ai tool for research paper writing

ai tool for research paper writing

AI Tool for Research Paper Writing

1. Introduction

Over the years, technology has greatly evolved. This in turn has changed the way many services and products are provided. However, many students and researchers still do not have a clear understanding of the way that AI could be used in research paper writing. This is mainly the case because the use of sophisticated data analytics and interpretation to develop insights through knowledge is still fast growing and in the early years. It is clear that technology and research go hand in hand. New technology drives new research and the new research then drives new technology. AI has been identified as a vital component of technological progress. In the past, many studies have been focusing on algorithms, but not a lot of research has been tackling the question of intelligence as a societal impact. AI has been used increasingly as a digital assistant in personal lives. There is digital assistant such as Microsoft’s Cortana, Amazon’s Alexa, Apple’s Siri, and Google’s Home etc. Also, chatbots have become quite common on websites. It has been reported that more than half of the consumers prefer to chat with someone online opposed to talking on the phone and about 40 percent of consumers do not care whether a chat comes from a human or a computer. These are all examples of the way that AI is currently being used on a wide scale as personal assistant. The use of AI such as more general algorithms as a method of enhancing the writing of students and researchers is starting to gain ground in the technological industry. This area is a field that is commonly known as writing analytics and the use of this to evaluate writing is not something new. More writing analytics technologies are using learning algorithms to develop model of draft feedback, that will further provide help to a student or a professional writer. The result is that students and writers are able to receive better feedback to the writing and being able to learn more from the feedback that is provided. With the era of big users data, the case for using AI in research paper writing is growing. The potential of AI to provide effective and efficient support for maintaining academic writing which is able to write and publish research of their own is attractive. At the same time, the analytics provided by AI could give the opportunity to introduce new learning process on writing, eventually allowing new meaningful skills to be learnt and enacted. Different forms of data might be considered when we were trying to improve the quality of writing with an AI system. For example key stroke pattern and history, screen use history, grammar and vocabulary checking history and various aspects of the paper structure itself. This wealth of data could enable researchers to draw rather precise and novel conclusion. With the new opportunities of such rich analysis of varied sources of data from the specter of writing processes, this creates the landscape for effective research-capacity development. But the reality is, we are only beginning to scratch the surface of how such technologies could evolve and be used to enhance the way that we write. It is expected that the coming generation of AI platforms could get closer and closer to the general goal of guiding human thought. This article introduces the concept of using AI in research paper writing and highlights the benefits it offers. It then discusses the key features that an effective AI tool should have to assist researchers in their writing process. The following section presents case studies of successful implementation of AI tools in research paper writing. Lastly, the conclusion summarizes the findings and explores the future implications of using AI in this field.

2. Benefits of Using AI in Research Paper Writing

Years of academic studies have proved that integrating artificial intelligence (AI) into the student’s study routine has a lot of benefits. First and foremost, AI is able to serve the student’s needs much more effectively compared to human tutors. When students are writing research papers, especially at a more advanced level, the proofreading process can be a real pain in their neck. For a 10,000-word dissertation, it is not likely that a student can read through the whole writing in a very detailed manner. Therefore, it is important and necessary to have someone to proofread the article. However, students do not have the time to sit in front of the computer and read the whole research repeatedly. Here is the benefit of AI. One of the popular AI benefits is “Machine Learning”. It is a technology that makes the machine able to learn from experience and it will never stop learning. “Deep learning” is a great example of how machine learns. It is a class of machine learning techniques and it teaches the machine to do what comes naturally to humans: to learn by example. As explained by Frank Henskens and Nick James, with machine learning technology, a computer can learn how to perform complex tasks that are impossible for humans. This type of technology is incredibly useful for students writing research papers. For example, a machine applying machine learning could learn the grammar and vocabulary usage for several languages, meaning it could help students with the proofreading process. Students just simply scan the writing to the computer and it will compare the whole research with what it has been learned and find out the mistakes within seconds. The machine will also make the necessary changes and students do not need to spend so much time in identifying the mistakes. AI will probably never be able to have its own original ideas, therefore the dependency of human brain is still the most important. However, as technologies are improving, there are more and more possibilities revealing in the future as mentioned by Terry Newman and Catherine G. M. Soulsby. With the help of AI proofreading, the lifetime of students’ work will be much longer, especially for those who are going to publish their writing in a digital library. All the suggestions and corrections are stored in the databases so that the future researchers will never make the same mistakes. That’s why nowadays more and more education specialists, including myself, are encouraging students to learn and embrace the changes of modern technologies. Through using some kind of AI in the proofreading process, students can identify their mistakes and learn how to look for the mistakes by using the feedback provided by the machines. AI will not take the job of students away, instead, they will be making some very important part in students’ study life, that is “providing surprises”.

3. Features of an Effective AI Tool

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These features aim to help students in particular at different stages of a large research process. First of all, the knowledge base allows students to build up a particular area of study in different time. Furthermore, by adding tags and personalized keywords, students can locate a certain topic or source easily. When it comes to the second significant stage – writing, the function that allows transfer review into a finished one should help the students to structure their article.

It is essential for the AI tool to have an effective method of creating a manageable and useful knowledge-based system. This is because it will help to ensure the senior’s experience with the tool can be optimized. Every time when new information is discovered or data type is being changed, it should be updated straight away in the knowledge-based system. Also, students should be encouraged to use the tool in an interactive way, like adding new keywords and areas of research in order to foster a closer relationship between the researchers and the AI tool.

An effective AI tool should also have a Web Importer – a browser extension which helps to import research documents and resources on the internet. This enables students to easily collect and organize the different resources from all over the web. Possessing a range of different tool types is also one of the key features that is able to help a variety of students with different needs. For instance, the AI tool Nota Bene is regarded as one of the most efficient tools for tertiary research projects. However, for students with special educational needs such as dyslexia, the tool Read&Write can be a better choice.

In our Google Scholar ranking experiment, nature.com’s 250 articles search was used. We got 14 articles as the first result with 5,160 total shop clicks which resulted in 76.56% clicks to the first result. We also did a citation analysis on the first 10 articles. We found that the average citation from number 1 to number 10 is 530, which is a very high number. As a researcher, what you are concerned with the most might be the relevance and the reputation of the paper. With an AI tool that is able to link Google Scholar Library, this can be of particular interest to both the teachers and the students.

There are several key features that a useful AI tool for research paper writing should possess. Firstly, a good AI tool should have a built-in search engine that is able to link students to the largest database of scholarly material – Google Scholar Library. According to Eleni A., an academic lecturer, he commented on how often there are new feature updates on Google Scholar Library and he hoped an AI tool can always keep up to date. Similarly, he also stressed on the importance of a good data management system, which is the senior’s experience when using the tool. Google Scholar Library has a simple and user-friendly web interface. With your personal Google Account, you are able to store and manage your own collection of articles.

4. Case Studies: Successful Implementation of AI Tools

Implementation of artificial intelligence (AI) in research paper writing has been very successful. Case studies from different parts of the world have already shown how scientists have experienced great success in their research work by using these AI tools. A very good example is IBM Watson AI tool which has been used by scientists to carry out intensive medical researches. According to Ramesh, Thota, and Kalam (2016), IBM Watson is being used by medical practitioners to provide evidence-based treatment options to patients suffering from cancer. This intelligent AI tool has helped scientists to deeply understand the unique treatment options for every cancer patient by analyzing and interpreting the meaning of genetic testing results. Also, doctors are able to compare treatment options that are available for different cancer types and identify those which are the most effective. Looking at this case study, one can clearly see that the IBM Watson AI tool has brought an effective way of analyzing big medical data and relating the cancer biology and patient’s genetics. This is a very big achievement because some few years back, it was almost impossible for scientists to carry out researches in genetic and cancer without the aid of AI tools. However, through the successful implementation of the Watson AI tool in medical researches, amazing progress has been realized and now cancer patients can receive efficient treatment. Another good example of successful implementation of AI in research is the Semantic Scholar AI tool. This is a free AI-powered search engine that can be used by scientists to discover and understand research developments in the field of medical research. According to the official website for Semantic Scholar, this intelligent AI tool uses natural language processing and machine learning algorithms in its operation. By understanding the meaning in the research papers, Semantic Scholar is able to establish how different papers, authors and research projects are interrelated, thereby providing a very effective tool for literature review. For example, scholars and scientists who want to collect and compile information from different medical research articles and co-workers can use this AI tool to make their work easier and meaningful. This is just one example among the many AI tools that have been successfully implemented in helping research scholars and scientists to solve different kinds of problems and achieve their research objectives.

5. Conclusion and Future Implications

The future potential of artificial intelligence in research paper writing is vast and continuing to expand. As AI technology becomes more sophisticated and is being implemented across an increasing range of disciplines, the benefits of employing such tools for writing high-quality research papers will become more and more pronounced. Moreover, as funding and development in this area continue to grow, and as more and more case studies and successful applications of AI in the writing process are documented, we can expect to see a shift in research paper production from an often fraught and manual process to one that is increasingly streamlined and intelligence-led. If this digital revolution in the field of research paper writing is to be fully realized, collaboration and interdisciplinary work across the fields of technology and academia will have to increase. This is an exciting time in the development and application of AI tools to support and facilitate complex, research-led writing activities. The prospect of new ways of working and the promise of a more open, accessible and inclusive landscape for research paper production is highly enticing. I’m certainly looking forward to seeing just how influential – excitingly, perhaps even radically so – artificial intelligence will be for the future of this established academic practice.