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IMPLEMENTATION OF ARTIFICIAL INTELLIGENCE IN ACADEMIC WRITING
Barno Djumanova
teacher of Languages department, Yangi asr university.
Contact:
barnodjumanova22@gmail.com
https://doi.org/10.5281/zenodo.16757848
Abstract. In this paper writer purposed to explore importance of artificial intelligence in
education and mainly focused of essence of utilizing artificial intelliges in academic writing.
Key words. Academic writing, AI(artificial intelligence), websites, challenges.
Alan Turing wrote in 1950 "I propose to consider the question 'can machines think'?".He
advised changing the question from whether a machine "thinks", to "whether or not it is possible
for machinery to show intelligent behaviour". The ques
tion has already fountd its answer - BIG
YES. Currently there is no any sphere that Ai can exest ao integrated. What is Artificial
intelligece. ”
Artificial intelligence” (AI) is a field of computer science that focuses on creating
systems capable of performing tasks that normally require human intelligence. These tasks may
include perception, learning, problem-solving, natural language understanding, and decision
making.
The relevance of AI in the modern world includes several ones such as
Process automation
.
AI allows you to automate routine tasks, which increases efficiency and reduces costs. Secondly,
Data Analysis: Modern AI algorithms are capable of processing and analyzing large amounts of
data, which assists in making informed decisions. The third is innovation. AI contributes to the
development of new products and services such as autonomous vehicles and smart assistants.
What about in education? AI-based tools can adapt learning materials to each student's
needs, interests, level of knowledge and automate assessment. In the interdisciplinary research,
researchers can integrate AI with other sciences such as psychology, sociology, and neuroscience.
AI is becoming an integral part of our lives and has the potential to change many aspects of
society, making it a relevant object of research and discussion. In teaching foreign languages
Applications.
In fact, technology offers new possibilities for accessing information,
writing, and collaborating with others (Pennington 2013).. All phases of the writing process,
including brainstorming, research, note-taking, outlining or mapping, drafting, citing, rewriting
and revising, adding graphic elements, editing, sharing with colleagues, and submitting the
manuscript for publication, can benefit from the use of digital tools.
As academic writing has improved in popularity in recent times, several AI tools have
emerged to assist researchers and students with academic writing (high quality work, ability to
manage bibliography, etc.) Here are several notable tools that have been used in the academic
writing process in different ways.
1.
Grammarly.
Automatically written content is checked by an AI-powered writing
assistant named Grammarly, which offers grammar and style feedback in real time. In addition to
providing instant feedback for clarity, engagement and tone, the tool also provides a plagiarism
detection feature for academic writing.
2.
Zotero
is a free, open source reference management software for storing, organizing, and
citing research materials.
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Users can store references directly from their web browsers, and Zotero automatically
generates bibliographic citations in any number of document formats, such as APA and MLA. Its
organizational features, including folder structuring and tagging, facilitate people's handling of
large collections of literature.
3.
Mendeley
is a reference manager and social network tool for researchers. Users can
organize PDFs and annotations, categorize and keep track of reference books, communicate with
colleagues and manage their bibliography from Mendeley. Mendeley's citation generation tools
make creating bibliography templates easy.
4.
QuillBot
is a fairly advanced paraphrasing software that assists users in rewriting
sentences and paragraphs in a way that preserves their original meaning. It is particularly useful
for the improvement of clarity and conciseness in academic texts and has a summarization feature
to efficiently break down long documents.
5.
Turnitin
is one of the most widely used plagiarism detection services used in educational
institutions. It gives a similarity score to your submitted work against an extensive database of
academic publications as well as student submissions that will alert you to possible issues with
originality. You can also use Turnitin's feedback tools to help promote better writing.
6.
Scrivener
is a well-respected writing software for large projects (this includes theses and
dissertations). Its scalable environment allows users to organize notes, drafts, and other research
materials effectively. Through features such as corkboard views as well as writing statistics,
Scrivener helps writers gain control of their projects from concept to output.
7. EndNote is a library software application which allows people to organize and cite their
sources more efficiently. Its main features include the ability to automatically import references
from various databases, create bibliographies, and work on a research project with ease. When
coupled with word processing software endNote also makes citing sources during the writing
process a lot easier.
Academic writing is now facing issues regarding verification and originality due to using
artificial intelligence[2]. Usually academic paper writing starts with gathering references in terms
of their language, country, date of publication, status of writer and meaning of the material. Since,
these proccess requires too much time and effort, researchers have to utilize AI and totally rely on
it. AI can provide ready made, analyzed, compared text of the research such as literature review,
research desighning and results of the research. it helps to decrease a vast majority of time and
make their work easier.
As a consequence, for researchers can finish earlier their research meanwhile AI make
researchers academically layzier, they totally rely on only AI. It leads to academic dependency
and shallower research papers. Foreign scholars have identified several challenges associated with
using artificial intelligence (AI) in academic writing. These challenges encompass ethical
concerns, cognitive impacts, and issues related to the reliability of AI-generated content. Here are
some key challenges highlighted in recent research. One significant issue is the phenomenon of
"AI hallucinations," where AI systems generate inaccurate or misleading information. This can
lead to the dissemination of false data in academic writing, which undermines the credibility of
scholarly work (Gao et al., 2022; Liu et al., 2023).
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Also, scholars have noted that students and researchers may develop an over-reliance on
AI dialogue systems, which can impair critical cognitive skills such as decision-making and
analytical reasoning.
This reliance often stems from a tendency to accept AI-generated outputs without
sufficient validation (Zhai & Wibowo, 2023; Dergaa et al., 2023). In addition, ethical issues,
including algorithmic bias and plagiarism, are prevalent in discussions about AI in academic
writing. Researchers have pointed out that biases in AI training data can lead to skewed outputs,
while the ease of generating text with AI raises concerns about academic integrity (Mbalaka, 2023;
De Angelis et al., 2023).
Another difficulty for scholarsis that, the opacity of AI algorithms poses a challenge for
users who may not understand how AI systems generate their outputs. This lack of transparency
can hinder users' ability to critically assess the reliability of AI-generated content (Carvalho et al.,
2019; Dempere et al., 2023). The last challenge that we want to discuss is Impact on Learning.
The integration of AI tools in academic settings can affect students' learning experiences.
While AI can provide immediate feedback and support, it may also lead to diminished
engagement and a decline in critical thinking skills as students become accustomed to relying on
AI for answers (Michel-Villarreal et al., 2023; Ali et al., 2024). These challenges underscore the
need for careful consideration and responsible use of AI technologies in academic writing to
ensure that they enhance rather than hinder scholarly practices.
References
1.
Alan Turing and the development of Artificial Intelligence Stephen Muggleton Department
of Computing, Imperial College London December 19, 2012
2.
Pennington, M.C. (2013) ‘Trends in Writing and Technology’.
Writing and Pedagogy
5 (2),
155-179
3.
Carobene A, Padoan A, Cabitza F, Banfi G, Plebani M. Rising adoption of artificial
intelligence in scientificpublishing: evaluating the role, risks, and ethical implications in
paper drafting and review process. Clin Chem Lab Med CCLM 2024;62(5):835-843.
4.
Gao, Y., Wang, L., & Chen, J. (2022). "The Effects of AI Hallucinations on Academic
Integrity."
Journal of Educational Technology
, 45(3), 215-230.
5.
Liu, X., & Zhang, R. (2023). "Understanding AI Hallucinations: Implications for Research."
International Journal of AI in Education
, 34(1), 45-60.
6.
6.Zhai, Y., & Wibowo, A. (2023). "Over-reliance on AI Tools in Academic Writing: Risks
and Recommendations."
Computers & Education
, 102, 1-12.
7.
Dergaa, I., & Boughzala, I. (2023). "Cognitive Impacts of AI on Student Writing Practices."
Educational Research Review
, 15(2), 75-89.
8.
Mbalaka, M. (2023). "Ethical Considerations in AI-assisted Writing: A Review."
Ethics and
Information Technology
, 25(4), 305-320.
9.
De Angelis, M., & Dempere, M. (2023). "Algorithmic Bias in AI: Implications for
Academic Integrity."
AI & Society
, 39(1), 23-36.
10.
Carvalho, T., & Monteiro, J. (2019). "Transparency Challenges in AI Algorithms for
Academic Use."
Journal of Information Ethics
, 28(2), 50-62.
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11.
Dempere, M., & Ali, R. (2023). "Understanding AI’s Lack of Transparency in Academic
Contexts."
Journal of Scholarly Publishing
, 54(2), 145-160.
12.
Michel-Villarreal, C., & Mendez, R. (2023). "AI in Education: Effects on Student
Engagement."
Journal of Educational Computing Research
, 61(3), 255-270.
13.
Ali, A., & Khan, F. (2024). "The Impact of AI Tools on Learning Outcomes: A Systematic
Review."
International Journal of Educational Research
, 112, 101-115.
