essay writing by eduref

10 Great Essay Writing Tips

Knowing how to write a college essay is a useful skill for anyone who plans to go to college. Most colleges and universities ask you to submit a writing sample with your application. As a student, you’ll also write essays in your courses. Impress your professors with your knowledge and skill by using these great essay writing tips.

Most college essays ask you to answer a question or synthesize information you learned in class. Review notes you have from lectures, read the recommended texts and make sure you understand the topic. You should refer to these sources in your essay.

Plan Your Essay

Many students see planning as a waste of time, but it actually saves you time. Take a few minutes to think about the topic and what you want to say about it. You can write an outline, draw a chart or use a graphic organizer to arrange your ideas. This gives you a chance to spot problems in your ideas before you spend time writing out the paragraphs.

Choose a Writing Method That Feels Comfortable

You might have to type your essay before turning it in, but that doesn’t mean you have to write it that way. Some people find it easy to write out their ideas by hand. Others prefer typing in a word processor where they can erase and rewrite as needed. Find the one that works best for you and stick with it.

View It as a Conversation

Writing is a form of communication, so think of your essay as a conversation between you and the reader. Think about your response to the source material and the topic. Decide what you want to tell the reader about the topic. Then, stay focused on your response as you write.

Provide the Context in the Introduction

If you look at an example of an essay introduction, you’ll see that the best essays give the reader a context. Think of how you introduce two people to each other. You share the details you think they will find most interesting. Do this in your essay by stating what it’s about and then telling readers what the issue is.

Explain What Needs to be Explained

Sometimes you have to explain concepts or define words to help the reader understand your viewpoint. You also have to explain the reasoning behind your ideas. For example, it’s not enough to write that your greatest achievement is running an ultra marathon. You might need to define ultra marathon and explain why finishing the race is such an accomplishment.

Answer All the Questions

After you finish writing the first draft of your essay, make sure you’ve answered all the questions you were supposed to answer. For example, essays in compare and contrast format should show the similarities and differences between ideas, objects or events. If you’re writing about a significant achievement, describe what you did and how it affected you.

Stay Focused as You Write

Writing requires concentration. Find a place where you have few distractions and give yourself time to write without interruptions. Don’t wait until the night before the essay is due to start working on it.

Read the Essay Aloud to Proofread

When you finish writing your essay, read it aloud. You can do this by yourself or ask someone to listen to you read it. You’ll notice places where the ideas don’t make sense, and your listener can give you feedback about your ideas.

Avoid Filling the Page with Words

A great essay does more than follow an essay layout. It has something to say. Sometimes students panic and write everything they know about a topic or summarize everything in the source material. Your job as a writer is to show why this information is important.

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Essay Writing by EduRef

The world of AI has been developing rapidly over the past decade, with tech giants like Facebook, Amazon, Microsoft and Google competing against entire countries such as France, Israel and the United Kingdom. The AI breakthrough GPT-3 developed by OpenAI co-founded by Elon Musk is taking this competition to a whole new level. Eduref decided to find out if artificial intelligence can pass college exams just like humans do. A panel of professors created a writing prompt which was then given both to recent grads & undergraduate writers along with GPT-3 and had the panel grade their anonymous submissions followed by a survey for feedback about them. The results showed that while human writers achieved B’s and D’s on their research methods paper on COVID-19 vaccine efficacy; GPT-3 scored a “C” average across four subjects failing only one paper. Even when it came to writing policy memos for law class GPT 3 passed with flying colours getting a B-. This shows us that although AI isn’t perfect yet its capabilities are remarkable enough for it to achieve decent grades in college just like its human counterparts!

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Automated Essay Writing: An AIED Opinion

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• Published: 02 August 2022
• volume  32 ,  pages 1119–1126 ( 2022 )

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• Mike Sharples   ORCID: orcid.org/0000-0001-7081-3320 1  

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This opinion piece emerged from research for the book, Story Machines: How Computers Have Become Creative Writers , by Mike Sharples and Rafael Pérez y Pérez, published by Routledge. While thinking of ways to promote the book, I realised that students could employ AI story generators to write essays. That led me to research automated essay writing, write a Twitter thread that has garnered 43,000 engagements, and author a blog article (Sharples, 2022 ). The current piece is a revised and expanded version of that article.

Avoid common mistakes on your manuscript.

Essay Writing with Transformer AI Systems

Essays have formed part of academic assessment since the early 19th century, when students in some European universities were required to write scholarly papers for discussion in seminars (Kruse, 2006 ). Academic essays continue to be a mainstay of assessment in schools, colleges and universities because they are easy to set, assess depth of understanding, and train students in how to express an argument. In recent years, the scope of written assignments has expanded to include narrative, argumentative, reflective, expressive, responsive and analytical papers.

The widespread practice of setting written assignments as coursework has been criticised as laborious and unfair (Race, 2018 ). It is also subject to contract cheating through “essay mills” that sell written assignments to order, at fees of up to £400 for writing a 20-page essay Footnote 1 . A study by Newton ( 2018 ) found that 15.7% of students surveyed admitted to paying someone else to write an assignment. Now, an unintended consequence of generative “Transformer” AI systems such as GPT-3 is that they democratise cheating. A student can generate an entire essay in seconds, at a cost of around 50 US cents Footnote 2 . Equally worrying, would-be academic researchers can call on these systems to generate articles for submission to conferences and journals.

How do such Transformer AI systems work? How can we detect whether an academic essay has been written by an AI? Could any good come from widespread use of such technology? What does this mean for the AIED community?

How Does a Transformer AI Work?

Take time to read this brief undergraduate student essay on “A Critique of Learning Styles”. If this were your student, how would you assess the written work? What mark would you give? What are its strengths and weaknesses?

The construct of “learning styles” is problematic because it fails to account for the processes through which learning styles are shaped. Some students might develop a particular learning style because they have had particular experiences. Others might develop a particular learning style by trying to accommodate to a learning environment that was not well suited to their learning needs. Ultimately, we need to understand the interactions among learning styles and environmental and personal factors, and how these shape how we learn and the kinds of learning we experience. Learning Styles and Learning Modes In the 1970s, learning styles became an important feature of educational practice. In the 1990s, “learning modalities” became a major focus of learning style research. This is the idea that we process information in different ways. For example, some individuals may be auditory learners, benefiting from listening to lectures and using recorded materials. Others may be visual learners, who gain from using visual materials such as textbooks, handouts, and computer graphics. Still others may be kinesthetic learners, who benefit from learning by movement and doing. Numerous experiments have been conducted to test this idea, and a number of different classifications of learning modalities have been proposed. In a review of this research, Dunn and Dunn (1997) found that the evidence does not support the idea that people have a particular learning mode that is dominant or that they process information in a particular way. In their study, the authors found that when students were given a particular instructional treatment, they could be classified in a particular learning modality category. But when they were given a different instructional treatment, they were classified in a different category. In a follow-up study in which they gave students a number of instructional treatments, Dunn and Dunn found that students could be placed in a particular category in some treatments, but not others. Dunn and Dunn also found that the results varied by age. Older students generally fit the results of more than one modality, whereas younger students were more likely to fit the results of just one modality. This led them to conclude that style preferences are learned over the course of development. This is consistent with the idea that people are flexible in responding to the way they are taught. References Dunn, R., & Dunn, K. (1997). Learning styles: Research and practice. Journal of Research in Education, 7(2), 139–151.

The entire essay was written by GPT-3, a Transformer AI program. It was given the prompt “The construct of ‘learning styles’ is problematic because” and it generated the rest, including heading and citation. The text shown here is the first attempt. The reference at the end was generated by adding the prompt “References” to the end of the text and resubmitting.

Gaining access to GPT-3 is straightforward. Anyone with internet can sign up to the OpenAI website Footnote 3 , gain an account, click the “Playground” tab, type a prompt such as the title of an essay, set the maximum length of output (up to 4000 language “tokens”, or approximately 3000 words) and click the Submit button. A few seconds later, the system produces a typed and formatted text. Some companies are already promoting AI-based essay writing services Footnote 4 .

GPT-3 works like a highly trained text completer of the kind found on mobile phones and email interfaces. Instead of looking back at the last few characters and using these to predict the next word or two, it can attend to the previous 750 words it has written, to continue an entire short story, blog, or student essay. The same program can also summarise a scientific article in simpler language, write a review, translate languages, and answer general questions. In short, a Transformer AI is a general-purpose language machine.

How Can We Detect Whether An Essay is Written by a Transformer AI System?

Plagiarism software will not detect essays written by Transformers, because the text is generated, not copied. A Google search shows that each sentence in the essay above is original. Two plagiarism detectors each indicated over 95% original text Footnote 5 .

What better way to discover whether the essay is written by human or machine than to ask GPT-3? Here is its response when presented with the essay above and the prompt “Was that essay written by a human or a computer?”.

It is difficult to say for certain, but it seems more likely that it was written by a computer. The language is very technical and does not seem to flow smoothly. In addition, the ideas are presented in a very concise, bullet-point style, which is often seen in computer-generated texts.

Impressive, yet it gave a similar response when presented with the introduction to a highly-cited research paper written by Sharples (Sharples, 2010 ), claiming it “does exhibit some characteristics that are often associated with AI-generated text, such as a lack of clear authorial voice and a somewhat stilted, awkward style of writing”. Rather than attempt further embarrassing comparisons, we note that any sufficiently powerful program to determine whether a piece is written by human or machine could frequently be outwitted by an equally powerful AI text generator, in a futile computational arms race.

Humans fare no better than machines at detecting AI-generated essays. In a small study by EduRef.net Footnote 6 , college professors were asked to grade essays produced by human writers and by GPT-3, without being informed that any piece was generated by machine. For a Research Methods topic, the machine-written essay was given a grade of C, while the human essays were graded B and D. For US History, machine and human were given similar grades. For a Law essay, GPT-3 was graded B-, while the human essays ranged from A- to F. For one topic, Creative Writing, the machine essay was failed, while human-written essays were graded from A- to D+. The professors gave similar written feedback to the machine productions as to human writers.

A comprehensive study of state-of-the-art methods to determine if a piece of extended text is human-written or machine-generated concludes that “humans detect machine-generated texts at chance level” and that for AI-based detection “overall, the community needs to research and develop better solutions for mission-critical applications” (Uchendu et al., 2021 ). Students employ AI to write assignments. Teachers use AI to assess and review them (Lu & Cutumisu, 2021 ; Lagakis & Demetriadis, 2021 ). Nobody learns, nobody gains.

On the surface, our sample text appears to be a mediocre to good (though very short) student essay. It is correctly spelled, with good sentence construction. It begins with an appropriate claim and presents a coherent argument in support, backed up by evidence of a cited research study. The essay ends with a re-statement of the claim that learning styles are flexible and change with environment.

But look more closely and the paper falls apart. It references “Dunn, R., & Dunn, K. (1997). Learning styles: Research and practice. Journal of Research in Education, 7(2), 139–151.” There is a journal named Research in Education , but no issue 7(2) in 1997. Dunn & Dunn did publish research on learning styles, but not in that journal. GPT-3 has fashioned a plausible-looking but fake reference. The program also appears to have invented the research study it cites. We can find no research study by Dunn and Dunn which claims that learning styles are flexible, not fixed.

To understand why a Transformer AI program should write plausible text, yet invent references and research studies, we turn to the seminal paper written by the developers of GPT-3. In a discussion of its limitations, the authors write: “large pretrained language models are not grounded in other domains of experience, such as video or real-world physical interaction, and thus lack a large amount of context about the world” (Brown, et al. 2020 , p.34). Transformers are models of language not experiential knowledge. They are not designed to be scholarly – to check academic references and ensure that evidence is grounded in fact. In human terms, they are essentially inexperienced, unthinking and amoral. They have no ability to reflect on what they have written, to judge whether it is accurate and decent.

OpenAI has provided an add-on to GPT-3 that filters bad language. However, it is unlikely that the company will produce tools to check for accuracy. Its focus is on artificial general intelligence not education. Other companies could, in the future, provide tools to check generated references for accuracy or add genuine references to an article. But these would not overcome the fundamental limitation of Transformer language models such as GPT-3: that they have no internal inspectable model of how the world works to provide a basis for the system to reflect on the accuracy and scholarship of its generated work. Research is in progress to develop explainable neural AI (Gunning et al., 2019 ) and hybrid neural/symbolic AI systems (Garcez & Lamb, 2020 ) that might address this problem.

Could Any Good Come from Widespread Use of Such Technology?

Transformer AI systems belong to an alternative history of educational technology, where students have appropriated emerging devices – pocket calculators, mobile phones, machine translation software, and now AI essay generators – to make their lives easier. The response from teachers and institutions is a predictable sequence of ignore, resist, then belatedly accommodate.

It will be hard to ignore the growing number of students who submit assignments written by AI. Turnitin, the leading plagiarism checking company, admits that “we’re already seeing the beginnings of the oncoming AI wave … when students can push a button and the computer writes their paper” (Turnitin, 2020 ). As we have already indicated, resisting AI-generated assignments by deploying software to detect which ones are written by machine is likely to be a futile exercise. How, then, can we accommodate these new tools?

Teachers could restrict essay assignments to invigilated exams, but these are formal and time consuming. Alternatively, they could set reflective and contextualised written assignments that could not be generated by AI. For example, a teacher could set each student an independent research project, then ask for a written report on that specific project, give the student feedback on the report, then ask for the student to write a critical reflection on the feedback and issues raised by the project.

An imaginative way to incorporate AI-generated text into teaching could be for the teacher to employ Transformer AI to generate a set of alternative essays on a topic, then ask students to critique these and write their own better versions. Or set a complex question then ask each student to generate AI responses to the question and for the student to evaluate these responses in relation to the marking criteria. The student would then write an integrative essay drawing on the AI answers to address the original question. Footnote 7

Transformer AI can be a tool for creative writing. For example, the student writes a first paragraph, the AI continues with the second paragraph, and so on. The AI writing partner helps maintain a flow of words and also takes the story in unexpected directions, to which the student must respond. Generating a few alternative continuations to a story may help a student writer see creative writing not as a linear progression, but an exploration of a space of possibilities.

AI assisted writing exercises could focus on skills of critical reading, accuracy, argumentation and structure. Assignments where AI is not allowed could be assessed for style, expression, voice and personal reflection.

Additionally, teachers could explore with students the ethics and limits of generative AI. How does it feel to interact with an expert wordsmith that has no intrinsic morals and no experience of the world? Is writing with AI tantamount to plagiarism (Fyfe, 2022 ).

What Does This Mean for the AIED Community?

Reviewers for IJAIED will not be able to avoid the challenge of assessing whether a submitted article has been written with the aid of an AI system. As an exercise, we generated an entire short research paper. First, we chose at random the title of a real paper published in IJAIED: “Domain-Specific Modeling Languages in Computer-Based Learning Environments: a Systematic Approach to Support Science Learning through Computational Modeling” (Hutchins et al., 2020 ). Then we used GPT-3 to generate three alternative Abstracts, just from the title. We chose a generated abstract for a “review paper”. Then, we added to the abstract the heading “Introduction” and requested GPT-3 to generate the paper. We followed with a prompt of “Discussion” and then “References”, which GPT-3 added in neat APA format. Finally, we presented GPT-3 with just the newly generated Abstract and requested it to generate a new title for the paper. It responded with: “Using Domain-Specific Modeling Languages to Support Science Learning: A Review of the Literature”.

The result is an original 2,200 word “academic paper” produced in under five minutes. The output can be read at https://t.co/RTxogLRlJT . It will probably not pass a first Editor’s review but is a harbinger of a flood of papers generated with the aid of AI. IJAIED will not be the only journal to receive papers produced wholly or partly by AI, but we are well placed to lead a debate on how to detect and deal with them.

A related issue is how to respond to genuine papers in the general area of AI Transformer systems in education. Should we publish papers on new tools to automate essay writing, or software to detect AI-generated essays? Where is the dividing line between promoting competition between AI generators and detectors, and enabling new forms of academic writing assisted by generative AI?

This could be a pivotal time for education, as students equip themselves with powerful new AI tools that substitute for what some perceive as the drudgery of assessment. These will not just write essays for students but answer complex questions and generate computer code (Bombazine et al., 2021 ). An education system that depends on summative written assessment to grade student abilities may have reached its apotheosis.

Every new educational technology arrives with affordances and limitations. AI Transformer technology is a powerful general-purpose language model that is already becoming embedded in education through chatbots, text summarisers, language translators, and now essay generators and tools for creative writing. The AIED community is well placed not only to debate the application of these systems to education, but to design new generative AI tools for writing, reasoning and conversation for learning.

https://www.essaymills.co.uk/pricing .

https://openai.com/api/pricing/ . The cost to access the most powerful GPT-3 model is US$0.06 for 1000 tokens (or approximately 750 output words).

https://openai.com/api/ .

https://www.nichepursuits.com/best-ai-essay-writers/ .

https://plagiarismdetector.net/ , https://smallseotools.com/plagiarism-checker/ . The example essay has now been published online, so plagiarism detectors no longer indicate it as original.

https://best-universities.net/features/what-grades-can-ai-get-in-college/ .

These suggestions are based on responses by @jennicarr8 to a Twitter discussion on rethinking assessment in an era of generative AI. https://twitter.com/sharplm/status/1534051131978047494 .

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I wish to thank Judy Kay for valuable comments on a draft of this article.

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Sharples, M. Automated Essay Writing: An AIED Opinion. Int J Artif Intell Educ 32 , 1119–1126 (2022). https://doi.org/10.1007/s40593-022-00300-7

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Who Writes Better: College Students or GPT-3 Essay Writers?

Table of Contents 

What is gpt-3 , the future of ai.

• What Can GPT- 3 Do? 

GPT-3 Essay Writer vs. College Students

• The Assessment 

Key Takeaways 

Artificial intelligence (AI) is no more an odyssey that we can experience only through cinema. It may no more be found in the shape of sentient machines with general artificial intelligence, as we see in the movies. It is very much a part of our real lives now. AI is now all around us. For example, did you know that Netflix’s recommendations engine is powered by AI and is worth $1 billion a year?

Travel and navigation, smartphone apps, smart homes, driverless cars, security and surveillance, social media feed, personalized recommendations in online advertising, proactive healthcare management, disease mapping, smart assistants like SIRI, Cortana, Alexa—AI is at work everywhere. Isn’t AI making our lives convenient then? Indeed it is, but we all understand that with our increasing dependence on AI, we are heading toward a future where machines will outperform humans in many jobs, a possibility that is echoing across various industries. 

Nell Watson, a Futurist and AI Technology Speaker who speaks about upcoming trends for businesses or organizations, says that in the future, which is not so distant, machines will be making business decisions such as devising strategies, choosing employees, forming companies, and so on. Other experts agree that job automation is the most immediate risk of AI. 

Those involved in creative fields like music, art, and literature often think that their work is considerably more secure from robots. After all, AI is all about calculative power, superlative memory, and high-speed decision-making; it lacks imagination and ingenuity, which is innately human. But can’t AI be trained to “learn” the rules of being creative? Can AI be an innovative music composer or a writer? 

It is hard to say, but the writing efficiency of Generative Pre-trained Transformer 3 (GPT-3)—an AI-powered text generator—indicates that content creation by AI can be creative enough to fool people into believing that humans write it. Last year, The Guardian , one of the most revered British newspapers, published an Op-Ed titled, “A robot wrote this entire article. Are you scared yet, human?” 

As per the news piece, GPT-3 produced not just one but eight different versions of the essay, and each essay was “unique, interesting and advanced a different argument.” The Guardian‘s article is highly descriptive of the writing potential of GPT-3. Although many criticized the Op-Ed as “ yet another GPT-3 Hype ,” at least it confirmed that AI could write (nearly) as well as humans. Maybe it is not efficient or creative enough to write a best-selling novel or a highly engaging blog yet. But is GPT-3’s writing skill on par with or even better than that of college students and content writers who write for SEO rankings? Before discussing this in detail, let’s first understand what GPT-3 is and what it can do. 

Introduced in May 2020, GPT-3 accelerated the hype and excitement in the world about AI. It was even referred to as “one of the most interesting and important AI systems ever produced.” Created by OpenAI , a San Francisco-based artificial intelligence firm co-founded by Elon Musk, GPT-3 is a language model that uses deep machine learning to generate human-like text that has a language structure. 

GPT-3 is not the first-of-its-kind; similar language models exist. Microsoft’s Turing NLG was the largest language model before the release of GPT-3. The capacity of these kinds of language models is defined in terms of “parameters.” Simply put, “more parameters” means more data has been used to train the model. The Turing NLG parameter capacity is 17 billion parameters, which is less than a tenth of GPT-3’s parameter capacity, which is 175 billion.  

What Can GPT-3 Do? 

GPT-3 can create anything with a language structure, which means it can write an essay, a blog, a news article, answer a question, summarize long texts, translate, and much more. It is interesting to learn how GPT-3 generates text. This AI uses a pre-trained algorithm for generating text. It has already been fed with a massive volume, around 570 GB , of textual information. Its algorithmic structure takes one piece of language (the prompt) as an input and then runs a training analysis on its vast body of pre-fed multiple datasets and then predicts the most useful piece of language for a reader.  

So basically, GPT-3 is a language prediction model with access to vast resources, making it more efficient in understanding how languages work and are structured. 

Many articles on the internet showcase how adept GPT-3 is at content creation. However, to test the efficacy of GPT-3 as a writer in comparison to college students, a company called EduRef conducted an essay-writing competition between GPT-3 essay writers and a group of recent college graduates and students. The students were asked to write essays on American history, research methods, creative writing, and law based on writing instructions created by a group of professors. The exact instructions were fed to the GPT-3 as prompt. The test papers were anonymized and given to the panel to test whether AI could get better grades than human students. 

• GPT-3 could score the highest grade of B- (B minus) in the test. It wrote a history essay on the American state of emergency. The human rivals also scored more or less similar grades, ranging from C+ to B. 
• GPT-3 performed well during the legal assignment as only one in three students could get a grade higher than the AI. 
• In the research methodology paper on COVID-19 vaccine effectiveness, GPT-3 scored a C, while students received Bs or Ds.
• The only paper GPT-3 failed was creative writing, with student writers scoring grades ranging from A to D+.

Overall, based on the test result analysis, it can be concluded that GPT-3’s technical skills are more refined than its creative skills. Its content showcases an exceptional understanding of grammar, syntax, and word frequency. It lacks craftsmanship, as it fails to demonstrate strong narratives in creative writing tasks. As per EduRef project manager Sam Larson, an academic himself, the low craftsmanship of GPT-3 in this area could be because of how GPT-3 pulls information. 

When it was revealed that the articles employed AI, the students seemed more interested in AI’s capacity to support them in their own essays! This competitive experiment also highlighted another important aspect: while real students took an average of three days to complete the assignment, GPT-3 spent between 3 to 20 minutes generating content for each task. 

Although Mr. Larson was impressed with the performance of GPT-3, he did emphasize that AI-generated content needs editors. Even while publishing the GPT-3-written article, The Guardian confirmed that it did edit the essays and asserted that “Editing GPT-3’s Op-Ed was no different to editing a human Op-Ed. We cut lines and paragraphs and rearranged their order in some places. Overall, it took less time to edit than many human Op-Eds.” 

The Assessment

Who writes better essays: college students or GPT-3? This is a subjective question as not all human writers are equal. As the EduRef study revealed, some students beat the AI model, but GPT-3 outperformed some. So, it is fair to conclude that GPT-3 is an efficient text-generating AI, and undeniably, its content creation capacities are way ahead of previously existing language models. But because GPT-3 is an early glimpse of the rapid AI evolution, in all probability, its succeeding versions will show higher degrees of sophistication. 

So, without getting tangled in deep discussions about who writes better or whether GPT 3 will take over writing jobs, it is important to accept that just like AI is revolutionizing other industries, it will also impact content marketing. To stay on top, humans need to team up with AI like GPT-3. 

Someone (a human) at The Guardian came up with the idea of getting an article written by GPT-3; maybe another human came up with that sensational topic and the awe-inspiring intro. And then GPT-3 wrote the essay; editors edited that. And the final output triggered discussions across social media and helped news organizations generate a lot of impressions and ad revenue. 

• In the future, which is not so distant, machines will be making business decisions such as devising strategies, choosing employees, forming companies.
• AI is all about calculative power, superlative memory, and high-speed decision-making; it lacks imagination and ingenuity, which is innately human. 
• Created by OpenAI , a San Francisco-based artificial intelligence firm co-founded by Elon Musk, GPT-3 is a language model that uses deep machine learning to generate human-like text that has a language structure.
• GPT-3 can create anything with a language structure, which means it can write an essay, a blog, a news article, answer a question, summarize long texts, translate, and much more. 
• AI uses a pre-trained algorithm for generating text. It has already been fed with a massive volume, around 570 GB , of textual information. Its algorithmic structure takes one piece of language (the prompt) as an input and then runs a training analysis on its vast body of pre-fed multiple datasets and then predicts the most useful piece of language for a reader.  

The quality of GPT-3 generated content improves after expert human writers or editors have fine-tuned it. In the same way, performances of content writers or content marketing campaigns can be made even more impressive by using the AI of GPT-3. For instance, consider Peppertype.ai . It is a GPR 3-based virtual content assistant that content professionals, college students, or anyone looking to generate short-scale content can use. This includes website headlines/copy, brand/product descriptions, tweet ideas, social media post captions, blog ideas, etc. 

The idea behind the tool is that content writing is a demanding job, and content ideation often takes much of a writer’s time, so the GPT-3 content creating tool helps writers with their ideation needs. Professional writers in content marketing, SEO, or digital agencies can use this AI tool to get multiple content ideas for Google ads, Facebook ads, tweets, blogs, articles, etc., all in a matter of just one click. The tool is also efficient in writing short content pieces such as e-commerce product descriptions and SEO meta descriptions. 

Quickchat is a wholly conversational AI ChatBot run by OpenAI’s GPT-3. It can be used in customer support, online applications, internal knowledge base, etc.

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The GPT-3 model has an open-source version: GPT-J created by Eleuther AI, a group of researchers who seek to democratize artificial intelligence.

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Auto essay: Teen allegedly scores straight A's with GPT-3

A teenager claims on Reddit that he writes school essays for himself and his classmates with the support of GPT-3 - collecting A's and earning money.

First, the post is published anonymously in the OpenAI subreddit. So, it's difficult to verify whether the story is true. Nevertheless, I'm reporting it because I think it's plausible, and that's the real insight.

Using GPT-3 to get better grades in school

"I feel a little guilty about it, but I don't really care that much anymore," writes the student, whose name is "Kevin" according to his profile information. He was born in 2005 and lives in Norway. He had been experimenting with GPT-3 for some time, he says, before deciding to test the system for school assignments.

"For a couple of weeks, I have made $100 profit by 'doing' homework for other classmates and now I am looked at as a genius," writes Kevin, who says he even uses GPT-3 as a writing aid for some of his Reddit posts.

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The student does not completely automate his homework with GPT-3: "I verify if everything is correct, and rephrase the text and shape it the way I want it. It kind of just boosts me and I finish my homework more quickly."

He also says the AI helps him discover new ways of writing and words he wouldn't have used without AI support.

"I learn a lot from just reading and editing the things that the AI writes. It's not like I just put in a prompt and paste the results in a Word document," Kevin writes.

As the conversation continues, the student gives an example of an AI-written essay. He uses OpenAI's GPT-3 DaVinchi model for it via the Playground user interface.

The biological perspective in psychology is the study of the mind and behavior from a biological standpoint. This perspective emphasizes the role of the nervous system, genes, and hormones in behavior and mental processes. Researchers who take a biological perspective often study the structure and function of the brain, as well as the effects of drugs and other chemicals on the brain and behavior.

The biological perspective has helped researchers to better understand mental disorders and to develop treatments for them. For example, the biological perspective has led to the development of medications that can help to regulate the brain chemistry of people with mental disorders. In addition, this perspective has contributed to our understanding of the role of genetics in mental disorders.

Overall, the biological perspective has provided valuable insights into the mind and behavior. This perspective has helped us to better understand mental disorders and to develop treatments for them.

A study on GPT-3 supports the story of the Reddit account

The story confirms a February 2021 study in which a U.S. website specializing in education (then called EduRef) had essays from GPT-3, anonymized essays from students, and freelance writers evaluated by professors.

LAION urges open AI models with continued rapid innovation

The texts from GPT-3 were slightly edited. In addition, the better of two versions was submitted. Facts and grammar remained unchanged.

The result: The AI texts passed the test and were rated similarly to the texts written by humans, some better, some worse.

Only in creative writing did the AI fail, lacking consistency in its story according to the professor's judgment. This lack of consistency is a well-known problem in AI text and image generators that has not yet been solved despite major advances in machine attention through transformer architectures.

• A Norwegian student generates essays using GPT-3 and talks about his experience with it on Reddit.
• He claims to get straight A's with the essays. He also earns money by generating essays for his classmates.
• The student says he uses GPT-3 mainly as a writing aid and to work faster. He edits the AI essay and does not take it as a direct copy.

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