[From Fleury’s book: Chain Letter To America: The One Thing You Can Do To End Racism:
A Collection of Essays, Fiction and Poetry Celebrating Multiculturalism]
While the butterfly hovers and the bird sways…
I take tepid steps around the forest
So not to disturb the natural way of things;
Night time in the woods,
I stroll into its evening with a lantern,
So dark a night I can only see what
The light will allow;
I can feel earthly debris crunching
Beneath my feet, the sounds echo in the distance,
I see the dilapidated treehouse that
Father and I built, a once buxom structure
Now barely standing with little nurturing…
Yet still I climb the ladder leading up to it,
The rungs creak beneath my feet,
I get into the pungent pad on the floor
And lay next to the spot where father
Once leisurely reposed while we talked into the night
Listening to at times tiresome benedictions:
The eternal noise of crickets and other cryptic night noises;
We spoke of traveling and transcending,
Navigating and never minding…
He spoke of his epistolary love with mother
And how they got together,
How glad he was when I saw light for the first time,
And how he would always be by my side,
“Promise?”
“Promise!”
“Cross your heart and hope to die?”
“Promise.”
I can hear the leaves rustling in the wind,
As a gentle swaying of the treehouse that
Father and I built rocks me to sleep…
Jacques Fleury
Jacques Fleury is a Boston Globe featured Haitian American Poet, Educator, Author of four books and literary arts student at Harvard University online. His latest publication “You Are Enough: The Journey to Accepting Your Authentic Self” & other titles are available at all Boston Public Libraries, the University of Massachusetts Healey Library, University of Wyoming, Askews and Holts Library Services in the United Kingdom, The Harvard Book Store, The Grolier Poetry Bookshop, Amazon etc… He has been published in prestigious publications such as Spirit of Change Magazine, Wilderness House Literary Review, Muddy River Poetry Review, Litterateur Redefining World anthologies out of India, Poets Reading the News, the Cornell University Press anthology Class Lives: Stories from Our Economic Divide, Boston Area Small Press and Poetry Scene among others…Visit him at: http://www.authorsden.com/jacquesfleury.–
Jacques Fleury’s book You Are Enough: The Journey Towards Understanding Your Authentic Self
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.
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.
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.
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.
