations of the methodology used, it was an important study in the development of how we view the workings of the human mind.”

Giving examples

Good essays always back up points with examples, but it’s going to get boring if you use the expression “for example” every time. Here are a couple of other ways of saying the same thing.

31. For instance

Example : “Some birds migrate to avoid harsher winter climates. Swallows, for instance, leave the UK in early winter and fly south…”

32. To give an illustration

Example : “To give an illustration of what I mean, let’s look at the case of…”

Signifying importance

When you want to demonstrate that a point is particularly important, there are several ways of highlighting it as such.

33. Significantly

Usage : Used to introduce a point that is loaded with meaning that might not be immediately apparent.

Example : “Significantly, Tacitus omits to tell us the kind of gossip prevalent in Suetonius’ accounts of the same period.”

34. Notably

Usage : This can be used to mean “significantly” (as above), and it can also be used interchangeably with “in particular” (the example below demonstrates the first of these ways of using it).

Example : “Actual figures are notably absent from Scholar A’s analysis.”

35. Importantly

Usage : Use “importantly” interchangeably with “significantly”.

Example : “Importantly, Scholar A was being employed by X when he wrote this work, and was presumably therefore under pressure to portray the situation more favourably than he perhaps might otherwise have done.”

Summarising

You’ve almost made it to the end of the essay, but your work isn’t over yet. You need to end by wrapping up everything you’ve talked about, showing that you’ve considered the arguments on both sides and reached the most likely conclusion. Here are some words and phrases to help you.

36. In conclusion

Usage : Typically used to introduce the concluding paragraph or sentence of an essay, summarising what you’ve discussed in a broad overview.

Example : “In conclusion, the evidence points almost exclusively to Argument A.”

37. Above all

Usage : Used to signify what you believe to be the most significant point, and the main takeaway from the essay.

Example : “Above all, it seems pertinent to remember that…”

38. Persuasive

Usage : This is a useful word to use when summarising which argument you find most convincing.

Example : “Scholar A’s point – that Constanze Mozart was motivated by financial gain – seems to me to be the most persuasive argument for her actions following Mozart’s death.”

39. Compelling

Usage : Use in the same way as “persuasive” above.

Example : “The most compelling argument is presented by Scholar A.”

40. All things considered

Usage : This means “taking everything into account”.

Example : “All things considered, it seems reasonable to assume that…”

How many of these words and phrases will you get into your next essay? And are any of your favourite essay terms missing from our list? Let us know in the comments below!

Additional Information ( more examples)

+20 examples of important transition words, additional information.

There are many linking words which can lead us into additional information and while it is useful to vary your vocabulary beyond ‘ and ,’ these words are not mere replacements for ‘ and .’ They have nuanced differences, thus, by these particular meanings, we can offer a more delicate illustration of the relationships between our ideas.

• ‘Furthermore’ is used to add information that expands upon the previous point. It precedes information that expands upon that already given. It usually occurs at the beginning of an independent clause.
• ‘Moreover’ and ‘More so’ are both similar to ‘furthermore’ while giving special emphasis to the greater importance of the following clause.
• “Despite cutting back on other staff, her father gave her a position, furthermore , he gave her an enviable office while still not having a role for her.”
• Writers also sequence additional information. ‘Firstly,’ ‘secondly’ and ‘thirdly’ are obvious options used to achieve this, however, there are others. For example, we can look into the past with ‘previously,’ ‘until the present’ or ‘preceded by.’
• “Present growth in the company was *preceded by several quarters of stagnation”*
• ‘Meanwhile’ and ‘simultaneously’ talk about things which are happening at the same time as another, while ‘concurrently’ does this while emphasising that the two ideas have played out in conjunction with one another.
• Usually, ‘incidentally’ is used to add relevant information while downplaying its significance compared with that of other ideas.
• “The priority of the zoo had been to protect species’ from extinction. The panda breeding program was enjoying some rare success, while simultaneously , other programs to increase the numbers of endangered species were being trialled. Meanwhile , the zoo was being visited by an influx of tourists who were, incidentally , able to enjoy seeing the young animals.”
• ‘Subsequently’ and ‘afterward’ lead into information after the fact.

Compare and Contrast

When writers need to illustrate similarity they can employ words such as ‘in like manner,’ ‘comparatively,’ and ‘correspondingly.’ Whereas , when they wish to highlight difference they have phrases like ‘on the contrary,’ ‘however,’ ‘notwithstanding,’ ‘nevertheless’ and ‘on the other hand.’

Notwithstanding the vehement opposition to online education programs being made available to inmates, considerable improvements were made to the re-employment prospects of many offenders who benefited from the trial. On the contrary, prisoners who were not able to access education while incarcerated were found to be more likely to reoffend and return to prison.

Clarification

When it comes time to clarify an argument or point, some of the transitional phrases which are used are, ‘to reiterate,’ ‘specifically,’ or ‘inasmuch as.’

Consequence and Conclusion

When we have lead our reader through our flow of logic, there might be nothing more rewarding than driving our point home by showing consequence or concluding our arguments. There are a lot of strong phrases such as ‘accordingly,’ ‘hence,’ ‘thus’ and ‘thereupon’ which can do this.

I hope you will feel encouraged, by this article, to continue to further your understanding of how transitional words can work to guide your reader through your flow of logic. When used well, they add power and order to your argument and can add to the result you see from your work.

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CAMBRIDGE, MASSACHUSETTS - JUNE 29: People walk through the gate on Harvard Yard at the Harvard ... [+] University campus on June 29, 2023 in Cambridge, Massachusetts. The U.S. Supreme Court ruled that race-conscious admission policies used by Harvard and the University of North Carolina violate the Constitution, bringing an end to affirmative action in higher education. (Photo by Scott Eisen/Getty Images)

The college application season is upon us, and high school students everywhere are staring down at one of the most daunting tasks: the college essay. As someone who has guided countless applicants through the admissions process and reviewed admissions essays on an undergraduate admissions committee, I've pinpointed the essential ingredient to a differentiated candidacy—the core of your college admissions X-factor .

The essential ingredient to your college admissions X-factor is your intellectual vitality. Intellectual vitality is your passion for learning and curiosity. By demonstrating and conveying this passion, you can transform an average essay into a compelling narrative that boosts your chances of getting accepted to your top schools. Here are five dynamic strategies to achieve that goal.

Unleash Your Authentic Voice

Admissions officers sift through thousands of essays every year. What stops them in their tracks? An authentic voice that leaps off the page. Forget trying to guess what the admissions committee wants to hear. Focus on being true to yourself. Share your unique perspective, your passions, and your values. Authenticity resonates deeply with application reviewers, making your essay memorable and impactful. You need not have experienced trauma or tragedy to create a strong narrative. You can write about what you know—intellectually or personally—to convey your enthusiasm, creativity, and leadership. Intellectual vitality shines through when you write with personalized reflection about what lights you up.

Weave A Captivating Story

Everyone loves a good story, and your essay is the perfect place to tell yours. The Common Application personal statement has seven choices of prompts to ground the structure for your narrative. The most compelling stories are often about the smallest moments in life, whether it’s shopping at Costco or about why you wear socks that have holes. Think of the Common Application personal statement as a window into your soul rather than a dry list of your achievements or your overly broad event-based life story. Use vivid anecdotes to bring your experiences to life. A well-told story can showcase your growth, highlight your character, and illustrate how you've overcome challenges. Intellectual vitality often emerges in these narratives, revealing how your curiosity and proactive approach to learning have driven you to explore and innovate.

Reflect And Reveal Insights

It's not just about what you've done—it's about what you've learned along the way. When you are writing about a specific event, you can use the STAR framework—situation, task, action, and result (your learning). Focus most of your writing space on the “R” part of this framework to dive deeply into your experiences and reflect on how they've shaped your aspirations and identity.

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The most insightful college-specific supplement essays demonstrate depth of thought, and the ability to connect past experiences with your future life in college and beyond. Reflecting on your intellectual journey signals maturity and a readiness to embrace the college experience. It shows admissions officers that you engage deeply with your studies and are eager to contribute to the academic community.

Highlight Your Contributions—But Don’t Brag

Whether it's a special talent, an unusual hobby, or a unique perspective, showcasing what you can bring to the college environment can make a significant impact. Recognize that the hard work behind the accomplishment is what colleges are interested in learning more about—not retelling about the accomplishment itself. (Honors and activities can be conveyed in another section of the application.) Walk us through the journey to your summit; don’t just take us to the peak and expect us know how you earned it.

Intellectual vitality can be demonstrated through your proactive approach to solving problems, starting new projects, or leading initiatives that reflect your passion for learning and growth. These experiences often have a place in the college-specific supplement essays. They ground the reasons why you want to study in your major and at the particular college.

Perfect Your Prose

Great writing is essential. Anyone can use AI or a thesaurus to assist with an essay, but AI cannot write your story in the way that you tell it. Admissions officers don’t give out extra credit for choosing the longest words with the most amount of syllables.

The best essays have clear, coherent language and are free of errors. The story is clearly and specifically told. After drafting, take the time to revise and polish your writing. Seek feedback from teachers, mentors, or trusted friends, but ensure the final piece is unmistakably yours. A well-crafted essay showcases your diligence and attention to detail—qualities that admissions officers highly value. Intellectual vitality is also reflected in your writing process, showing your commitment to excellence and your enthusiasm for presenting your best self.

Crafting a standout college essay is about presenting your true self in an engaging, reflective, and polished manner while showcasing your intellectual vitality. Happy writing.

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Navigating Modes of Communication: Experiences of Being Bilingual

By Sue Yuan

Published: June 06, 2024

1st place McPartlin Award

“Stop trying to tell me what to do!” As I screamed into the phone, the room froze silent. I immediately felt regret the moment these words left my lips. The sounds coming from the gentle rustling of leaves outside my window only magnified the echoing silence from my mother. After what felt like an eternity, I could hear her sigh on the other end of the line, her voice quiet and resigned. “I just want what's best for you,” she responded softly in Mandarin Chinese, yet her words were barely audible over my racing heartbeat.

It all started as a casual Sunday afternoon check-in call with my mother, a part of our routine for two years since I left China to attend a boarding school in England. Over the weekend, my friends and I decided to dye our hair red (yes, Little Mermaid style) out of quarantine boredom. I was thrilled at how the impromptu decision turned out and wanted to tell my mother immediately, which obviously didn’t turn out exactly how I expected it to.

My mother’s extensive criticism included, but not limited to, how I looked “crazy”, was being too “inconsiderate”, alongside with concern that I would be perceived negatively or not taken seriously by teachers at school. In retrospect, all of her criticisms can be traced back to underlying cultural values associated with collectivism and conformity to social order, two key values embedded in traditional Chinese culture.

However, from a linguistics perspective, what’s more interesting is how I carried out the conversation. As a bilingual fluent in both Chinese and English, I oftentimes find myself code-switching between two languages when speaking to my mother who understands some English but can’t speak it. According to Laura M. Ahearn, a linguistic anthropologist and professor at Rutgers University, code-switching refers to the shifting from one language to another in a single speech event; moreover, such shift is oftentimes culturally meaningful and can “index particular social relationships, meaning or hierarchies” (Ahearn 147). To linguistic anthropologists, code-switching or code-mixing can be a reflection of the speakers’ moral alignments and changing social identities, as the contrast between one code and the other is oftentimes purposeful, whether it is a conscious decision or not.

In this sense, a seemingly pointless argument with my mother becomes complex and can be critically analyzed as I navigate alignment and dissociation between two distinct speech communities of Chinese and English, both representing different sociocultural values, beliefs, and behaviors. During the call, I find myself often articulating my individual self-descriptions (concepts such as trying to “be myself” or “look cool”) in English, which are ideologically Western individualistic values, while voicing agreement and compliance with my mother in Chinese. Nevertheless, could this shift be universally experienced by all bilingual or multilingual speakers? Do we feel, think, or behave differently when speaking different languages? And most importantly, what prompts these differences?

There has been substantial research in recent years demonstrating bilingualism’s effects on influencing speakers’ perceptions of the self and the world. Hull’s pioneering research into bilingualism and personality asked three groups of first-generation immigrants from Mexico (Spanish), Korea (Korean) and China (Mandarin Chinese) to complete the California Psychological Inventory, a self-assessment instrument used to measure personality aspects, in their native language and English respectively. After conducting in-group between-language analysis, he found significant differences in the responses between the participants’ native language and English. For instance, Spanish speakers scored much higher on “individualistic Anglo cultural values” such as self-acceptance and interpersonal prestige when surveyed in English. On the contrary, when surveyed in Spanish, the same participants scored higher on values like interpersonal harmony and positive impression, which are features of a collectivist, Spanish-speaking culture that emphasize group dynamics (Hull 132).

Moreover, Ukrainian-American professor and linguist, Dr. Pavlenko conducted a study involving over 1000 multilingual participants that reaffirmed Hull’s findings. Participants were asked to complete a web questionnaire with open-ended questions such as “do you feel like a different person when using different languages?”, which gained an overwhelming 65% affirmative response overall (Pavlenko 26). With thematic analysis, Pavlenko determined several sources that contributed to multilinguals’ feeling of self-fragmentation, one of them being language socialization (the learning contexts in which the language was acquired). Growing up, English has primarily been a classroom language for me since I acquired most of my English abilities in an educational setting, while I mainly conversed in Chinese with family and friends. The corollary of my experience is that English became institutionalized as a language of evaluation, in which my command of English was always accompanied by an implicit expectation of judgment on my academic abilities, whether it is grammatical correctness, vocabulary repertoire, or accurateness in pronunciation.

In turn, this has manifested in my higher level of formality when it comes to speaking English and a sense of constant self-awareness that propels me to fixate on how I speak instead of what I speak. On top of that, the formal socialization of English has also translated into a ‘performative’ feeling that I experience when speaking English, where I feel less ‘real’ or ‘natural’ compared to speaking Mandarin due to an ingrained sense of judgment that comes with English-speaking settings that I was socialized in. Pavlenko describes this as a difference in “experienced language emotionality”, suggesting that this is another major contributing factor to the changes in self-perception of multilingual speakers.

Similarly, the command of multiple languages might also translate into changes in conversational expectations that could lead to greater emotionality and intimacy when perceiving and reacting to events. Panayiotou’s study compared Greek and English’s narrative emotivity on Greek-English bilinguals by reading them the same story in two different languages. He discovered that participants interpreted and reacted to the same narration differently depending on the linguistic context, where the Greek story was reported to elicit more sympathy and concern for the protagonist than when the story was read to them in English (Panayiotou 134).

Such phenomenon could be explained by the theory of Cultural Frame Switching , which states that bicultural individuals tend to experience a shift in “values and attributions in the presence of culture-relevant stimuli”, in this case being the language spoken (Ramírez-Esparza, Nairán, et al. 100). The fluent command of a language often requires the speaker to be fully aware of and observe the set of cultural values and expectations in order to become a competent, functional member of its speech community. Therefore, when the bilingual individual code-switches from one language to another, a switch in cultural scripts occurs subconsciously where the individual accommodates to the present situation based on the behavioral expectations of the given culture in which the language was acquired. This is because language itself can act as an instrument to trigger certain cultural memories regarding the appropriate values, attitudes and norms to adopt or conform to when speaking.

As a result of Cultural Frame Switching , I always find myself to be bolder, more expressive, and more individualized when speaking English. For example, I’m able express values and opinions on topics such as social activism, individual rights, and equality more coherently. These values were acquired in an English-speaking setting through classroom discussions, talking with friends, or even on Western social media platforms. Therefore, as I code-switch from Chinese to English, I (consciously or subconsciously) shift my moral alignment from a highly collective cultural framework that prioritize respect for social order, hierarchies, and polite language use to a more casual, individualistic cultural script where idiosyncratic expression of thoughts is not only accepted but preferred.

Furthermore, bilingual speakers can develop the skills for Cultural Frame Switching from a very young age. A study by Chen and colleagues compared the difference in narrative styles between a group of children who speak both Chinese and English, and a group of monolingual English-speaking children. They discovered that although both groups displayed similar age-related growth in the development and use of evaluative expressions, Chinese-English bilingual children produced more evaluative clauses and adopted more of a local perspective on the story character’s frame of mind compared to English-speaking peers (Chen & Yan 570). The authors argued that such differences could be explained from a cultural perspective, where Chinese speakers “tend to focus on relations between a person or an object and the environment as the antecedent of a behavior.” On the contrary, Americans are more prone to “decontextualize” components of an event from its environment and attend to “internal attributes” of an individual in isolation. In other words, the peculiarity of Chinese culture fosters an increased awareness of social situations and contextual environment amongst Chinese speaking individuals, which in turn reinforces the collectivist, socio-centric features of Chinese society. Thus, bilingualism is oftentimes intertwined with biculturalism, where the bilingual individual is endowed with the mastery of two internalized cultural frameworks that command their perspectives and behaviors of themselves and the world.

Nonetheless, although there are shared experiences of being multilingual, such as the ability to adopt different cultural outlooks, we must acknowledge that there is no “universal” language experience. This means that bilingual/multilingual experiences are particularly individualized depending on the different socialization processes and cultural upbringing of the speaker. To illustrate, an English-Chinese bilingual raised in an English-speaking country might experience a different set of cultural shifts compared to a local Chinese-speaking individual who acquired English later in life.

Bilingualism’s effects on an individual expands far beyond a sociocultural aspect, as psychological research has suggested a link between bilingualism and one’s cognitive competency. An archaic view on bilingualism suggests that children exposed to a bilingual environment at an early age might suffer from cognitive deficiency due to linguistic confusions, leading to academic difficulties and diminishing school performances. However, professor and scholar Ellen Bialystok at the University of York argues otherwise. Her study on bilingualism’s effects on the brain from a neuroscience perspective shows that sufficient bilingual exposure could protect individuals against age-related cognitive decline, such as the development of dementia due to bilingualism’s ability to enhance one’s cognitive control and mental flexibility (Bialystok 242).

I vividly remember the constant scolding I received as a kid by teachers at my English-instructed international school for speaking Chinese with other Chinese peers. “English only!” was a phrase of nightmare for my middle-school self, a phrase that made me feel guilty and ashamed for speaking my native tongue. To a lot of instructors, code-switching between Chinese and English indicated a poor or incomplete acquisition of both languages. This is a common misconception among educators that ignores the multifunctionality of language in which code-mixing is deliberate, an index for cultural identification and moral alignment that formulates one’s sense of self.

The consequence of normalizing monolingualism manifests itself in the clear hierarchy of language, ranking standard American English on top as the dominant “global language” which leads to a pervading “English-only” ideology in the US, where immigrant parents will sacrifice anything (including speaking their mother tongue at home) to teach their children standard English in order to assimilate. This is because the proficient, native-level command of English with impeccable grammar and pronunciation is naturally equated to high socioeconomic status of the speaker, while someone who speaks English with a non-western accent is often subconsciously assumed to be less educated. Moreover, this English-centric view of language directly influences how people perceive non-Anglo cultures that have a completely different perception of appropriate language use by associating their cultures with a lesser degree of education, morals, or logic.

With more than half of the world’s population being bilingual or multilingual, it is crucial to recognize the unique beauty of being able to speak more than one language, as it comes with not only the ability to experience different cultures, but to also serve as a bridge between one and another. As my memories wander back from the rustling noise of leaves outside my boarding room’s window, I can’t quite recall how the phone call ended with my mother. However, I no longer feel the distraught from disagreeing with her, wishing that she could understand from my point of view. My bilingualism has become an integral part of my identity, as it enables me to see the world through an alternative cultural lens, neither of which is necessarily right nor wrong. As I navigate through the worlds of Chinese and English, I realized that it is possible for me to exist in both, where I’m learning to derive enjoyment instead of anguish from such hybridity.

Works Cited

Ahearn, Laura M. Living Language : An Introduction to Linguistic Anthropology . Wiley-Blackwell 2012.

Bialystok, Ellen et al. “Bilingualism: consequences for mind and brain.” Trends in cognitive sciences vol. 16,4 (2012): 240-50. doi:10.1016/j.tics.2012.03.001

Chen, Liang, and Yan, Ruixia. “Development and Use of English Evaluative Expressions in Narratives of Chinese–English Bilinguals.” Bilingualism: Language and Cognition, vol. 14, no. 4, 2011, pp. 570–578., doi:10.1017/S1366728910000362 .

Hull, Philip Veryan. Bilingualism : Two Languages, Two Personalities? University of California, Berkeley, 1990, https://books.google.com/books?id=M2BLAQAAMAAJ .

Panayiotou, Alexia. (2010). Switching Codes, Switching Code: Bilinguals' Emotional Responses in English and Greek. Journal of Multilingual and Multicultural Development. June 1. 124-139. 10.1080/01434630408666525 .

Pavlenko, Aneta. "1. Bilingual Selves". Bilingual Minds: Emotional Experience, Expression, and Representation , edited by Aneta Pavlenko, Bristol, Blue Ridge Summit: Multilingual Matters, 2006, pp. 1-33. https://doi.org/10.21832/9781853598746-003

Ramírez-Esparza, Nairán, et al. “Do Bilinguals Have Two Personalities? A Special Case of Cultural Frame Switching.” Journal of Research in Personality, vol. 40, no. 2, Apr. 2006, pp. 99–120. DOI.org (Crossref), https://doi.org/10.1016/j.jrp.2004.09.001 .

Sue Yuan, Class of 2026, is an Anthropology major at the University of Notre Dame. Her essay, “Navigating Modes of Communication: Experiences of Being Bilingual”, explores her own personal experiences of being bilingual in Mandarin Chinese and English in an English-dominant world. Growing up as a bil-cultural kid and facing many identity challenges, Sue has learned to embrace her bilingualism as a normal, natural, and beautiful phenomenon that results from her multiculturalism. Sue would like to thank Professor Want for her support and encouragement during the writing process. Most importantly, Sue would like to thank her mother for everything she has done for Sue and her family.

Getting Write Down to It: Passion and Purpose in Writing

A personal perspective: writing as an art form..

Posted June 2, 2024 | Reviewed by Lybi Ma

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If we think about writing as having the privilege of entering a conversation and pushing it in the direction we think it needs to go, then writing—yes, even academic writing—becomes creative. It becomes our own art form, if you will. It gives meaning to our lives and is one of the ways that we contribute to the world.

Once we recognize that our writing is an art form, we need new ways to judge ourselves and our productivity . Should a painter’s worthiness as an artist be determined by how many pieces they landed in a juried show in the last year? When we think of an artist’s career , we see the arc of their art over time. Similarly, as academics, we write over the arc of our careers. It’s the way that we—as people involved in the front lines of knowledge production, construction, and consumption—make art.

Publishing monographs and articles in top-tier journals is a fine goal—in fact, even necessary sometimes to get or keep a job. But publishing isn’t the only reason for writing any more than juried exhibitions and winning awards are the sole reasons an artist goes to paint. The painter finds at least as much, if not much more, nourishment and fulfillment in the process of making art as in the external recognition, however validating and joyful those accolades. Indeed, dreaming of accolades is rarely why an artist sits down to paint. The painter makes art to thrive, to share the meaning they find in the world with others. So, too, if a writer recognizes their work as their art, they sit down to do it to share their gifts with other people and society in general. And the process of writing itself becomes a way to thrive, to contribute to the world.

To take our writing seriously, we must think about it as a core part of our life’s work. We often write for our peers, sometimes for our students, and sometimes for audiences outside of academia. Once we have confidence in our writing, that paves the way for more outward-facing scholarship, bolstering the possibility of becoming a public scholar.

Once we take seriously our art form—or craft, if the word sounds more apt or comfortable—we must make time for it. When we finish a research project, we must realize that good writing takes care, thought, and loving attention to words, phrasing, and paragraph construction. Knowing that it takes time, and is worth the time, can boost our confidence. Good writing brings our ideas, and our findings, to life.

With all of the competing demands that students, colleagues, and our increasingly bureaucratic administrations in higher education impose on us, writing can be something we can claim as our own. While our course material is housed in learning management systems with accompanying questions of control over our intellectual property, and committee work is in service to the institution, the writing we do is ours. And the time we claim for it—for cultivating and honing it—is time we’ve declared, if only to ourselves, as precious and sacred, reserved to nurture ourselves and our ability to contribute to those around us. There’s something very liberating about that.

In sum, while many faculty members see the “publish or perish” message as exemplifying the competitive pressure of an academic career, making the time to enjoy the process of writing is an antidote to some of what has become the drudgery of university life. It reminds us what turns us on in our fields of study and motivates our inquiry in the first place.

A version of this post also appeared in Inside Higher Ed with Barbara Risman.

Deborah J. Cohan, Ph.D., is a professor of sociology at the University of South Carolina-Beaufort where she teaches and writes about the intersections of the self and society.

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Home — Essay Samples — Education — Scholarship — The Impact of Scholarships on Academic and Professional Development

The Impact of Scholarships on Academic and Professional Development

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Introduction, scholarships as catalysts for academic excellence, fostering personal and professional development, promoting social mobility and equity.

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• Published: 03 June 2024

Applying large language models for automated essay scoring for non-native Japanese

• Wenchao Li 1 &
• Haitao Liu 2  

Humanities and Social Sciences Communications volume  11 , Article number:  723 ( 2024 ) Cite this article

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• Language and linguistics

Recent advancements in artificial intelligence (AI) have led to an increased use of large language models (LLMs) for language assessment tasks such as automated essay scoring (AES), automated listening tests, and automated oral proficiency assessments. The application of LLMs for AES in the context of non-native Japanese, however, remains limited. This study explores the potential of LLM-based AES by comparing the efficiency of different models, i.e. two conventional machine training technology-based methods (Jess and JWriter), two LLMs (GPT and BERT), and one Japanese local LLM (Open-Calm large model). To conduct the evaluation, a dataset consisting of 1400 story-writing scripts authored by learners with 12 different first languages was used. Statistical analysis revealed that GPT-4 outperforms Jess and JWriter, BERT, and the Japanese language-specific trained Open-Calm large model in terms of annotation accuracy and predicting learning levels. Furthermore, by comparing 18 different models that utilize various prompts, the study emphasized the significance of prompts in achieving accurate and reliable evaluations using LLMs.

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Conventional machine learning technology in aes.

AES has experienced significant growth with the advancement of machine learning technologies in recent decades. In the earlier stages of AES development, conventional machine learning-based approaches were commonly used. These approaches involved the following procedures: a) feeding the machine with a dataset. In this step, a dataset of essays is provided to the machine learning system. The dataset serves as the basis for training the model and establishing patterns and correlations between linguistic features and human ratings. b) the machine learning model is trained using linguistic features that best represent human ratings and can effectively discriminate learners’ writing proficiency. These features include lexical richness (Lu, 2012 ; Kyle and Crossley, 2015 ; Kyle et al. 2021 ), syntactic complexity (Lu, 2010 ; Liu, 2008 ), text cohesion (Crossley and McNamara, 2016 ), and among others. Conventional machine learning approaches in AES require human intervention, such as manual correction and annotation of essays. This human involvement was necessary to create a labeled dataset for training the model. Several AES systems have been developed using conventional machine learning technologies. These include the Intelligent Essay Assessor (Landauer et al. 2003 ), the e-rater engine by Educational Testing Service (Attali and Burstein, 2006 ; Burstein, 2003 ), MyAccess with the InterlliMetric scoring engine by Vantage Learning (Elliot, 2003 ), and the Bayesian Essay Test Scoring system (Rudner and Liang, 2002 ). These systems have played a significant role in automating the essay scoring process and providing quick and consistent feedback to learners. However, as touched upon earlier, conventional machine learning approaches rely on predetermined linguistic features and often require manual intervention, making them less flexible and potentially limiting their generalizability to different contexts.

In the context of the Japanese language, conventional machine learning-incorporated AES tools include Jess (Ishioka and Kameda, 2006 ) and JWriter (Lee and Hasebe, 2017 ). Jess assesses essays by deducting points from the perfect score, utilizing the Mainichi Daily News newspaper as a database. The evaluation criteria employed by Jess encompass various aspects, such as rhetorical elements (e.g., reading comprehension, vocabulary diversity, percentage of complex words, and percentage of passive sentences), organizational structures (e.g., forward and reverse connection structures), and content analysis (e.g., latent semantic indexing). JWriter employs linear regression analysis to assign weights to various measurement indices, such as average sentence length and total number of characters. These weights are then combined to derive the overall score. A pilot study involving the Jess model was conducted on 1320 essays at different proficiency levels, including primary, intermediate, and advanced. However, the results indicated that the Jess model failed to significantly distinguish between these essay levels. Out of the 16 measures used, four measures, namely median sentence length, median clause length, median number of phrases, and maximum number of phrases, did not show statistically significant differences between the levels. Additionally, two measures exhibited between-level differences but lacked linear progression: the number of attributives declined words and the Kanji/kana ratio. On the other hand, the remaining measures, including maximum sentence length, maximum clause length, number of attributive conjugated words, maximum number of consecutive infinitive forms, maximum number of conjunctive-particle clauses, k characteristic value, percentage of big words, and percentage of passive sentences, demonstrated statistically significant between-level differences and displayed linear progression.

Both Jess and JWriter exhibit notable limitations, including the manual selection of feature parameters and weights, which can introduce biases into the scoring process. The reliance on human annotators to label non-native language essays also introduces potential noise and variability in the scoring. Furthermore, an important concern is the possibility of system manipulation and cheating by learners who are aware of the regression equation utilized by the models (Hirao et al. 2020 ). These limitations emphasize the need for further advancements in AES systems to address these challenges.

Deep learning technology in AES

Deep learning has emerged as one of the approaches for improving the accuracy and effectiveness of AES. Deep learning-based AES methods utilize artificial neural networks that mimic the human brain’s functioning through layered algorithms and computational units. Unlike conventional machine learning, deep learning autonomously learns from the environment and past errors without human intervention. This enables deep learning models to establish nonlinear correlations, resulting in higher accuracy. Recent advancements in deep learning have led to the development of transformers, which are particularly effective in learning text representations. Noteworthy examples include bidirectional encoder representations from transformers (BERT) (Devlin et al. 2019 ) and the generative pretrained transformer (GPT) (OpenAI).

BERT is a linguistic representation model that utilizes a transformer architecture and is trained on two tasks: masked linguistic modeling and next-sentence prediction (Hirao et al. 2020 ; Vaswani et al. 2017 ). In the context of AES, BERT follows specific procedures, as illustrated in Fig. 1 : (a) the tokenized prompts and essays are taken as input; (b) special tokens, such as [CLS] and [SEP], are added to mark the beginning and separation of prompts and essays; (c) the transformer encoder processes the prompt and essay sequences, resulting in hidden layer sequences; (d) the hidden layers corresponding to the [CLS] tokens (T[CLS]) represent distributed representations of the prompts and essays; and (e) a multilayer perceptron uses these distributed representations as input to obtain the final score (Hirao et al. 2020 ).

AES system with BERT (Hirao et al. 2020 ).

The training of BERT using a substantial amount of sentence data through the Masked Language Model (MLM) allows it to capture contextual information within the hidden layers. Consequently, BERT is expected to be capable of identifying artificial essays as invalid and assigning them lower scores (Mizumoto and Eguchi, 2023 ). In the context of AES for nonnative Japanese learners, Hirao et al. ( 2020 ) combined the long short-term memory (LSTM) model proposed by Hochreiter and Schmidhuber ( 1997 ) with BERT to develop a tailored automated Essay Scoring System. The findings of their study revealed that the BERT model outperformed both the conventional machine learning approach utilizing character-type features such as “kanji” and “hiragana”, as well as the standalone LSTM model. Takeuchi et al. ( 2021 ) presented an approach to Japanese AES that eliminates the requirement for pre-scored essays by relying solely on reference texts or a model answer for the essay task. They investigated multiple similarity evaluation methods, including frequency of morphemes, idf values calculated on Wikipedia, LSI, LDA, word-embedding vectors, and document vectors produced by BERT. The experimental findings revealed that the method utilizing the frequency of morphemes with idf values exhibited the strongest correlation with human-annotated scores across different essay tasks. The utilization of BERT in AES encounters several limitations. Firstly, essays often exceed the model’s maximum length limit. Second, only score labels are available for training, which restricts access to additional information.

Mizumoto and Eguchi ( 2023 ) were pioneers in employing the GPT model for AES in non-native English writing. Their study focused on evaluating the accuracy and reliability of AES using the GPT-3 text-davinci-003 model, analyzing a dataset of 12,100 essays from the corpus of nonnative written English (TOEFL11). The findings indicated that AES utilizing the GPT-3 model exhibited a certain degree of accuracy and reliability. They suggest that GPT-3-based AES systems hold the potential to provide support for human ratings. However, applying GPT model to AES presents a unique natural language processing (NLP) task that involves considerations such as nonnative language proficiency, the influence of the learner’s first language on the output in the target language, and identifying linguistic features that best indicate writing quality in a specific language. These linguistic features may differ morphologically or syntactically from those present in the learners’ first language, as observed in (1)–(3).

我-送了-他-一本-书

Wǒ-sòngle-tā-yī běn-shū

1 sg .-give. past- him-one .cl- book

“I gave him a book.”

Agglutinative

彼-に-本-を-あげ-まし-た

Kare-ni-hon-o-age-mashi-ta

3 sg .- dat -hon- acc- give.honorification. past

Inflectional

give, give-s, gave, given, giving

Additionally, the morphological agglutination and subject-object-verb (SOV) order in Japanese, along with its idiomatic expressions, pose additional challenges for applying language models in AES tasks (4).

足-が 棒-に なり-ました

Ashi-ga bo-ni nar-mashita

leg- nom stick- dat become- past

“My leg became like a stick (I am extremely tired).”

The example sentence provided demonstrates the morpho-syntactic structure of Japanese and the presence of an idiomatic expression. In this sentence, the verb “なる” (naru), meaning “to become”, appears at the end of the sentence. The verb stem “なり” (nari) is attached with morphemes indicating honorification (“ます” - mashu) and tense (“た” - ta), showcasing agglutination. While the sentence can be literally translated as “my leg became like a stick”, it carries an idiomatic interpretation that implies “I am extremely tired”.

To overcome this issue, CyberAgent Inc. ( 2023 ) has developed the Open-Calm series of language models specifically designed for Japanese. Open-Calm consists of pre-trained models available in various sizes, such as Small, Medium, Large, and 7b. Figure 2 depicts the fundamental structure of the Open-Calm model. A key feature of this architecture is the incorporation of the Lora Adapter and GPT-NeoX frameworks, which can enhance its language processing capabilities.

GPT-NeoX Model Architecture (Okgetheng and Takeuchi 2024 ).

In a recent study conducted by Okgetheng and Takeuchi ( 2024 ), they assessed the efficacy of Open-Calm language models in grading Japanese essays. The research utilized a dataset of approximately 300 essays, which were annotated by native Japanese educators. The findings of the study demonstrate the considerable potential of Open-Calm language models in automated Japanese essay scoring. Specifically, among the Open-Calm family, the Open-Calm Large model (referred to as OCLL) exhibited the highest performance. However, it is important to note that, as of the current date, the Open-Calm Large model does not offer public access to its server. Consequently, users are required to independently deploy and operate the environment for OCLL. In order to utilize OCLL, users must have a PC equipped with an NVIDIA GeForce RTX 3060 (8 or 12 GB VRAM).

In summary, while the potential of LLMs in automated scoring of nonnative Japanese essays has been demonstrated in two studies—BERT-driven AES (Hirao et al. 2020 ) and OCLL-based AES (Okgetheng and Takeuchi, 2024 )—the number of research efforts in this area remains limited.

Another significant challenge in applying LLMs to AES lies in prompt engineering and ensuring its reliability and effectiveness (Brown et al. 2020 ; Rae et al. 2021 ; Zhang et al. 2021 ). Various prompting strategies have been proposed, such as the zero-shot chain of thought (CoT) approach (Kojima et al. 2022 ), which involves manually crafting diverse and effective examples. However, manual efforts can lead to mistakes. To address this, Zhang et al. ( 2021 ) introduced an automatic CoT prompting method called Auto-CoT, which demonstrates matching or superior performance compared to the CoT paradigm. Another prompt framework is trees of thoughts, enabling a model to self-evaluate its progress at intermediate stages of problem-solving through deliberate reasoning (Yao et al. 2023 ).

Beyond linguistic studies, there has been a noticeable increase in the number of foreign workers in Japan and Japanese learners worldwide (Ministry of Health, Labor, and Welfare of Japan, 2022 ; Japan Foundation, 2021 ). However, existing assessment methods, such as the Japanese Language Proficiency Test (JLPT), J-CAT, and TTBJ Footnote 1 , primarily focus on reading, listening, vocabulary, and grammar skills, neglecting the evaluation of writing proficiency. As the number of workers and language learners continues to grow, there is a rising demand for an efficient AES system that can reduce costs and time for raters and be utilized for employment, examinations, and self-study purposes.

This study aims to explore the potential of LLM-based AES by comparing the effectiveness of five models: two LLMs (GPT Footnote 2 and BERT), one Japanese local LLM (OCLL), and two conventional machine learning-based methods (linguistic feature-based scoring tools - Jess and JWriter).

The research questions addressed in this study are as follows:

To what extent do the LLM-driven AES and linguistic feature-based AES, when used as automated tools to support human rating, accurately reflect test takers’ actual performance?

What influence does the prompt have on the accuracy and performance of LLM-based AES methods?

The subsequent sections of the manuscript cover the methodology, including the assessment measures for nonnative Japanese writing proficiency, criteria for prompts, and the dataset. The evaluation section focuses on the analysis of annotations and rating scores generated by LLM-driven and linguistic feature-based AES methods.

Methodology

The dataset utilized in this study was obtained from the International Corpus of Japanese as a Second Language (I-JAS) Footnote 3 . This corpus consisted of 1000 participants who represented 12 different first languages. For the study, the participants were given a story-writing task on a personal computer. They were required to write two stories based on the 4-panel illustrations titled “Picnic” and “The key” (see Appendix A). Background information for the participants was provided by the corpus, including their Japanese language proficiency levels assessed through two online tests: J-CAT and SPOT. These tests evaluated their reading, listening, vocabulary, and grammar abilities. The learners’ proficiency levels were categorized into six levels aligned with the Common European Framework of Reference for Languages (CEFR) and the Reference Framework for Japanese Language Education (RFJLE): A1, A2, B1, B2, C1, and C2. According to Lee et al. ( 2015 ), there is a high level of agreement (r = 0.86) between the J-CAT and SPOT assessments, indicating that the proficiency certifications provided by J-CAT are consistent with those of SPOT. However, it is important to note that the scores of J-CAT and SPOT do not have a one-to-one correspondence. In this study, the J-CAT scores were used as a benchmark to differentiate learners of different proficiency levels. A total of 1400 essays were utilized, representing the beginner (aligned with A1), A2, B1, B2, C1, and C2 levels based on the J-CAT scores. Table 1 provides information about the learners’ proficiency levels and their corresponding J-CAT and SPOT scores.

A dataset comprising a total of 1400 essays from the story writing tasks was collected. Among these, 714 essays were utilized to evaluate the reliability of the LLM-based AES method, while the remaining 686 essays were designated as development data to assess the LLM-based AES’s capability to distinguish participants with varying proficiency levels. The GPT 4 API was used in this study. A detailed explanation of the prompt-assessment criteria is provided in Section Prompt . All essays were sent to the model for measurement and scoring.

Measures of writing proficiency for nonnative Japanese

Japanese exhibits a morphologically agglutinative structure where morphemes are attached to the word stem to convey grammatical functions such as tense, aspect, voice, and honorifics, e.g. (5).

食べ-させ-られ-まし-た-か

tabe-sase-rare-mashi-ta-ka

[eat (stem)-causative-passive voice-honorification-tense. past-question marker]

Japanese employs nine case particles to indicate grammatical functions: the nominative case particle が (ga), the accusative case particle を (o), the genitive case particle の (no), the dative case particle に (ni), the locative/instrumental case particle で (de), the ablative case particle から (kara), the directional case particle へ (e), and the comitative case particle と (to). The agglutinative nature of the language, combined with the case particle system, provides an efficient means of distinguishing between active and passive voice, either through morphemes or case particles, e.g. 食べる taberu “eat concusive . ” (active voice); 食べられる taberareru “eat concusive . ” (passive voice). In the active voice, “パン を 食べる” (pan o taberu) translates to “to eat bread”. On the other hand, in the passive voice, it becomes “パン が 食べられた” (pan ga taberareta), which means “(the) bread was eaten”. Additionally, it is important to note that different conjugations of the same lemma are considered as one type in order to ensure a comprehensive assessment of the language features. For example, e.g., 食べる taberu “eat concusive . ”; 食べている tabeteiru “eat progress .”; 食べた tabeta “eat past . ” as one type.

To incorporate these features, previous research (Suzuki, 1999 ; Watanabe et al. 1988 ; Ishioka, 2001 ; Ishioka and Kameda, 2006 ; Hirao et al. 2020 ) has identified complexity, fluency, and accuracy as crucial factors for evaluating writing quality. These criteria are assessed through various aspects, including lexical richness (lexical density, diversity, and sophistication), syntactic complexity, and cohesion (Kyle et al. 2021 ; Mizumoto and Eguchi, 2023 ; Ure, 1971 ; Halliday, 1985 ; Barkaoui and Hadidi, 2020 ; Zenker and Kyle, 2021 ; Kim et al. 2018 ; Lu, 2017 ; Ortega, 2015 ). Therefore, this study proposes five scoring categories: lexical richness, syntactic complexity, cohesion, content elaboration, and grammatical accuracy. A total of 16 measures were employed to capture these categories. The calculation process and specific details of these measures can be found in Table 2 .

T-unit, first introduced by Hunt ( 1966 ), is a measure used for evaluating speech and composition. It serves as an indicator of syntactic development and represents the shortest units into which a piece of discourse can be divided without leaving any sentence fragments. In the context of Japanese language assessment, Sakoda and Hosoi ( 2020 ) utilized T-unit as the basic unit to assess the accuracy and complexity of Japanese learners’ speaking and storytelling. The calculation of T-units in Japanese follows the following principles:

A single main clause constitutes 1 T-unit, regardless of the presence or absence of dependent clauses, e.g. (6).

ケンとマリはピクニックに行きました (main clause): 1 T-unit.

If a sentence contains a main clause along with subclauses, each subclause is considered part of the same T-unit, e.g. (7).

天気が良かった の で (subclause)、ケンとマリはピクニックに行きました (main clause): 1 T-unit.

In the case of coordinate clauses, where multiple clauses are connected, each coordinated clause is counted separately. Thus, a sentence with coordinate clauses may have 2 T-units or more, e.g. (8).

ケンは地図で場所を探して (coordinate clause)、マリはサンドイッチを作りました (coordinate clause): 2 T-units.

Lexical diversity refers to the range of words used within a text (Engber, 1995 ; Kyle et al. 2021 ) and is considered a useful measure of the breadth of vocabulary in L n production (Jarvis, 2013a , 2013b ).

The type/token ratio (TTR) is widely recognized as a straightforward measure for calculating lexical diversity and has been employed in numerous studies. These studies have demonstrated a strong correlation between TTR and other methods of measuring lexical diversity (e.g., Bentz et al. 2016 ; Čech and Miroslav, 2018 ; Çöltekin and Taraka, 2018 ). TTR is computed by considering both the number of unique words (types) and the total number of words (tokens) in a given text. Given that the length of learners’ writing texts can vary, this study employs the moving average type-token ratio (MATTR) to mitigate the influence of text length. MATTR is calculated using a 50-word moving window. Initially, a TTR is determined for words 1–50 in an essay, followed by words 2–51, 3–52, and so on until the end of the essay is reached (Díez-Ortega and Kyle, 2023 ). The final MATTR scores were obtained by averaging the TTR scores for all 50-word windows. The following formula was employed to derive MATTR:

\({\rm{MATTR}}({\rm{W}})=\frac{{\sum }_{{\rm{i}}=1}^{{\rm{N}}-{\rm{W}}+1}{{\rm{F}}}_{{\rm{i}}}}{{\rm{W}}({\rm{N}}-{\rm{W}}+1)}\)

Here, N refers to the number of tokens in the corpus. W is the randomly selected token size (W < N). \({F}_{i}\) is the number of types in each window. The \({\rm{MATTR}}({\rm{W}})\) is the mean of a series of type-token ratios (TTRs) based on the word form for all windows. It is expected that individuals with higher language proficiency will produce texts with greater lexical diversity, as indicated by higher MATTR scores.

Lexical density was captured by the ratio of the number of lexical words to the total number of words (Lu, 2012 ). Lexical sophistication refers to the utilization of advanced vocabulary, often evaluated through word frequency indices (Crossley et al. 2013 ; Haberman, 2008 ; Kyle and Crossley, 2015 ; Laufer and Nation, 1995 ; Lu, 2012 ; Read, 2000 ). In line of writing, lexical sophistication can be interpreted as vocabulary breadth, which entails the appropriate usage of vocabulary items across various lexicon-grammatical contexts and registers (Garner et al. 2019 ; Kim et al. 2018 ; Kyle et al. 2018 ). In Japanese specifically, words are considered lexically sophisticated if they are not included in the “Japanese Education Vocabulary List Ver 1.0”. Footnote 4 Consequently, lexical sophistication was calculated by determining the number of sophisticated word types relative to the total number of words per essay. Furthermore, it has been suggested that, in Japanese writing, sentences should ideally have a length of no more than 40 to 50 characters, as this promotes readability. Therefore, the median and maximum sentence length can be considered as useful indices for assessment (Ishioka and Kameda, 2006 ).

Syntactic complexity was assessed based on several measures, including the mean length of clauses, verb phrases per T-unit, clauses per T-unit, dependent clauses per T-unit, complex nominals per clause, adverbial clauses per clause, coordinate phrases per clause, and mean dependency distance (MDD). The MDD reflects the distance between the governor and dependent positions in a sentence. A larger dependency distance indicates a higher cognitive load and greater complexity in syntactic processing (Liu, 2008 ; Liu et al. 2017 ). The MDD has been established as an efficient metric for measuring syntactic complexity (Jiang, Quyang, and Liu, 2019 ; Li and Yan, 2021 ). To calculate the MDD, the position numbers of the governor and dependent are subtracted, assuming that words in a sentence are assigned in a linear order, such as W1 … Wi … Wn. In any dependency relationship between words Wa and Wb, Wa is the governor and Wb is the dependent. The MDD of the entire sentence was obtained by taking the absolute value of governor – dependent:

MDD = \(\frac{1}{n}{\sum }_{i=1}^{n}|{\rm{D}}{{\rm{D}}}_{i}|\)

In this formula, \(n\) represents the number of words in the sentence, and \({DD}i\) is the dependency distance of the \({i}^{{th}}\) dependency relationship of a sentence. Building on this, the annotation of sentence ‘Mary-ga-John-ni-keshigomu-o-watashita was [Mary- top -John- dat -eraser- acc -give- past] ’. The sentence’s MDD would be 2. Table 3 provides the CSV file as a prompt for GPT 4.

Cohesion (semantic similarity) and content elaboration aim to capture the ideas presented in test taker’s essays. Cohesion was assessed using three measures: Synonym overlap/paragraph (topic), Synonym overlap/paragraph (keywords), and word2vec cosine similarity. Content elaboration and development were measured as the number of metadiscourse markers (type)/number of words. To capture content closely, this study proposed a novel-distance based representation, by encoding the cosine distance between the essay (by learner) and essay task’s (topic and keyword) i -vectors. The learner’s essay is decoded into a word sequence, and aligned to the essay task’ topic and keyword for log-likelihood measurement. The cosine distance reveals the content elaboration score in the leaners’ essay. The mathematical equation of cosine similarity between target-reference vectors is shown in (11), assuming there are i essays and ( L i , …. L n ) and ( N i , …. N n ) are the vectors representing the learner and task’s topic and keyword respectively. The content elaboration distance between L i and N i was calculated as follows:

\(\cos \left(\theta \right)=\frac{{\rm{L}}\,\cdot\, {\rm{N}}}{\left|{\rm{L}}\right|{\rm{|N|}}}=\frac{\mathop{\sum }\nolimits_{i=1}^{n}{L}_{i}{N}_{i}}{\sqrt{\mathop{\sum }\nolimits_{i=1}^{n}{L}_{i}^{2}}\sqrt{\mathop{\sum }\nolimits_{i=1}^{n}{N}_{i}^{2}}}\)

A high similarity value indicates a low difference between the two recognition outcomes, which in turn suggests a high level of proficiency in content elaboration.

To evaluate the effectiveness of the proposed measures in distinguishing different proficiency levels among nonnative Japanese speakers’ writing, we conducted a multi-faceted Rasch measurement analysis (Linacre, 1994 ). This approach applies measurement models to thoroughly analyze various factors that can influence test outcomes, including test takers’ proficiency, item difficulty, and rater severity, among others. The underlying principles and functionality of multi-faceted Rasch measurement are illustrated in (12).

\(\log \left(\frac{{P}_{{nijk}}}{{P}_{{nij}(k-1)}}\right)={B}_{n}-{D}_{i}-{C}_{j}-{F}_{k}\)

(12) defines the logarithmic transformation of the probability ratio ( P nijk /P nij(k-1) )) as a function of multiple parameters. Here, n represents the test taker, i denotes a writing proficiency measure, j corresponds to the human rater, and k represents the proficiency score. The parameter B n signifies the proficiency level of test taker n (where n ranges from 1 to N). D j represents the difficulty parameter of test item i (where i ranges from 1 to L), while C j represents the severity of rater j (where j ranges from 1 to J). Additionally, F k represents the step difficulty for a test taker to move from score ‘k-1’ to k . P nijk refers to the probability of rater j assigning score k to test taker n for test item i . P nij(k-1) represents the likelihood of test taker n being assigned score ‘k-1’ by rater j for test item i . Each facet within the test is treated as an independent parameter and estimated within the same reference framework. To evaluate the consistency of scores obtained through both human and computer analysis, we utilized the Infit mean-square statistic. This statistic is a chi-square measure divided by the degrees of freedom and is weighted with information. It demonstrates higher sensitivity to unexpected patterns in responses to items near a person’s proficiency level (Linacre, 2002 ). Fit statistics are assessed based on predefined thresholds for acceptable fit. For the Infit MNSQ, which has a mean of 1.00, different thresholds have been suggested. Some propose stricter thresholds ranging from 0.7 to 1.3 (Bond et al. 2021 ), while others suggest more lenient thresholds ranging from 0.5 to 1.5 (Eckes, 2009 ). In this study, we adopted the criterion of 0.70–1.30 for the Infit MNSQ.

Moving forward, we can now proceed to assess the effectiveness of the 16 proposed measures based on five criteria for accurately distinguishing various levels of writing proficiency among non-native Japanese speakers. To conduct this evaluation, we utilized the development dataset from the I-JAS corpus, as described in Section Dataset . Table 4 provides a measurement report that presents the performance details of the 14 metrics under consideration. The measure separation was found to be 4.02, indicating a clear differentiation among the measures. The reliability index for the measure separation was 0.891, suggesting consistency in the measurement. Similarly, the person separation reliability index was 0.802, indicating the accuracy of the assessment in distinguishing between individuals. All 16 measures demonstrated Infit mean squares within a reasonable range, ranging from 0.76 to 1.28. The Synonym overlap/paragraph (topic) measure exhibited a relatively high outfit mean square of 1.46, although the Infit mean square falls within an acceptable range. The standard error for the measures ranged from 0.13 to 0.28, indicating the precision of the estimates.

Table 5 further illustrated the weights assigned to different linguistic measures for score prediction, with higher weights indicating stronger correlations between those measures and higher scores. Specifically, the following measures exhibited higher weights compared to others: moving average type token ratio per essay has a weight of 0.0391. Mean dependency distance had a weight of 0.0388. Mean length of clause, calculated by dividing the number of words by the number of clauses, had a weight of 0.0374. Complex nominals per T-unit, calculated by dividing the number of complex nominals by the number of T-units, had a weight of 0.0379. Coordinate phrases rate, calculated by dividing the number of coordinate phrases by the number of clauses, had a weight of 0.0325. Grammatical error rate, representing the number of errors per essay, had a weight of 0.0322.

Criteria (output indicator)

The criteria used to evaluate the writing ability in this study were based on CEFR, which follows a six-point scale ranging from A1 to C2. To assess the quality of Japanese writing, the scoring criteria from Table 6 were utilized. These criteria were derived from the IELTS writing standards and served as assessment guidelines and prompts for the written output.

A prompt is a question or detailed instruction that is provided to the model to obtain a proper response. After several pilot experiments, we decided to provide the measures (Section Measures of writing proficiency for nonnative Japanese ) as the input prompt and use the criteria (Section Criteria (output indicator) ) as the output indicator. Regarding the prompt language, considering that the LLM was tasked with rating Japanese essays, would prompt in Japanese works better Footnote 5 ? We conducted experiments comparing the performance of GPT-4 using both English and Japanese prompts. Additionally, we utilized the Japanese local model OCLL with Japanese prompts. Multiple trials were conducted using the same sample. Regardless of the prompt language used, we consistently obtained the same grading results with GPT-4, which assigned a grade of B1 to the writing sample. This suggested that GPT-4 is reliable and capable of producing consistent ratings regardless of the prompt language. On the other hand, when we used Japanese prompts with the Japanese local model “OCLL”, we encountered inconsistent grading results. Out of 10 attempts with OCLL, only 6 yielded consistent grading results (B1), while the remaining 4 showed different outcomes, including A1 and B2 grades. These findings indicated that the language of the prompt was not the determining factor for reliable AES. Instead, the size of the training data and the model parameters played crucial roles in achieving consistent and reliable AES results for the language model.

The following is the utilized prompt, which details all measures and requires the LLM to score the essays using holistic and trait scores.

Please evaluate Japanese essays written by Japanese learners and assign a score to each essay on a six-point scale, ranging from A1, A2, B1, B2, C1 to C2. Additionally, please provide trait scores and display the calculation process for each trait score. The scoring should be based on the following criteria:

Moving average type-token ratio.

Number of lexical words (token) divided by the total number of words per essay.

Number of sophisticated word types divided by the total number of words per essay.

Mean length of clause.

Verb phrases per T-unit.

Clauses per T-unit.

Dependent clauses per T-unit.

Complex nominals per clause.

Adverbial clauses per clause.

Coordinate phrases per clause.

Mean dependency distance.

Synonym overlap paragraph (topic and keywords).

Word2vec cosine similarity.

Connectives per essay.

Conjunctions per essay.

Number of metadiscourse markers (types) divided by the total number of words.

Number of errors per essay.

Japanese essay text

出かける前に二人が地図を見ている間に、サンドイッチを入れたバスケットに犬が入ってしまいました。それに気づかずに二人は楽しそうに出かけて行きました。やがて突然犬がバスケットから飛び出し、二人は驚きました。バスケット の 中を見ると、食べ物はすべて犬に食べられていて、二人は困ってしまいました。(ID_JJJ01_SW1)

The score of the example above was B1. Figure 3 provides an example of holistic and trait scores provided by GPT-4 (with a prompt indicating all measures) via Bing Footnote 6 .

Example of GPT-4 AES and feedback (with a prompt indicating all measures).

Statistical analysis

The aim of this study is to investigate the potential use of LLM for nonnative Japanese AES. It seeks to compare the scoring outcomes obtained from feature-based AES tools, which rely on conventional machine learning technology (i.e. Jess, JWriter), with those generated by AI-driven AES tools utilizing deep learning technology (BERT, GPT, OCLL). To assess the reliability of a computer-assisted annotation tool, the study initially established human-human agreement as the benchmark measure. Subsequently, the performance of the LLM-based method was evaluated by comparing it to human-human agreement.

To assess annotation agreement, the study employed standard measures such as precision, recall, and F-score (Brants 2000 ; Lu 2010 ), along with the quadratically weighted kappa (QWK) to evaluate the consistency and agreement in the annotation process. Assume A and B represent human annotators. When comparing the annotations of the two annotators, the following results are obtained. The evaluation of precision, recall, and F-score metrics was illustrated in equations (13) to (15).

\({\rm{Recall}}(A,B)=\frac{{\rm{Number}}\,{\rm{of}}\,{\rm{identical}}\,{\rm{nodes}}\,{\rm{in}}\,A\,{\rm{and}}\,B}{{\rm{Number}}\,{\rm{of}}\,{\rm{nodes}}\,{\rm{in}}\,A}\)

\({\rm{Precision}}(A,\,B)=\frac{{\rm{Number}}\,{\rm{of}}\,{\rm{identical}}\,{\rm{nodes}}\,{\rm{in}}\,A\,{\rm{and}}\,B}{{\rm{Number}}\,{\rm{of}}\,{\rm{nodes}}\,{\rm{in}}\,B}\)

The F-score is the harmonic mean of recall and precision:

\({\rm{F}}-{\rm{score}}=\frac{2* ({\rm{Precision}}* {\rm{Recall}})}{{\rm{Precision}}+{\rm{Recall}}}\)

The highest possible value of an F-score is 1.0, indicating perfect precision and recall, and the lowest possible value is 0, if either precision or recall are zero.

In accordance with Taghipour and Ng ( 2016 ), the calculation of QWK involves two steps:

Step 1: Construct a weight matrix W as follows:

\({W}_{{ij}}=\frac{{(i-j)}^{2}}{{(N-1)}^{2}}\)

i represents the annotation made by the tool, while j represents the annotation made by a human rater. N denotes the total number of possible annotations. Matrix O is subsequently computed, where O_( i, j ) represents the count of data annotated by the tool ( i ) and the human annotator ( j ). On the other hand, E refers to the expected count matrix, which undergoes normalization to ensure that the sum of elements in E matches the sum of elements in O.

Step 2: With matrices O and E, the QWK is obtained as follows:

K = 1- \(\frac{\sum i,j{W}_{i,j}\,{O}_{i,j}}{\sum i,j{W}_{i,j}\,{E}_{i,j}}\)

The value of the quadratic weighted kappa increases as the level of agreement improves. Further, to assess the accuracy of LLM scoring, the proportional reductive mean square error (PRMSE) was employed. The PRMSE approach takes into account the variability observed in human ratings to estimate the rater error, which is then subtracted from the variance of the human labels. This calculation provides an overall measure of agreement between the automated scores and true scores (Haberman et al. 2015 ; Loukina et al. 2020 ; Taghipour and Ng, 2016 ). The computation of PRMSE involves the following steps:

Step 1: Calculate the mean squared errors (MSEs) for the scoring outcomes of the computer-assisted tool (MSE tool) and the human scoring outcomes (MSE human).

Step 2: Determine the PRMSE by comparing the MSE of the computer-assisted tool (MSE tool) with the MSE from human raters (MSE human), using the following formula:

\({\rm{PRMSE}}=1-\frac{({\rm{MSE}}\,{\rm{tool}})\,}{({\rm{MSE}}\,{\rm{human}})\,}=1-\,\frac{{\sum }_{i}^{n}=1{({{\rm{y}}}_{i}-{\hat{{\rm{y}}}}_{{\rm{i}}})}^{2}}{{\sum }_{i}^{n}=1{({{\rm{y}}}_{i}-\hat{{\rm{y}}})}^{2}}\)

In the numerator, ŷi represents the scoring outcome predicted by a specific LLM-driven AES system for a given sample. The term y i − ŷ i represents the difference between this predicted outcome and the mean value of all LLM-driven AES systems’ scoring outcomes. It quantifies the deviation of the specific LLM-driven AES system’s prediction from the average prediction of all LLM-driven AES systems. In the denominator, y i − ŷ represents the difference between the scoring outcome provided by a specific human rater for a given sample and the mean value of all human raters’ scoring outcomes. It measures the discrepancy between the specific human rater’s score and the average score given by all human raters. The PRMSE is then calculated by subtracting the ratio of the MSE tool to the MSE human from 1. PRMSE falls within the range of 0 to 1, with larger values indicating reduced errors in LLM’s scoring compared to those of human raters. In other words, a higher PRMSE implies that LLM’s scoring demonstrates greater accuracy in predicting the true scores (Loukina et al. 2020 ). The interpretation of kappa values, ranging from 0 to 1, is based on the work of Landis and Koch ( 1977 ). Specifically, the following categories are assigned to different ranges of kappa values: −1 indicates complete inconsistency, 0 indicates random agreement, 0.0 ~ 0.20 indicates extremely low level of agreement (slight), 0.21 ~ 0.40 indicates moderate level of agreement (fair), 0.41 ~ 0.60 indicates medium level of agreement (moderate), 0.61 ~ 0.80 indicates high level of agreement (substantial), 0.81 ~ 1 indicates almost perfect level of agreement. All statistical analyses were executed using Python script.

Results and discussion

Annotation reliability of the llm.

This section focuses on assessing the reliability of the LLM’s annotation and scoring capabilities. To evaluate the reliability, several tests were conducted simultaneously, aiming to achieve the following objectives:

Assess the LLM’s ability to differentiate between test takers with varying levels of oral proficiency.

Determine the level of agreement between the annotations and scoring performed by the LLM and those done by human raters.

The evaluation of the results encompassed several metrics, including: precision, recall, F-Score, quadratically-weighted kappa, proportional reduction of mean squared error, Pearson correlation, and multi-faceted Rasch measurement.

Inter-annotator agreement (human–human annotator agreement)

We started with an agreement test of the two human annotators. Two trained annotators were recruited to determine the writing task data measures. A total of 714 scripts, as the test data, was utilized. Each analysis lasted 300–360 min. Inter-annotator agreement was evaluated using the standard measures of precision, recall, and F-score and QWK. Table 7 presents the inter-annotator agreement for the various indicators. As shown, the inter-annotator agreement was fairly high, with F-scores ranging from 1.0 for sentence and word number to 0.666 for grammatical errors.

The findings from the QWK analysis provided further confirmation of the inter-annotator agreement. The QWK values covered a range from 0.950 ( p  = 0.000) for sentence and word number to 0.695 for synonym overlap number (keyword) and grammatical errors ( p  = 0.001).

Agreement of annotation outcomes between human and LLM

To evaluate the consistency between human annotators and LLM annotators (BERT, GPT, OCLL) across the indices, the same test was conducted. The results of the inter-annotator agreement (F-score) between LLM and human annotation are provided in Appendix B-D. The F-scores ranged from 0.706 for Grammatical error # for OCLL-human to a perfect 1.000 for GPT-human, for sentences, clauses, T-units, and words. These findings were further supported by the QWK analysis, which showed agreement levels ranging from 0.807 ( p  = 0.001) for metadiscourse markers for OCLL-human to 0.962 for words ( p  = 0.000) for GPT-human. The findings demonstrated that the LLM annotation achieved a significant level of accuracy in identifying measurement units and counts.

Reliability of LLM-driven AES’s scoring and discriminating proficiency levels

This section examines the reliability of the LLM-driven AES scoring through a comparison of the scoring outcomes produced by human raters and the LLM ( Reliability of LLM-driven AES scoring ). It also assesses the effectiveness of the LLM-based AES system in differentiating participants with varying proficiency levels ( Reliability of LLM-driven AES discriminating proficiency levels ).

Reliability of LLM-driven AES scoring

Table 8 summarizes the QWK coefficient analysis between the scores computed by the human raters and the GPT-4 for the individual essays from I-JAS Footnote 7 . As shown, the QWK of all measures ranged from k  = 0.819 for lexical density (number of lexical words (tokens)/number of words per essay) to k  = 0.644 for word2vec cosine similarity. Table 9 further presents the Pearson correlations between the 16 writing proficiency measures scored by human raters and GPT 4 for the individual essays. The correlations ranged from 0.672 for syntactic complexity to 0.734 for grammatical accuracy. The correlations between the writing proficiency scores assigned by human raters and the BERT-based AES system were found to range from 0.661 for syntactic complexity to 0.713 for grammatical accuracy. The correlations between the writing proficiency scores given by human raters and the OCLL-based AES system ranged from 0.654 for cohesion to 0.721 for grammatical accuracy. These findings indicated an alignment between the assessments made by human raters and both the BERT-based and OCLL-based AES systems in terms of various aspects of writing proficiency.

Reliability of LLM-driven AES discriminating proficiency levels

After validating the reliability of the LLM’s annotation and scoring, the subsequent objective was to evaluate its ability to distinguish between various proficiency levels. For this analysis, a dataset of 686 individual essays was utilized. Table 10 presents a sample of the results, summarizing the means, standard deviations, and the outcomes of the one-way ANOVAs based on the measures assessed by the GPT-4 model. A post hoc multiple comparison test, specifically the Bonferroni test, was conducted to identify any potential differences between pairs of levels.

As the results reveal, seven measures presented linear upward or downward progress across the three proficiency levels. These were marked in bold in Table 10 and comprise one measure of lexical richness, i.e. MATTR (lexical diversity); four measures of syntactic complexity, i.e. MDD (mean dependency distance), MLC (mean length of clause), CNT (complex nominals per T-unit), CPC (coordinate phrases rate); one cohesion measure, i.e. word2vec cosine similarity and GER (grammatical error rate). Regarding the ability of the sixteen measures to distinguish adjacent proficiency levels, the Bonferroni tests indicated that statistically significant differences exist between the primary level and the intermediate level for MLC and GER. One measure of lexical richness, namely LD, along with three measures of syntactic complexity (VPT, CT, DCT, ACC), two measures of cohesion (SOPT, SOPK), and one measure of content elaboration (IMM), exhibited statistically significant differences between proficiency levels. However, these differences did not demonstrate a linear progression between adjacent proficiency levels. No significant difference was observed in lexical sophistication between proficiency levels.

To summarize, our study aimed to evaluate the reliability and differentiation capabilities of the LLM-driven AES method. For the first objective, we assessed the LLM’s ability to differentiate between test takers with varying levels of oral proficiency using precision, recall, F-Score, and quadratically-weighted kappa. Regarding the second objective, we compared the scoring outcomes generated by human raters and the LLM to determine the level of agreement. We employed quadratically-weighted kappa and Pearson correlations to compare the 16 writing proficiency measures for the individual essays. The results confirmed the feasibility of using the LLM for annotation and scoring in AES for nonnative Japanese. As a result, Research Question 1 has been addressed.

Comparison of BERT-, GPT-, OCLL-based AES, and linguistic-feature-based computation methods

This section aims to compare the effectiveness of five AES methods for nonnative Japanese writing, i.e. LLM-driven approaches utilizing BERT, GPT, and OCLL, linguistic feature-based approaches using Jess and JWriter. The comparison was conducted by comparing the ratings obtained from each approach with human ratings. All ratings were derived from the dataset introduced in Dataset . To facilitate the comparison, the agreement between the automated methods and human ratings was assessed using QWK and PRMSE. The performance of each approach was summarized in Table 11 .

The QWK coefficient values indicate that LLMs (GPT, BERT, OCLL) and human rating outcomes demonstrated higher agreement compared to feature-based AES methods (Jess and JWriter) in assessing writing proficiency criteria, including lexical richness, syntactic complexity, content, and grammatical accuracy. Among the LLMs, the GPT-4 driven AES and human rating outcomes showed the highest agreement in all criteria, except for syntactic complexity. The PRMSE values suggest that the GPT-based method outperformed linguistic feature-based methods and other LLM-based approaches. Moreover, an interesting finding emerged during the study: the agreement coefficient between GPT-4 and human scoring was even higher than the agreement between different human raters themselves. This discovery highlights the advantage of GPT-based AES over human rating. Ratings involve a series of processes, including reading the learners’ writing, evaluating the content and language, and assigning scores. Within this chain of processes, various biases can be introduced, stemming from factors such as rater biases, test design, and rating scales. These biases can impact the consistency and objectivity of human ratings. GPT-based AES may benefit from its ability to apply consistent and objective evaluation criteria. By prompting the GPT model with detailed writing scoring rubrics and linguistic features, potential biases in human ratings can be mitigated. The model follows a predefined set of guidelines and does not possess the same subjective biases that human raters may exhibit. This standardization in the evaluation process contributes to the higher agreement observed between GPT-4 and human scoring. Section Prompt strategy of the study delves further into the role of prompts in the application of LLMs to AES. It explores how the choice and implementation of prompts can impact the performance and reliability of LLM-based AES methods. Furthermore, it is important to acknowledge the strengths of the local model, i.e. the Japanese local model OCLL, which excels in processing certain idiomatic expressions. Nevertheless, our analysis indicated that GPT-4 surpasses local models in AES. This superior performance can be attributed to the larger parameter size of GPT-4, estimated to be between 500 billion and 1 trillion, which exceeds the sizes of both BERT and the local model OCLL.

Prompt strategy

In the context of prompt strategy, Mizumoto and Eguchi ( 2023 ) conducted a study where they applied the GPT-3 model to automatically score English essays in the TOEFL test. They found that the accuracy of the GPT model alone was moderate to fair. However, when they incorporated linguistic measures such as cohesion, syntactic complexity, and lexical features alongside the GPT model, the accuracy significantly improved. This highlights the importance of prompt engineering and providing the model with specific instructions to enhance its performance. In this study, a similar approach was taken to optimize the performance of LLMs. GPT-4, which outperformed BERT and OCLL, was selected as the candidate model. Model 1 was used as the baseline, representing GPT-4 without any additional prompting. Model 2, on the other hand, involved GPT-4 prompted with 16 measures that included scoring criteria, efficient linguistic features for writing assessment, and detailed measurement units and calculation formulas. The remaining models (Models 3 to 18) utilized GPT-4 prompted with individual measures. The performance of these 18 different models was assessed using the output indicators described in Section Criteria (output indicator) . By comparing the performances of these models, the study aimed to understand the impact of prompt engineering on the accuracy and effectiveness of GPT-4 in AES tasks.

Based on the PRMSE scores presented in Fig. 4 , it was observed that Model 1, representing GPT-4 without any additional prompting, achieved a fair level of performance. However, Model 2, which utilized GPT-4 prompted with all measures, outperformed all other models in terms of PRMSE score, achieving a score of 0.681. These results indicate that the inclusion of specific measures and prompts significantly enhanced the performance of GPT-4 in AES. Among the measures, syntactic complexity was found to play a particularly significant role in improving the accuracy of GPT-4 in assessing writing quality. Following that, lexical diversity emerged as another important factor contributing to the model’s effectiveness. The study suggests that a well-prompted GPT-4 can serve as a valuable tool to support human assessors in evaluating writing quality. By utilizing GPT-4 as an automated scoring tool, the evaluation biases associated with human raters can be minimized. This has the potential to empower teachers by allowing them to focus on designing writing tasks and guiding writing strategies, while leveraging the capabilities of GPT-4 for efficient and reliable scoring.

PRMSE scores of the 18 AES models.

This study aimed to investigate two main research questions: the feasibility of utilizing LLMs for AES and the impact of prompt engineering on the application of LLMs in AES.

To address the first objective, the study compared the effectiveness of five different models: GPT, BERT, the Japanese local LLM (OCLL), and two conventional machine learning-based AES tools (Jess and JWriter). The PRMSE values indicated that the GPT-4-based method outperformed other LLMs (BERT, OCLL) and linguistic feature-based computational methods (Jess and JWriter) across various writing proficiency criteria. Furthermore, the agreement coefficient between GPT-4 and human scoring surpassed the agreement among human raters themselves, highlighting the potential of using the GPT-4 tool to enhance AES by reducing biases and subjectivity, saving time, labor, and cost, and providing valuable feedback for self-study. Regarding the second goal, the role of prompt design was investigated by comparing 18 models, including a baseline model, a model prompted with all measures, and 16 models prompted with one measure at a time. GPT-4, which outperformed BERT and OCLL, was selected as the candidate model. The PRMSE scores of the models showed that GPT-4 prompted with all measures achieved the best performance, surpassing the baseline and other models.

In conclusion, this study has demonstrated the potential of LLMs in supporting human rating in assessments. By incorporating automation, we can save time and resources while reducing biases and subjectivity inherent in human rating processes. Automated language assessments offer the advantage of accessibility, providing equal opportunities and economic feasibility for individuals who lack access to traditional assessment centers or necessary resources. LLM-based language assessments provide valuable feedback and support to learners, aiding in the enhancement of their language proficiency and the achievement of their goals. This personalized feedback can cater to individual learner needs, facilitating a more tailored and effective language-learning experience.

There are three important areas that merit further exploration. First, prompt engineering requires attention to ensure optimal performance of LLM-based AES across different language types. This study revealed that GPT-4, when prompted with all measures, outperformed models prompted with fewer measures. Therefore, investigating and refining prompt strategies can enhance the effectiveness of LLMs in automated language assessments. Second, it is crucial to explore the application of LLMs in second-language assessment and learning for oral proficiency, as well as their potential in under-resourced languages. Recent advancements in self-supervised machine learning techniques have significantly improved automatic speech recognition (ASR) systems, opening up new possibilities for creating reliable ASR systems, particularly for under-resourced languages with limited data. However, challenges persist in the field of ASR. First, ASR assumes correct word pronunciation for automatic pronunciation evaluation, which proves challenging for learners in the early stages of language acquisition due to diverse accents influenced by their native languages. Accurately segmenting short words becomes problematic in such cases. Second, developing precise audio-text transcriptions for languages with non-native accented speech poses a formidable task. Last, assessing oral proficiency levels involves capturing various linguistic features, including fluency, pronunciation, accuracy, and complexity, which are not easily captured by current NLP technology.

Data availability

The dataset utilized was obtained from the International Corpus of Japanese as a Second Language (I-JAS). The data URLs: [ https://www2.ninjal.ac.jp/jll/lsaj/ihome2.html ].

J-CAT and TTBJ are two computerized adaptive tests used to assess Japanese language proficiency.

SPOT is a specific component of the TTBJ test.

J-CAT: https://www.j-cat2.org/html/ja/pages/interpret.html

SPOT: https://ttbj.cegloc.tsukuba.ac.jp/p1.html#SPOT .

The study utilized a prompt-based GPT-4 model, developed by OpenAI, which has an impressive architecture with 1.8 trillion parameters across 120 layers. GPT-4 was trained on a vast dataset of 13 trillion tokens, using two stages: initial training on internet text datasets to predict the next token, and subsequent fine-tuning through reinforcement learning from human feedback.

https://www2.ninjal.ac.jp/jll/lsaj/ihome2-en.html .

http://jhlee.sakura.ne.jp/JEV/ by Japanese Learning Dictionary Support Group 2015.

We express our sincere gratitude to the reviewer for bringing this matter to our attention.

On February 7, 2023, Microsoft began rolling out a major overhaul to Bing that included a new chatbot feature based on OpenAI’s GPT-4 (Bing.com).

Appendix E-F present the analysis results of the QWK coefficient between the scores computed by the human raters and the BERT, OCLL models.

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This research was funded by National Foundation of Social Sciences (22BYY186) to Wenchao Li.

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Phi Beta Kappa recognizes winning words and music of Charles Nichols, Ashley Shew, and Ella Moeltner

• Melody Warnick
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An album of string quartets, a book reimagining disability, and an essay about anti-fat bias all received honors this spring from the Mu of Virginia chapter of Phi Beta Kappa . 

Charles Nichols, a faculty member in the School of Performing Arts , part of the College of Architecture, Arts, and Design , and Ashley Shew, a faculty member in the College of Liberal Arts and Human Sciences , received Sturm Awards recognizing excellence in creative arts and research, while College of Liberal Arts and Human Sciences student Ella Moeltner was honored for undergraduate writing.

Sturm Award for Excellence in Performance and Creative Arts

Violinist and composer Nichols , associate professor of composition and creative technologies, received the Sturm Award for Excellence in Performance and Creative Arts for his album “ Crossing the Divide .” Released by Centaur Records, one of the oldest classical labels in America, “Crossing the Divide” was supported in part by grants from the Office of the Executive Vice President and Provost , University Libraries , the College of Liberal Arts and Human Sciences, and the School of Performing Arts.

The album’s four original string quartets — two for acoustic instruments and two for amplified instruments processed with effects — each have their own origin story and purpose. For instance, “At the Boundary,” written for amplified string quartet and computer, “searches for the border between technically challenging music … and music that is fun to play and hear.”’ In creating it, Nichols found inspiration in sources as disparate as classical composers Bartók and Shostakovich and the Swedish metal band Opeth. “Verdigris,” on the other hand, began as nostalgic theme music for a radio history of Butte, Montana. 

Sturm Award for Excellence in Research

The Sturm Award for Excellence in Research was given to bioethicist Shew , associate professor in the Department of Science, Technology, and Society , for her widely lauded book “ Against Technoableism: Rethinking Who Needs Improvement.”

Described as “a manifesto exploding what we think we know about disability and arguing that disabled people are the real experts when it comes to technology and disability,” “Against Technoableism” repudiates the belief that technology is a “solution for disability” and proposes envisioning disabilities “not as liabilities, but as skill sets enabling all of us to navigate a challenging world.” Booklist recommended Shew’s work as “an essential text for the nondisabled to use to educate themselves on the harms of technoableism,” and Publisher’s Weekly predicted it would “galvanize readers to demand genuine equality for people with disabilities.”

John D. Wilson Essay Contest Award

Given annually to the best analytical or interpretive essay by an undergraduate, the 2024 John D. Wilson Essay prize was awarded to Moeltner, a senior from Blacksburg majoring in sociology  with ​​minors in visual arts and society and diversity and community engagement.

Moeltner’s essay addresses the role and causes of anti-fat bias in society, arguing that fatphobia stems primarily from “classist, sexist, and racist origins, the moralization of obesity, an oversimplification of the effect of fatness on mortality, and the many flaws associated with research on obesity currently available to the public.” Using social identity, attribution, and sociocultural theories, Moeltner argues that programs like Virginia Tech’s The Body Project can introduce more nuanced, empathetic ideas about body size, health, weight, and appearance.

As the country’s oldest and most widely known honor society, Phi Beta Kappa celebrates and advocates excellence in the liberal arts and sciences.

Dave Guerin

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Guest Essay

A Chill Has Fallen Over Jews in Publishing

By James Kirchick

Mr. Kirchick is a contributing writer to Tablet magazine, a writer at large for Air Mail and the author of “Secret City: The Hidden History of Gay Washington.”

This month, an account on X with the handle @moyurireads and 360 followers published a link to a color-coded spreadsheet classifying nearly 200 writers according to their views on the “genocide” in Gaza. Titled “Is Your Fav Author a Zionist?,” it reads like a cross between Tiger Beat and “The Protocols of the Elders of Zion.”

The novelist Emily St. John Mandel, the author of “Station Eleven” and “Sea of Tranquility,” earned a red “pro-Israel/Zionist” classification because, according to the list’s creator, she “travels to Israel frequently talks favorably about it.” Simply for posting a link to the Israeli chapter of the Red Cross, the novelist Kristin Hannah was deemed a “Zionist,” as was the author Gabrielle Zevin for delivering a book talk to Hadassah, a Jewish women’s organization. Needless to say, the creator of the list — whose post on X announcing it garnered over a million views within a few days — encourages readers to boycott any works produced by “Zionists.”

The spreadsheet is but the crudest example of the virulently anti-Israel — and increasingly antisemitic — sentiment that has been coursing through the literary world since the Hamas massacre of Oct. 7. Much of it revolves around the charge of genocide and seeks to punish Zionists and anyone else who refuses to explicitly denounce the Jewish state for allegedly committing said crime. Since a large majority of American Jews (80 percent of whom, according to a 2020 poll , said that caring about Israel is an important or essential part of their Judaism) are Zionists, to accuse all Zionists of complicity in genocide is to anathematize a core component of Jewish identity.

Over the past several months, a litmus test has emerged across wide swaths of the literary world effectively excluding Jews from full participation unless they denounce Israel. This phenomenon has been unfolding in progressive spaces (academia, politics, cultural organizations) for quite some time. That it has now hit the rarefied, highbrow realm of publishing — where Jewish Americans have made enormous contributions and the vitality of which depends on intellectual pluralism and free expression — is particularly alarming.

As is always and everywhere the case, this growing antisemitism is concomitant with a rising illiberalism. Rarely, if ever, do writers express unanimity on a contentious political issue. We’re a naturally argumentative bunch who — at least in theory — answer only to our own consciences.

To compel them to express support or disapproval for a cause is one of the cruelest things a society can do to writers, whose role is to tell society what they believe, regardless of how popular the message may be. The drawing up of lists, in particular, is a tactic with a long and ignominious history, employed by the enemies of literature — and liberty — on both the left and the right. But the problem goes much deeper than a tyro blacklist targeting “Zionists.”

One of the greatest mass delusions of the 21st century is the belief that Israel is committing a genocide against Palestinians. This grotesque moral inversion — in which a genocidal terrorist organization that instigated a war with Israel by committing the largest massacre of Jews since the Holocaust is absolved of responsibility while the victim of Hamas’s attack is charged with perpetrating the worst crime known to man — began taking shape before Israel even launched its ground invasion of Gaza.

A charitable description of those imputing genocidal motivations to Israel is that they are ignorant, essentially believing the word to mean “large numbers of civilian casualties.” (Here it’s worth noting that the United Nations, to little notice, has significantly lowered its estimate of the number of women and children killed in Gaza.) For others, accusing Israel of genocide is an emotional outlet for expressing outrage at such a horrific loss of life. A third, more pessimistic, characterization of the ubiquitous genocide canard is that it is only the latest iteration of the ancient antisemitic blood libel, which held that Jews murdered gentile children in order to use their blood for religious rituals.

College students and professional activists using overheated and imprecise language to convey their strongly held beliefs is hardly uncommon, and much of the intemperate language being directed at Israel and its Zionist supporters can be attributed to the hyperbole that increasingly characterizes our political discourse. What should worry us more is when people who have dedicated their lives to the written word manipulate language for a political end, one that is stigmatizing Jews.

Nine days after the Oct. 7 attack, the popular website Literary Hub began publishing what has since become a near-daily torrent of agitprop invective against what it describes as the “rogue ethnostate” of Israel, which it routinely accuses of committing genocide. In March, after a mass resignation of its staff members , the literary magazine Guernica retracted a personal essay by a left-wing Israeli woman about her experience volunteering to drive Palestinian children to Israel for medical treatment. In her resignation letter, one of the magazine’s co-publishers denounced the piece as “a hand-wringing apologia for Zionism and the ongoing genocide in Palestine.”

Whereas antisemitism in the literary world used to lurk in the shadows, according to the Jewish Book Council’s chief executive, Naomi Firestone-Teeter, since Oct. 7, it has become increasingly overt. “The fact that people have felt so proud and open about it is a different beast entirely,” she said. One of the most disturbing developments in this regard has been the frequency and contempt with which the word “Zionist” is now spit from people’s mouths in the United States.

Until relatively recently, the use of “Zionist” as a slur was most commonly confined to Soviet and Arab propagandists, who spent decades trying to render the word the moral equivalent of “Nazi.” Today many progressives use the word in similar fashion, making no distinction between a Zionist who supports a two-state solution (which, presumably, most Jews in the overwhelmingly liberal literary world do) and one who believes in a “Greater Israel” encompassing the entirety of the West Bank and Gaza Strip. And while anyone can be a Zionist, I’ve found in my 20 years of reporting on antisemitism that many Jews essentially hear “Jew” when someone shouts “Zionist" at them.

The corruption of the words “genocide” and “Zionist” lies at the root of the controversy threatening to unravel PEN America, the storied writers’ organization. As with many a literary contretemps, it involves a cascade of open letters. In February a missive that gained almost 1,500 signatures was published demanding that PEN “wake up from its own silent, tepid, neither-here-nor-there, self-congratulatory middle of the road and take an actual stand against an actual genocide.” The dozens of statements PEN had issued by that time calling attention to the plight of writers in Gaza (who the letter, without citing evidence, claimed had been “targeted” by Israel for assassination) were insufficient. “We demand PEN America release an official statement” about the writers killed in Gaza the letter read, “and name their murderer: Israel, a Zionist colonial state funded by the U.S. government.”

On March 20, PEN acceded to the ultimatum that it endorse the call for a cease-fire. But that did not satiate its critics.

Last month, in advance of PEN’s annual literary awards ceremony, nearly half of the nominated writers withdrew from the competition. A subset of those writers then released another open letter , declaring, “Among writers of conscience, there is no disagreement. There is fact and fiction. The fact is that Israel is leading a genocide of the Palestinian people.” They accused PEN of “normalizing genocide,” denounced PEN for its “platforming of Zionists” and, most shamefully, called for the resignation of its Jewish chief executive, Suzanne Nossel, on account of her “longstanding commitments to Zionism.”

Along with eight other past presidents of PEN, Salman Rushdie signed a letter in defense of the organization , an intervention that earned him an “unclear” rating on the anti-Zionist blacklist. (He has braved far worse from Islamist zealots and their Western apologists.) PEN ultimately canceled both the awards ceremony and subsequent World Voices Festival.

Dissatisfaction with PEN’s purported lack of indignation over the deaths of Palestinian writers is a fig leaf. Where were the efforts by those now decrying PEN to protest the complete absence of freedom of expression that has characterized the Gaza Strip under 17 years of Hamas rule?

The real objectives behind the cynical weaponization of the word “genocide” and the authoritarian insistence that anyone who disagrees with it is an enabler of one are to shut down debate, defame dissenters and impose a rigid orthodoxy throughout the publishing world. It is a naked attempt to impose an ideological litmus test on anyone hoping to join the republic of letters — a litmus test that the vast majority of Jews would fail.

A campaign of intimidation, the sort of thing that happens to the dissident writers in closed societies whom PEN regularly champions, is afoot to pressure writers into toeing this new party line. PEN’s current president, Jenny Finney Boylan, recently said that she had heard from “many, many authors who do not agree with those withdrawing from PEN events and who do not wish to withdraw from our events themselves but are afraid of the consequences if they speak up.”

Compelling speech — which is ultimately what PEN’s critics are demanding of it — is the tactic of commissars, not writers in a free society. Censorship, thought policing and bullying are antithetical to the spirit of literature, which is best understood as an intimate conversation between the author and individual readers.

PEN’s detractors aren’t helping the Palestinian people with their whitewashing of Hamas. They’re engaged in a hostile takeover of a noble organization committed to the defense of free expression in order to advance a sectarian and bigoted political agenda.

Neil Gaiman, Taylor Jenkins-Reid, Ms. Mandel and other hugely successful authors need not worry that being denounced as a Zionist will hurt their careers. But the blacklists and the boycotts do not really target them. The actual targets of this crusade are lesser-known authors, budding novelists, aspiring poets and creative writing students — largely but not exclusively Jewish — who can feel a change in the air.

“I do now definitely have concern as a Jewish author — two years working on a novel that has absolutely nothing to do with Jews in any way, just because it says ‘National Jewish Book Award winner’ in my bio — that it may change the way readers see the work,” said a Jewish creative writing professor and novelist who spoke to me on the condition of being quoted anonymously.

No longer is being on the receiving end of a review bomb the worst fate that can befall a Jewish writer exploring Jewish themes; even getting such a book published is becoming increasingly difficult. “It’s very clear you have to have real courage to acquire and publish proudly Jewish voices and books about being Jewish,” a prominent literary agent told me. “When you are seen as genocidal, a moral insult to humanity because you believe in Israel’s right to exist, you are now seen as deserving of being canceled.”

There’s a distasteful irony in a literary community that has gone to the barricades fighting book “bans” now rallying to boycott authors based on their ethnoreligious identity. For a growing set of writers, declaring one’s belief that the world’s only Jewish state is a genocidal entity whose dismantlement is necessary for the advancement of humankind is a political fashion statement, a bauble one parades around in order to signify being on the right team. As was Stalinism for an earlier generation of left-wing literary intellectuals, so is antisemitism becoming the avant-garde.

James Kirchick is a contributing writer to Tablet magazine, a writer at large for Air Mail and the author of “Secret City: The Hidden History of Gay Washington.”

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