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THE IMPACT OF AI TOOLS ON LANGUAGE LEARNING AND CREATIVE OUTPUT
AMONG UNIVERSITY STUDENTS
Shikina Anastasiya Aleksandrovna
Master’s degree student, Department of English Practical Course, Fergana State University
E-mail:
https://doi.org/10.5281/zenodo.15666404
Abstract.
This study explores the impact of AI tools on language learning and creativity
among university students in Uzbekistan, focusing on their use of platforms like ChatGPT and
Deepseek. Using a mixed-methods approach, findings reveal high levels of AI usage for
academic tasks, with students commonly integrating AI support to enhance understanding and
writing. While many reported improved efficiency and idea generation, concerns about
dependency, reduced motivation, and diminished creativity were also prevalent. The results
align with existing literature, emphasizing both the benefits and risks of AI in EFL education.
Pedagogical strategies must balance AI support with critical thinking and creativity
development.
Keywords:
AI in education, creativity, language learning, EFL, ChatGPT, academic
writing, student autonomy.
ВЛИЯНИЕ ИНСТРУМЕНТОВ ИИ НА ИЗУЧЕНИЕ ЯЗЫКА И ТВОРЧЕСКИЙ
РЕЗУЛЬТАТ СРЕДИ СТУДЕНТОВ УНИВЕРСИТЕТОВ
Аннотация.
В этом исследовании изучается влияние инструментов ИИ на
изучение языка и творческий результат среди студентов университетов в Узбекистане,
уделяя особое внимание использованию ими таких платформ, как ChatGPT и Deepseek.
Используя смешанный подход, результаты показывают высокий уровень использования
ИИ для выполнения академических задач, при этом студенты обычно интегрируют
поддержку ИИ для улучшения понимания и письма. Хотя многие сообщали об улучшении
эффективности и генерации идей, также были распространены опасения по поводу
зависимости, снижения мотивации и снижения креативности. Результаты согласуются
с существующей литературой, подчеркивая как преимущества, так и риски ИИ в
образовании EFL. Педагогические стратегии должны уравновешивать поддержку ИИ с
критическим мышлением и развитием креативности.
Ключевые слова:
ИИ в образовании, креативность, изучение языка, EFL, ChatGPT,
академическое письмо, студенческая автономия.
Introduction
The rapid integration of Artificial Intelligence (AI) tools in education has sparked
ongoing debates about their impact on language learning and creativity, particularly among
university students in EFL contexts. With tools such as ChatGPT and Deepseek becoming
increasingly accessible, students now have novel means to enhance their academic writing,
comprehension, and problem-solving. This study aims to investigate how university students in
Uzbekistan perceive and use AI tools in their academic practices, with a particular focus on their
influence on independent thinking, creative output, and learning strategies. By comparing
student-reported data with established literature, the study provides insights into the nuanced and
multifaceted effects of AI on higher education learning environments.
Literature review
The integration of AI tools such as ChatGPT and AI-enhanced writing platforms is
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reshaping language learning and creativity among university students, offering both substantial
benefits and noteworthy challenges. According to Alzubi, Nazim, and Alyami (2025), students
recognize the creative potential of AI tools in English as a Foreign Language (EFL) settings,
especially in inspiring writing, providing instant feedback, and simulating real-life scenarios (pp.
17–20). However, their study also identifies key concerns, including overreliance on AI, reduced
originality, and diminished critical thinking skills. Gender, specialization, and academic level
were found to influence student perceptions, underlining the need for contextualized
implementation strategies. Educators are urged to adopt a balanced approach that supports
creative engagement while minimizing dependency and ensuring the development of higher-
order cognitive skills.
Zhao’s (2025) research further demonstrates the transformative potential of AI-driven
Natural Language Processing (NLP) tools in improving writing proficiency. Through a pretest-
posttest experimental design, students using AI-enhanced tools exhibited greater progress in
grammar accuracy, vocabulary use, and creative expression compared to control groups (pp.
8059–8065). The AI tools facilitated not only mechanical improvements but also content
structuring and idea generation, which align with constructivist and cognitive learning theories.
This suggests that AI can act as a cognitive extension, promoting skill acquisition and fostering
learner autonomy. However, Zhao also highlights the importance of pedagogical frameworks
that embed AI meaningfully in curriculum design, reinforcing the value of personalization and
interaction for sustained creative output.
Teacher perspectives, such as those explored by Pham and Le (2024), provide essential
insights into how AI affects creativity in EFL classrooms. While many teachers appreciated AI’s
support in creative engagement and student autonomy, they also expressed apprehension about
its potential to undermine traditional teaching methods and limit authentic thinking. Their
findings align with Lin and Chen’s (2024) study, which underscores a dual-edged impact: while
AI applications can stimulate creativity through gamification and personalized feedback, they
may also restrict originality due to their formulaic structures and induce performance anxiety
from constant evaluation. Both studies emphasize the emotional and cognitive dimensions of
learning, suggesting that AI’s design and usage should be carefully aligned with pedagogical
goals to preserve and enhance student creativity.
Methodology
Research design
This study employed a mixed-methods approach, combining quantitative data collection
through multiple-choice survey questions with qualitative insights from open-ended responses.
The purpose was to explore the role of AI tools in students’ academic practices, particularly
focusing on how these tools influence problem-solving skills and creativity in the context of
language learning and student projects.
Participants demographic
The dataset presents demographic information of 36 participants categorized by gender
and age range. Of the total respondents, 24 were female and 12 were male. The largest age group
was 21–23, comprising 19 individuals (11 females and 8 males), representing over half the
sample. The second most represented group was 16–20 with 9 participants (7 females and 2
males). The 24–26 age group had 5 participants (3 females and 2 males), followed by the 27+
group with only 2 female respondents. The least represented category was under 16, with a
single female respondent. Overall, the data indicates a predominantly female sample (two-thirds)
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and a youthful participant pool, with the majority aged between 16 and 23 years. All of them are
from Uzbekistan, with at least 1 person as a representative from one region.
Table 1 Participant Demographics by Gender and Age
What is your gender?
female
male
Total
Choose your age range
16-20
7
2
9
27+
2
0
2
21-23
11
8
19
under 16
1
0
1
24-26
3
2
5
Total
24
12
36
Academic background of the participants
This dataset outlines the academic backgrounds of 36 participants, revealing a highly
diverse range of majors with a dominant focus on English and language-related fields. A
significant portion of respondents reported majors directly connected to English studies,
including "English Philology" (mentioned three times under varying spellings), "Linguistics" (2),
"English Linguistics" (2), "Teaching EFL" (1), "TESOL" (1), "English Language Teaching" (2),
"Philology and Teaching Languages English" (1), "Philology and Teaching Language" (1),
"Language Teaching, English Specifically" (1), and "English Philology and Teaching" (1),
among others. Altogether, at least 20 out of 36 (55.5%) participants are engaged in English-
related or philology/language education programs. The rest are spread across fields such as
Engineering (2), Computer Science (1), IT and Telecommunication (1), Data Science (1),
Economics (1), Business (1), Law (1), Audit (1), and History (3). Additionally, one participant
identified as still attending school, and another simply answered "University." Despite varied
wording and possible spelling inconsistencies, the data shows that a strong majority of
respondents come from language-oriented disciplines.
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Figure 1 Participants' Academic Majors
Data collection instruments
Data was collected through an anonymous online questionnaire consisting of both closed-
and open-ended questions. The survey included Likert-scale items, multiple-choice questions,
and reflective prompts designed to assess students' frequency of AI usage, typical strategies for
academic problem-solving, attitudes toward AI, and perceived impacts on skills like creativity,
motivation, and independent thinking.
Procedure
Participants were recruited via academic networks and social media platforms affiliated
with higher education institutions in Uzbekistan. Informed consent was obtained, and
participants were assured of confidentiality and voluntary participation. The questionnaire was
administered in English and took approximately 10–15 minutes to complete.
Data analysis
Quantitative responses were analyzed using descriptive statistics to determine usage
patterns and preference frequencies, presented in tables and figures. Qualitative data from open-
ended responses were thematically analyzed to identify common perceptions regarding the
benefits and drawbacks of AI tools in academic contexts. Coding focused on themes such as
creativity, autonomy, dependency, efficiency, and problem-solving ability.
Results
This dataset explores how frequently students use AI tools for academic tasks and their
initial approach when encountering study challenges. Out of 36 respondents, 20 reported
"Always" using AI tools like ChatGPT or Deepseek, 11 use them "Often (almost daily)," 4 use
them "Sometimes (a few times a week)," and only 1 uses them "Rarely (a few times a month),"
indicating that 86% of participants rely on AI tools frequently or always. When faced with a
difficult academic problem, 16 participants reported turning first to AI tools—11 of them always
and 5 often—making it the most common initial strategy. Another 16 students preferred to
attempt solving the problem independently using prior knowledge, showing a balanced trend
between self-reliance and AI assistance. A smaller number turned first to peers or teachers (2
total) or consulted textbooks and online resources (2 total). The data highlights a strong
integration of AI tools into students’ academic routines, with AI becoming a primary resource
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for problem-solving, especially among frequent users.
Table 2 Use of AI Tools in Academic Problem-Solving
How often do you use AI tools (e.g., ChatGPT,
Deepseek) to help with your homework or
assignments?
Often
(almost
daily)
Always
Sometimes
(a few times
a week)
Rarely
(a
few
times a
month)
Total
When faced with a
challenging
problem in your
studies, which of
the following do
you
usually
do
FIRST?
Ask an AI tool
for a solution
5
11
0
0
16
Try to solve it
on my own
using previous
knowledge
6
7
2
1
16
Ask a teacher
or
classmate
for help
0
1
1
0
2
Look
up
information in
textbooks
or
online
resources
0
1
1
0
2
Total
11
20
4
1
36
This dataset on Table shows how 36 students typically use AI tools for academic
assignments. The majority adopt a constructive or integrative approach: 14 students (38.89%)
use AI-generated answers as a starting point to build their own solutions, and another 14
(38.89%) use AI to understand the concepts before independently solving the problems.
Together, these thoughtful strategies account for 77.78% of responses, indicating a dominant
trend of using AI as a learning aid rather than a shortcut. In contrast, 7 students (19.44%)
admitted to copying AI answers directly, reflecting a less active learning approach. Only 1
respondent (2.78%) reported avoiding AI altogether in favor of solving problems independently.
Overall, while most students engage with AI tools in a pedagogically beneficial way, a minority
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still rely heavily on direct copying or avoid AI entirely.
Figure 2 Student Approaches to Using AI in Assignments
This dataset captures 36 participants' personal reflections on how relying on AI tools has
influenced their ability to solve problems independently. The majority express concern about a
negative impact, with many noting increased laziness, dependency, and a decline in creativity
and independent thinking—e.g., “I feel that I am too lazy now,” “It kills my creativity,” and “I
became a bit lazy because of AI.” Several responses emphasize a 50/50 or situational effect,
acknowledging both benefits and drawbacks, such as boosting efficiency or creativity while also
fostering dependence. A smaller number of participants described neutral or positive effects,
stating that AI helps with understanding, saves time, or is used sparingly to enhance their work.
While a few students find AI supportive in moderation, most responses reflect a critical
awareness of overreliance on AI tools and the resulting reduction in cognitive effort and self-
reliance.
A significant number of respondents use AI regularly for academic tasks, such as
completing assignments, writing code, translating texts, or researching unfamiliar topics. For
example, several mentioned using AI to write essays, generate case studies, or assist in scientific
writing, with outcomes generally described as successful or helpful. Some users shared specific
experiences, like using AI for calculus problems (with mixed success), preparing math
homework, or generating presentations. Others noted customizing AI-generated content to fit
personal needs, such as simplifying vocabulary. A few responses highlighted critical reflections,
noting that AI can produce content that sounds "robotic" or lacks emotional nuance.
A wide range of responses was shared, with creativity emerging as the most frequently
mentioned skill (at least 10 mentions), followed by motivation, autonomy, critical thinking, and
decision-making. Several participants highlighted that AI negatively impacts creativity and
independent thinking, often causing users to become lazy, less motivated, or overly reliant on
automated solutions. Others offered more nuanced perspectives, stating that AI can enhance
efficiency, support brainstorming, and provide useful data, but only when used appropriately and
with critical oversight. A few respondents pointed out that the balance between AI support and
human cognitive effort is crucial, and that AI's effectiveness depends heavily on how users
engage with it. Overall, while the majority recognized creativity, motivation, and thinking skills
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as central to problem-solving, opinions on AI’s role were mixed, emphasizing both its potential
benefits and risks of dependency.
Discussion
The findings of this study closely mirror the existing literature, reinforcing the dual-edged
impact of AI tools on student creativity and autonomy. As Alzubi, Nazim, and Alyami (2025)
highlight, while students acknowledge AI’s value in generating ideas and simulating real-life
scenarios, they also express concern about becoming overly dependent on such technologies (pp.
17–20). This tension was clearly reflected in the participant responses: although 86% of students
reported frequent or constant use of AI tools, a significant portion admitted that this reliance
negatively affected their creativity and self-motivation. For example, participants described
feeling “lazy” or “less creative” due to overuse, which aligns with Lin and Chen’s (2024)
observation that AI may constrain creative thinking and lead to emotional disengagement when
overused. However, the fact that over 77% of students used AI in an integrative manner—either
to build on ideas or to understand concepts—demonstrates that these tools are also facilitating
constructive cognitive engagement when used thoughtfully.
This balance between benefit and dependency is consistent with Zhao’s (2025)
experimental findings, which showed that students who received targeted AI support
demonstrated improved writing proficiency, especially in grammar and idea development (pp.
8059–8065). Similarly, students in this study reported using AI for a range of academic tasks—
from essay writing to generating presentations and coding—which indicates that AI tools are not
only supporting language acquisition but also enhancing broader academic productivity.
However, the qualitative reflections also echoed Zhao’s concern about the need for pedagogical
frameworks to ensure meaningful engagement. Students emphasized that AI output often lacked
emotional nuance or felt "robotic," suggesting the necessity of human oversight to preserve
authenticity and creativity in student work. These parallels between the literature and student
data emphasize that while AI tools can nurture creative growth, their impact is highly contingent
on user intent, training, and moderation in use.
Conclusion
The integration of AI tools into university-level language learning environments offers
both transformative opportunities and significant pedagogical challenges. The results of this
study underscore that while students benefit from enhanced efficiency, idea generation, and
support in academic writing, they are also at risk of becoming overly reliant on AI, potentially
hindering creativity and independent thinking. These findings echo broader academic discourse
and highlight the urgent need for educators to implement balanced, critical, and pedagogically
grounded strategies for AI use. Future research should adopt longitudinal and experimental
designs to further explore the long-term cognitive and emotional impacts of AI on learners,
ensuring that its use ultimately supports—not substitutes—the human dimensions of creativity
and language learning.
REFERENCES
1.
Alzubi, A. A. F., Nazim, M., & Alyami, N. (2025). Do AI-generative tools kill or nurture
creativity in EFL teaching and learning?. Education and Information Technologies, 1-38.
2.
Lin, H., & Chen, Q. (2024). Artificial intelligence (AI)-integrated educational
applications and college students’ creativity and academic emotions: students and
teachers’ perceptions and attitudes. BMC psychology, 12(1), 487.
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3.
Pham, T. T., & Le, T. T. (2024). Exploring the Impact of Artificial Intelligence on
Student Creativity in Vietnamese Tertiary EFL Classrooms: Teacher Perspectives. Jurnal
Komunikasi Pendidikan, 8(2), 116-128.
4.
Zhao, D. (2025). The impact of AI-enhanced natural language processing tools on writing
proficiency: An analysis of language precision, content summarization, and creative
writing facilitation. Education and Information Technologies, 30(6), 8055-8086.
