CAUSES OF STYLISTIC ERRORS IN STUDENTS’ SPEECH AND WAYS TO ELIMINATE THEM

O‘rinova Diyora

Master’s student, Namangan State Pedagogical Institute

Abstract

This article examines stylistic errors found in students’ oral and written speech, their underlying causes, and effective methods for eliminating them. The study employed content analysis, surveys, observation, experimental methods, focus group discussions, computational linguistic analysis, and psycholinguistic testing. The findings reveal that students frequently struggle with selecting appropriate speech styles according to text types. Based on the results, practical recommendations are proposed to improve students’ speech culture and stylistic competence.

Keywords: speech culture, stylistic errors, communication, language norms, educational process, statistical analysis, content analysis

INTRODUCTION

In modern education, developing students’ communication culture and ensuring stylistic accuracy in their speech has become one of the most pressing issues. In linguistics, stylistic errors are defined as the use of language units that are inappropriate for a given context or inconsistent with a particular speech style. Such errors negatively affect students’ speech culture, weakening their ability to express ideas clearly, engage in communication, and adhere to literary language norms.

Speech culture plays a crucial role not only in education but also in an individual’s social success. In the digital era, the rapid development of technology has introduced new tendencies in students’ speech. For example, abbreviations, emojis, and informal expressions commonly used in social media are increasingly transferred into formal written language, leading to stylistic distortions. This phenomenon can influence not only students’ academic writing but also their future professional communication.

Therefore, eliminating stylistic errors requires a comprehensive approach that considers not only grammatical but also pragmatic and discourse-related aspects. This article analyzes the main causes of stylistic errors in students’ speech and explores effective ways to address them.

LITERATURE REVIEW AND METHODOLOGY

Numerous scholars have conducted research in the field of speech culture. For instance, G‘afurov analyzed the theoretical aspects of speech culture, while Karimov systematized literary language styles. Qodirova provided practical examples of stylistic usage, and Xudoyberganova examined linguistic features from a psycholinguistic perspective. International researchers such as Smith, Ivanova, and Brown explored comparative, cognitive, and educational aspects of language norms. Recent studies by Yusupova, Petrov, Nurmatov, and Wilson highlight modern teaching methods and the impact of digital communication on speech.

The study was conducted among 100 students from grades 8–9 in Tashkent city and region. Their written works (essays, summaries) and oral responses were analyzed.

The following methods were used:

Content analysis: identifying and classifying stylistic errors

Survey: assessing students’ knowledge of speech styles

Observation: analyzing teaching approaches and classroom speech

Additional methods included:

1. Experimental Method

Two groups (control and experimental) were selected. A “Teaching Speech Styles” program was implemented in the experimental group for three months. As a result, students’ ability to choose appropriate styles improved by 35%.

2. Focus Group Discussions

Five groups (8 students each) discussed the influence of social media language. About 70% of participants preferred writing “as they do on Telegram.”

3. Computational Linguistics

Using the AntConc program, 100 essays were analyzed. Words such as “very” (143 times) and “amazing” (78 times) were overused, indicating excessive use of expressive vocabulary.

4. Psycholinguistic Testing

Only 31% of students correctly identified appropriate stylistic choices in academic contexts.

Additional statistical findings showed that errors in formal letters were distributed as follows:

Introduction – 23%

Main body – 41%

Conclusion – 36%

RESULTS

The analysis revealed the following common stylistic errors in students’ speech:

Mixing formal and informal styles – 43%

Using artistic expressions in scientific texts (and vice versa) – 29%

Pronunciation and stress-related stylistic distortions – 15%

Transfer of internet and colloquial language into writing – 13%

Although 67% of students demonstrated general knowledge of speech styles, only 21% understood the importance of selecting an appropriate style according to the text type.

DISCUSSION

The findings indicate that the main causes of stylistic errors include:

Insufficient theoretical knowledge of language styles

Transfer of informal speech into written language

Inability to distinguish between text types

Strong influence of internet and social media language

To address these issues, the following strategies are recommended:

Teaching speech styles through comparative practical exercises

Conducting text-based analysis and discussions

Developing exercises for appropriate stylistic selection

Ensuring teachers model correct speech usage

Limiting the use of informal internet language in academic contexts

One of the key reasons for stylistic errors is the lack of emphasis on stylistic aspects in textbooks and classroom instruction. Additionally, students’ exposure to informal digital communication significantly shapes their language habits. Therefore, teachers should dedicate more time to text analysis and encourage students to practice writing in various genres such as academic articles, formal letters, and essays.

CONCLUSION

Reducing stylistic errors and improving students’ speech culture requires systematic teaching of language styles in both theoretical and practical ways. This not only promotes adherence to literary language norms but also enhances students’ ability to communicate clearly, accurately, and effectively in social and professional contexts.

The following measures are recommended:

For teachers: organize seminars and training sessions on stylistics; expand textbook content

For students: engage in text analysis, speech exercises, and projects (e.g., “Correct Speech” clubs)

For parents: encourage reading and monitor children’s speech habits

For educational policy: develop national programs aimed at improving speech culture

O‘rinova Diyora Kamoliddin qizi was born on November 6, 1997, in Uchqo‘rg‘on district of Namangan region. She graduated from Secondary School No. 25 in her district and continued her studies at an academic lyceum. She obtained her higher education in the field of Uzbek Language at Namangan State University.

Currently, she is a second year master’s student at Namangan State Pedagogical Institute. She holds certificates in both native language and English and is recognized as a highly qualified teacher within her field. She is also the regional stage winner of the “Book-Loving Teacher” competition.

Her main goal is to share her knowledge with young learners and contribute to the development of future specialists through education and scientific activity.

Yunusova Robiyakhon Khayotbek qizi

Andijan State Technical Institute

1st-year student of Economics

E-mail: yunusovarobiya90@gmail.com

Development of Financial Technologies in the Context of the Digital Economy

Abstract: This article analyzes the development processes of financial technologies (FinTech) in the context of the digital economy, their impact on the financial system, and their importance in the economy. It also examines the development trends of digital payment systems, mobile banking services, blockchain technologies, and financial services based on artificial intelligence. The study highlights the role of financial technologies in increasing the efficiency of the banking system, improving service quality, and expanding financial inclusion. At the same time, the problems and prospects of FinTech development are also analyzed.

Keywords: Digital economy, financial technologies (FinTech), digital payment systems, blockchain technology, artificial intelligence, digital transformation.

Introduction

In today’s rapidly developing digital technologies, the global financial sector is undergoing unprecedented changes. Innovative technologies such as artificial intelligence, blockchain, and big data analytics are transforming traditional models of finance and banking into faster, more transparent, and more efficient systems. In particular, the widespread application of artificial intelligence algorithms in credit scoring, risk prediction, fraud prevention, investment analysis, and personalized customer services is enabling a fundamental transformation of the financial ecosystem [1].The digital financial ecosystem is undergoing major changes, mainly through the integration of machine learning technologies. Machine learning, with its ability to identify complex patterns from large datasets, has become a key factor in improving the efficiency and accuracy of financial services [2].

Main Part

With the development of digital technologies, banking and financial systems are experiencing significant transformations. Advanced technologies such as artificial intelligence (AI), blockchain, and big data analytics are expanding opportunities for automating financial operations, enhancing security, and providing personalized services to customers. The application of AI technologies in the global financial market is generating new innovations [1].

In recent years, the expansion of digital financial services (DFS) has not only increased financial accessibility but also created new opportunities from a taxation perspective. For example, according to an OECD report, more than 70% of tax authorities are working to increase tax revenues and reduce tax evasion through the use of artificial intelligence and analytical methods. Research conducted in Africa has also shown that DFS is a strong factor in expanding the tax base (for example, mobile money accounts are currently providing financial services to a large portion of the population). This situation is also important for Uzbekistan: through digital payments, e-commerce, and the introduction of fiscal systems, the economic activity of taxpayers and the tax base can become more transparent [3].

Like many developed countries, our country has chosen the path of developing the digital economy, which opens new directions in the field of information technologies and electronic document circulation. The shift of society towards digital technologies has been driven by improvements in the global internet network and the development of communication systems. As a result, opportunities have emerged for exchanging and collecting large volumes of data, which in turn enables data processing, forecasting, decision-making, and generating benefits in various ways.

For all this, it is necessary to create appropriate infrastructure, in other words, an ecosystem of global information platforms. However, this also creates risks such as data loss, business loss, job reduction, security threats, and the need for modernization. These issues must be addressed quickly, as delays may lead to serious risks [4].

The development of financial technologies plays an important role in global economic and social changes, as they provide more convenient and cost-effective solutions to meet the financial needs of society. Currently, financial technologies are the fastest-growing segment of the financial services market.

A number of studies have been conducted on the development of financial technologies. For example, Professor Patrick Schueffel of the Fribourg School of Management reviewed more than 200 scientific articles published over the past forty years and defined FinTech as “an emerging financial industry that uses technology to improve financial performance.”Professor Douglas W. Arner, one of the founders of the Hong Kong University Financial Law Center, and his colleagues define FinTech as “the improvement and development of financial services based on technological innovations.” Strategic management expert Hermann Simon defines financial technologies as “the process of adapting the traditional financial system to new, efficient, and secure forms of service through digital innovations.”

These definitions show that approaches to financial technologies are based on service convenience, innovation, and the value added by technology to the financial system [5].Financial technologies are important for technological development and economic stability and are one of the main driving forces of the digital revolution in the global economy. The main factors behind the emergence and rapid spread of FinTech include:growth in the quality and quantity of information technologies, the need for financial and non-financial companies to improve their activities, and changes in consumer behavior [5]

Conclusion

The rapid development of digital technologies is fundamentally transforming banking and financial systems, enabling the creation of automated, fast, and efficient services based on artificial intelligence. The study analyzed the implementation of AI technologies in Uzbekistan’s banking sector, their advantages, and existing challenges. The results show that the widespread adoption of AI technologies improves customer service quality, helps identify credit risks, prevents fraud, and increases operational efficiency.

At the same time, AI integration also creates challenges related to legal regulation, cybersecurity, and the development of technological infrastructure. There are prospects for the use of blockchain, generative AI, quantum computing, and embedded finance technologies in Uzbekistan’s banking system, and their effective implementation will contribute to increasing financial stability and competitiveness [1].

In conclusion, online lending platforms are becoming one of the key drivers of innovative and rapid digital transformation in Uzbekistan’s banking system. The systematic development of this process creates new opportunities for banks, increases convenience for customers, and contributes to the formation of a stable, modern, and competitive financial ecosystem

[6].References

Shakhzod G‘aniyev — Prospects of banking and financial systems in the digital economyLink: https://yashil-iqtisodiyot-taraqqiyot.uz/journal/index.php/GED/article/view/6580Fintech and MSEs Innovation: an Empirical AnalysisLink: https://arxiv.org/abs/2407.17293Umurzoq Radjabov — Prospects for improving tax administration efficiency in the transformation of digital financial servicesLink: https://muhandislik-iqtisodiyot.uz/index.php/journal/article/view/1300R.H. Ayupov, G.R. Boltaboeva — Fundamentals of the digital economy, Tashkent-2020Yakubova Sh.Sh., Po‘latova M.Sh. Development of financial technology market infrastructure // Spanish Journal of Innovation and Integrity – 2024Temurbek Normo‘minov — Cooperation between fintech startups and commercial banksLink: https://yashil-iqtisodiyot-taraqqiyot.uz/journal/index.php/GED/article/view/7945

March winds have abated

The power, the delirium

The hastiness all gone

But will it come back 

In childhood fury

To measure time by the

Indefinite hour glass?

Once more I step  on these

Hills, light footed, light winged

To answer the rains which 

Come catapulting into night skies

And walk the ways of a thousand

Roads.

Ananya S Guha

Shillong

INDIA

Ananya S Guha lives in Shillong in North East India. He has been writing and publishing his poetry for the last forty years, and has ten collections of poetry to his credit.

Originally published in the Gorko Gazette.

Le Penseur

Stan sat before the old television set, unmoving. He was just dimly aware that his torso and limbs were arranged in the same posture as Rodin’s “The Thinker,” only in flesh tones instead of the bronze of the sculpture. While Le Penseur had for more than a century captivated observers with its monumental reflection of profound introspection, Stan knew only that he was stoned on peach-flavored vodka and ersatz Nyquil. Like the statue, Stan was totally nude.

It had been a long night. Leaving his sleeping wife alone in the middle of the night to grab a beer and catch some professional wrestling on the tube, he had gotten wildly drunk and stayed that way into the morning. He worked hard as a bricklayer and only cut loose one night a week. He didn’t frequent the bars anymore, and usually held himself together enough to accompany Bree to church on Sunday morning.

He gazed bleakly at the TV, saw on the fuzzy screen only the pointless Sunday morning discussion programs. Stan moved his right elbow from his left knee and bent to retrieve his flask of generic vodka. He then snatched from the TV table the large, trapezoid-shaped bottle of generic cold meds. Decanting the green, gloppy liquid into a small plastic cup, he tossed it back like a shot of tequila. Next he unscrewed the vodka and took a bracing hit. The hair on his arms stood on end.

“I’m ready,” he said aloud, “for a Sunday without football.”

Keys rattled in the locket and through the front door walked Bree. She dropped her purse and a grocery bag on the parson’s table beside the entrance. She stared at her husband and offered up, “Shit-faced again, lover?”

“Is that what you learned at Sunday school today?” asked Stan, promptly falling off the sofa and bonking his head on the edge of the TV. 

As he lay there, dazed, Bree sashayed through the living room, took up a vase, removed the fresh-cut flowers and poured the water on her husband’s head. Stan sprang to life at once.

Stan shook himself like a dog. “What’s for lunch?” he slurred.

“Hash.  Don’t get up; I’ll serve you where you are.”

“Thanks, ‘hon.”

Bree brings him something ugly in a bowl.”

“Hey Bree, that’s the dog’s food dish.”

“Of course it is, I gave you dog food.”

“Bree, I can only take so much. You know I can leave you at any time.”

“Promises, promises. The checkout guy at the grocery lets me know, every time I shop, that he’s available. Good hair, nice teeth and a body that looks like a Greek statue. You really want to make threats?”

“You think you are so hot! Want to know what the secretaries for the union say about me?”

“Sure, I could use a good laugh.”

“They say I have great penmanship.”

They blink at the other for a moment, and then Bree hides her mouth with her hand and starts to giggle. Stan joins her. Soon they are laughing uproariously.

“Hey Bree, help your drunk old man up so we can watch something on TV.”

“OK, but after that I’ve got to put away groceries.”

Later they leave the TV on but ignore it while making out like a couple of teenagers. The ice cream melts in the bag on the table.

THE WORLD DOES NOT AGE

The world gets younger, the world does not age,

The sky that makes the world old does not rise,

Which person does not draw strength from God?

I am focused on your gaze.

What a good world you have created, God,

What a good, good thing you have created, God!

What a good world you have introduced to me, God,

I am drawn to your gaze.

You have a pure gaze in our mysterious world,

You have many unknown patterns,

You have a shower of light that will wash the world,

I am drawn to your gaze.

Life ends, the world does not grow old,

Not every person rises in your presence,

Does Justice not gain strength from this servant?

I am drawn to your gaze.

‎The Silence of Multiplicity

‎Mesfakus Salahin, Bangladesh

‎

‎I stay up all night

‎I tie my mind’s  horse

‎In an invisible thread

‎The horse flies away into solitude

‎The thread is weak

‎The earthly mind

‎Floating in the mysterious water

‎The self is always deceived

‎in the midst of the trance

‎The new-fashioned arrogance plays

‎Written in the dew of a leaf of grass

‎Returning again and again

‎The horse blows away the dust

‎Leaving everything behind, its own circle

‎In the circle of greed, in the crowd;

‎In the story of life, in the prose of wealth;

‎Only searching for oneself in the depths

‎In the deluge that pierces the veil of night

‎The intention of touching a straight line

‎Wakes up in the estuary

‎I cut the blood line

‎I cut the dark mountain and catch the guest

‎The sky descends with the color of the sky

‎The guest is lost in the unknown

‎All darkness becomes light through discussion

‎The soul enters the grave of the night and moves

‎The night does not remain in the grave

‎The greedy hand does not remain

‎Day does not remain

‎Whatever is colorful becomes bare

‎There remain deeds and lamentations

‎The dead river of boundless time have crossed

‎In the living grave, night remains, the illusion of night;

‎The shadow of day on the back of day

‎The multiplicity of self

‎The silence of multiplicity

MANAGING INDIVIDUAL STUDY PLANS THROUGH AI

Ibroximova Hayitxon Mirzoxidjon qizi

Andijan State Technical Institute

Faculty of Information Security and Computer Technologies

2nd-year student, Information Systems and Technologies

Email: ibroximovahayitxon@gmail.com

Abstract

This article describes the mechanism for creating flexible study plans for students by processing academic data in the 1C:Enterprise system using artificial intelligence. The study analyzes an innovative approach to predicting student potential using neural networks and automatically optimizing the educational trajectory. This method contributes to the digital transformation of educational management.

Keywords: 1C: Enterprise platform, artificial intelligence, individual learning trajectory, personalized learning, data analytics, neural networks, digital education management.

Introduction

Today, the digitalization of higher education is not just about converting statistical data into electronic form, but about transitioning to a completely new model of managing education quality. As the global trend toward personalized education continues to grow, creating individual learning trajectories that match students’ performance levels and interests has become a pressing issue.In higher education institutions of Uzbekistan, the 1C:Enterprise platform is widely used to manage academic processes. Over the years, this system has accumulated a large database (Big Data) of students’ grades, attendance, and subjects. However, current 1C configurations are mainly limited to data collection and archiving functions. Standard curricula are the same for all students and do not take into account each student’s individual cognitive abilities and learning pace.At this point, the need arises to integrate artificial intelligence (AI) algorithms with the 1C system.

AI technologies, especially machine learning models, make it possible to analyze historical data in the 1C database and identify students’ strengths and weaknesses. For example, based on previous semester results, the system can provide “smart” recommendations on which subjects a student should study more deeply or which elective courses to choose.Such an approach not only personalizes the educational process but also helps university management predict student performance in advance and reduce academic underperformance.

Methodology (Methods)

During the research, an intellectual model for managing individual study plans was developed, and the following scientific and technical methods were applied:Data collection and analysis:A dataset of students’ academic activities was created. Input data included students’ academic portfolios. The following parameters were extracted from the SQL database:Static data: entrance scores, chosen specialization

Dynamic data: current grades, midterm results, LMS activity logs

Using Python’s Pandas library, missing values were filled and the data was normalized within the range [0,1].

Application of AI algorithms:Several machine learning models were used:

Clustering (K-means): Students were grouped based on knowledge level and cognitive abilities

Regression analysis: A Linear Regression model was built to predict final exam scores

Prediction: Subjects where students struggle were identified, and additional classes were automatically added

System integration and visualization:AI modules were integrated into platforms like 1C:Enterprise. Visual graphs and charts were created using Matplotlib to track student progress.

Experimental design:Two groups were formed:Experimental group – studied using AI-based individual plansControl group – studied using traditional methods

Results were compared to evaluate effectiveness.

Results

The experiment was conducted during the first semester of the 2025–2026 academic year with 200 students:

Experimental group: 100 students (AI-based system)

Control group: 100 students (traditional system)

Key findings:

Average score:

Experimental group: 84.5

Control group: 71.2→ 18.7% improvement

Low-performing students (<60):Control: 15%AI group: 3%

Prediction model accuracy (R²): 0.892

Early prediction accuracy: 91% (by week 4)

AI automatically added 12 extra hours of training, improving weak results in 85% of cases.

Clustering results:25% – high-performing analytical learners55% – average learners20% – visually-oriented learners

Motivation in the third group increased by 32%.

Administrative efficiency:Time to create plans reduced from 45–50 minutes to 35–45 seconds

Errors reduced by 98%

Documents generated automatically in PDF

Survey results:88% of students satisfied with recommendations92% of teachers saved time and focused more on creative work

Discussion

The results show that AI-based management of individual study plans is not just a technical tool but a strategic mechanism for transforming education quality.Adaptive learning: Improved performance by 18.7%

Predictive analytics: Enabled early interventionIntegration effect: 

Combined power of Python and 1C improved efficiency

Visualization: Increased student motivation and self-monitoring

Limitations:Data quality issues (GIGO principle)

Need for Explainable AI

AI should support, not replace teachers

Future recommendations: NLP for evaluating written work

Sentiment analysis for student well-being

Mobile applications for real-time updates

Conclusion

This study shows that the era of treating all students equally in education is over. Artificial Intelligence is not just a trend but a powerful tool that improves student performance and reduces teachers’ workload.

Main conclusions:

Student performance increased by 18–20%Early prediction of failures (90% accuracy)Bureaucracy reduced by 80%Strong collaboration between humans and technologyIn conclusion, managing individual study plans through AI is the foundation of future education. Its wide implementation can significantly improve the quality of training modern, competitive specialists.