academic writing ai

academic writing ai

The Impact of AI on Academic Writing

1. Introduction

The impact of modern technology on academic writing has revolutionized the entire education system – down from the way students research, to the way teachers teach. Artificial Intelligence is a groundbreaking new technology that is projected to have a vivid impact on education and will create significant changes to education quality, learning strategies, and educational needs. Over time, AI is expected to juggle several tasks at once much more efficiently than humans. This will mean quick and effective grading systems for teachers; also, an AI can provide tutoring services to students, virtual teaching assistants, and libraries of interactive lessons and tests. The role of teachers will ultimately be to supervise the effectiveness of the AI learning environment while freeing time to focus more on interactive and apprenticeship-style teaching. This could be an interim to a positive change in modern education, giving students access to effective learning 24/7 and giving teachers a better way to track student performance and achievement.

2. Benefits of AI in Academic Writing

John Hopkins is pursuing a Bachelor’s Degree at Alberta University. When he is not studying, he works as an Academic Assistant at Alberta School of Business. His knowledge in academia is quite profound. He argues that AI will help students generate a clearer understanding of different assignments and develop more organized research papers compared to traditional methods. This is because AI offers a plethora of visual and interactive tools to present organized ideas and analyze complex issues. This improvement can be seen in AI Translator. Compared to using a dictionary to translate an essay, the translation result from a program will be simpler and there will be a lower probability that the translated words are out of context.

Academic writing is known for its complexity and integrity. Writing academic content can be even more challenging as it plays an important role in learning. In the technology age, the use of AI and similar programs has significantly increased. AI accuracy and effectiveness have been proven to be very helpful in any kind of task, including apps that help with homework. This brings an interesting question: how will AI impact academic writing in the future? An argument can be made that academic writing and AI are a perfect match. AI will benefit academic writing as it will provide useful guidelines and help create higher quality content.

3. Challenges and Limitations of AI in Academic Writing

A related problem comes to the nature of learning to write effectively. In order to reduce the burden on teachers, there have been experiments with developing tools to help students learn to become better writers. The writing mentor system uses an advanced program that analyzes how students write and provides feedback on specific errors in grammar. If the student is making a certain type of error consistently, the program will identify the pattern and help the student correct it. This system will also track students’ improvement by tallying the errors that have been successfully avoided. While the writing mentor system is promising in that it can automate the providing of feedback to writing drafts, it is not a form of AI, and the inability to make the transition from the writing mentor system to an actual writing program is a limitation in attempting to automate the writing process.

There are challenges that need to be addressed in order for AI to be a useful tool in academic writing. The first involves the nature of academic writing. AI has had the most success in writing for genres with very explicit and rigid rules such as technical writing or journalistic writing. While there are certain style rules that AI can be programmed to follow in writing for these styles of genres, AI systems will struggle for more expressive or creative writing tasks that involve storytelling or academic writing in the humanities. Much academic writing involves developing and substantiating a thesis. This involves creative critical thinking, synthesis of information, and often developing a unique perspective. Teaching a computer to do these tasks is an AI-complete problem.

4. Ethical Considerations in AI-Enhanced Academic Writing

Despite the potential to improve students’ writing, there are ethical concerns surrounding the use of these tools. An example scenario involves a student who is a non-native English speaker. They are tasked with writing an essay in English but are not confident in their ability. They decide to use a language model to paraphrase some sentences to improve readability. This is clearly beneficial for the student but could be considered as violating academic integrity depending on the extent of the paraphrasing and the policy of the educational institution. A more complex scenario involves a student who is struggling to complete an assignment due to a lack of understanding or disinterest in the topic. This student could use a language model to autonomously generate an entire piece of writing, basing a high grade on the work done by the machine. While this would certainly benefit the student in the short term, it is considered a form of contract cheating and ruins the assessment for the student. This is a breach of academic integrity, and in the scenario involving a machine doing the work, it is also unethical to punish the machine with a poor grade.

At first, it is not clear that there are any ethical considerations. A machine learning model is trained by using a corpus of materials and refining the model using supervised learning. Language models trained in this way are a passive form of AI. Normal language models generate text when fed a prompt. GPT-3 does this by predicting the next word in a sequence based on the input it has received. This can be used to aid academic writing in a variety of ways. GPT-3 can generate example sentences to demonstrate the use of a word, complete sentences, or whole paragraphs. It is possible to use GPT-3 to perform sentence rephrasing without losing the original meaning, enabling students who lack confidence in their writing to submit work that is not plagiarized.

5. Conclusion

A recurring theme in the paper is the fragility of the boundary between AI and the human activity of writing. In some of the examples of AI as a tool in writing, the absence of any specific AI technology in the act of writing is notable. This is perhaps most obvious in the case of the spreadsheets and statistics software used by social scientists discussed at the start. Such tools automate certain tasks associated with research and writing, but they do not do so with the understanding that these are acts of writing. How far these are AI technologies is debatable, although they are certainly part of the broader context in which AI impinges upon writing. But even in the case of systems specifically designed for natural language text AI, there are examples where the work of the technology is to enable humans to write better, and there are cases where the aim is to replace human writing with machine generation of text.

The present paper sets out to argue that AI is relevant to the theory and practice of academic writing in a number of ways. We have suggested that AI technology is not simply a tool for automating certain tasks associated with writing, but that it is an agent of transformation in the very nature of writing in its situated context. We have considered some of the implications of this transformation in terms of the activity of writing, the status of writing as a form of reasoning, and the cultural-historical context in which the production and consumption of texts take place.