ai for academic writing

ai for academic writing

AI for Improving Academic Writing

1. Introduction

The goal of this paper is to introduce an innovative system which will make written English more accessible to foreign speakers. This system achieves this goal by first identifying the local flaws in the writing of non-native speakers. It then provides specific feedback based on these flaws with which non-native speakers can implement targeted improvements to their writing. This is done with a new version of the Virtual Writing Tutor, an ESL grammar checker that is to be embedded in a new Word add-in. This new system and the AI technology behind it are the result of a collaborative research project involving academics in the field of TESL and machine learning. This project was initiated in response to the frustration English teachers often feel when they realize that their students’ grammatical errors are symptoms of underlying knowledge gaps. Traditional grammar checkers find and correct errors, but they fail to help students acquire a better understanding of the language. Teachers also note that the sheer volume of errors on a typical student essay can be overwhelming and that many of the same errors are made repeatedly. With these realities in mind, it is clear that traditional grammar checkers are not meeting the writing improvement needs of the students and teachers who use them. A more systematic approach is needed.

2. Benefits of AI in Academic Writing

AI has widely helped in the educational sector. In academic writing, the work of the students is compared to various papers and articles available online and is given a percentage of originality. In case the student has done a close reference to the article, it may be marked as plagiarized and in worse cases the student may be rusticated or expelled from the college. Different tools and techniques are being developed to increase the accuracy in the detection of originality of the article. One such tool is being developed by Microsoft. It is a known fact that writing an academic research article is a stressful work. There are times when the researcher may be confused or get a writer’s block thus unable to proceed further in writing the article. At different times, the researcher may tend to deviate from the subject of the article. In such a case, AI could prove very beneficial. By providing its capability for reasoning, AI would provide instant suggestions to the researcher through various pop-ups and correct the researcher if he is deviating from the subject. This would save time and would increase the quality of the article. There are various automatic citation and reference generators which have reduced the workload in writing citations. One such software is Cite u like. This is a free online service to organize your citations and resources. With this, you can now teach machines how to write and if in the future, the machines are capable of developing software on their own, the whole scenario of academic writing would change. You could order a robot to write an article on a particular subject and it would give you a very well-written article with very less or no need of correction. Thus overall, it can be said that AI and the tools being developed can vastly improve the writing of academic papers.

3. AI Tools for Enhancing Writing Skills

Writing is considered the most difficult skill among second language learners, and to many, the approach of “practice makes perfect” does not work, as writing in a non-native language can be a very daunting and demoralizing experience. This is where rhetorical and text planning tools can be used to guide and assist writers through the writing process. The CASTLE project researched using rhetorical structure theory to improve ESL writing. It was found that when students were taught to use RST to plan compositions, their writing was of better quality compared to those who were taught traditional methods. However, the teaching method was not very effective. An automated tool to teach RST can be more effective, as encapsulated knowledge can be used to simulate expert performance. Data can be taken from studies of expert writers using think-aloud protocol. An example of a text planning tool is R-WISE, which is designed to guide students through writing a school report within a writing framework specific to the task. This is also related to recent work in genre analysis and systemic functional linguistics, which has produced genre-specific pedagogical materials to improve student writing. AI technology can be used to deliver these materials in an interactive manner and also to develop adaptive systems that tailor tasks and instruction to the needs of the individual learner.

Finally, there have been recent advancements in feedback provision through the automatic generation of multimedia content. The kReSt project creates interactive feedback on student writing through hypermedia annotations and links to learning resources. This is an interesting and engaging way to present feedback to the user; however, the cost of authoring such material is high.

Another approach to providing corrective feedback is through the use of Intelligent Tutoring Systems. The TERRIER project used a dialogue-based tutoring system to guide students through the process of writing a comparison essay. This was done through a typed interface between the user and the system. We can employ a similar method using a chatbot-like interface to simulate a conversation between a user and a software agent, avoiding the costs and time associated with human tutors. An example of a dialogue system can be seen, which is an online Chinese grammar checker and instruction tool. This is a sophisticated approach to providing feedback and can also help with task-specific writing instruction.

One of the best ways to enhance writing is through language presentation. Automated feedback can be done through completion exercises. Implementing language presentation, practiced in the “form focused instruction” approach recommended by many SLA researchers, can be facilitated through automatic writing programs. Such programs can identify and highlight sentences that contain specific linguistic features, thus directing students to compare their own writing to correct instances and provide hints, tips, and feedback on a particular feature. Tools like WritePoint use simple rule-based systems to check for errors. These tools are not very effective as they do not take into account the context of the composition. This would be best done through a semantic parser that checks whether a sentence has been constructed correctly in terms of meaning. An example of this can be seen where text is analyzed and a “meaning” is generated to be displayed to the user. This tool is primarily designed for converting text to speech, but the same technology can be used to generate a meaning-based correction tool for writers.

4. Ethical Considerations in AI Writing Assistance

Provide context-sensitive advice. For instance, vocabulary that a linguistics student would learn in an introductory language course is something that students do not want AI software to call incorrect. An AI system was coded with the common usage of today’s American college students in mind. Because that population represents only a tiny subset of people learning English, our system cannot be readily improved to serve the needs of all these different groups. Devising effective methods for limiting and specifying the scope of AI advice will be necessary to keep it from interfering with ELL and L2 learners.

Recognize and respect disciplinary standards. Students, instructors, and AI developers must keep up to date on norms and expectations in writing and research within specific disciplines so that the AI tools reflect and teach them accurately. AI developers should collaborate with writing center experts and writing-across-the-curriculum initiatives to situate AI development within effective pedagogies for learning scholastic writing.

5. Conclusion

In conclusion, academic writing has always been a problem in the educational arena. It is time-consuming and students and professionals often make lots of errors. It contains many ambiguities and, truthfully, the work may not deliver what it should. By automating it with artificial intelligence, we can help the writer by pointing out any possible errors that may cause misinterpretation in the writing. This categorization is still in the early stage of our future goal, which is not only providing error checking but also a solution to overcome it. With more development in this field, we hope it could minimize the ambiguity in writing and provide a better tool for academic writing. This method could also be implemented in any other formal writing, as the rules are universal. Lastly, by making this tool web-based, it could help writers at a distance. Imagine a teacher or student receiving error suggestions while checking their document using another PC. This tool would be very helpful.