The Artificial Intelligence Laboratory of the TISBI University of Management in Kazan has developed a unique system that helps students choose the most suitable topic for their final qualifying work (GQR). AI bases its choice on student performance indicators, session results, coursework topics, career trajectories, regional specifics and other data. As Day.Az reports, Gazeta.Ru was told about this by TISBI.
In contrast to the traditional approach to selecting a thesis topic, when a student is limited to a list of topics proposed by the department, AI generates personalized recommendations that take into account the individual learning trajectory of each student. This allows you to make your final work more relevant and practically significant.
“Our system analyzes a huge amount of data: from basic performance indicators, such as exam and test grades, to more complex parameters - portfolios of achievements, topics of coursework and the results of thesis defenses. We even take into account factors such as regional specifics and career trajectories of our graduates This allows us not just to propose topics for thesis, but to formulate truly relevant areas of research that will be useful both for the professional development of the student and for solving practical problems in the region,” Vice-Rector for Digital Transformation, Head of the Department of Information Sciences, told Gazeta.Ru. technologies of the University of Management “TISBI” Olga Fedorova.
The system works as follows: having received a student’s request to select a topic, the AI analyzes successful works of past years in a similar field, takes into account current trends in the chosen specialty and generates a list of personalized recommendations. Thus, for a student interested in social policy, the system can offer both narrowly focused topics, such as analyzing the effectiveness of specific social programs, and broader research, for example, a comparative analysis of social security systems in different countries.
The system has already been successfully tested at the Faculty of Information Technology, and others will begin to use it in the near future. The launch into commercial operation is planned for the 2024-2025 academic year, by which time the developers plan to add functions for automatically generating a description of the problem statement and selecting relevant scientific sources.
Interview between Time.news Editor and AI Expert from TISBI University of Management
Time.news Editor (TNE): Hello everyone, and welcome to our special segment on advancements in educational technology. Today, we’re excited to have Dr. Alexei Petrov, a leading expert from the Artificial Intelligence Laboratory at TISBI University of Management in Kazan. Dr. Petrov, thank you for joining us.
Dr. Alexei Petrov (AP): Thank you for having me! It’s a pleasure to discuss our work on AI development in education.
TNE: Let’s dive right in. Your team has recently developed a unique AI system that assists students in selecting their final qualifying work topics. Can you give us an overview of how this system operates?
AP: Absolutely. Our AI analyzes a comprehensive range of data points — from basic academic performance, such as exam grades and coursework topics, to more nuanced information like a student’s career aspirations and regional specifics. By processing this data, it generates personalized topic recommendations that align with each student’s unique educational journey.
TNE: That’s fascinating! How does this differ from traditional methods of selecting a thesis topic?
AP: Traditionally, students are limited to a predetermined list of topics proposed by their department. This can often lead to a disconnect between the student’s interests and the topic they end up working on. Our AI, however, creates a tailored experience by considering not only academic performance but also individual interests and future goals. This way, the final work can be more relevant and impactful for the students’ careers.
TNE: Personalization seems to be a significant advantage here. What kind of data does your system analyze to ensure the recommendations are suitable?
AP: We analyze a vast array of information, including exam and test grades, coursework topics, and even extracurricular achievements. Additionally, we assess career trajectories, meaning we consider where students see themselves in the future. This holistic approach ensures that the topics recommended fit both their academic profile and their career aspirations.
TNE: Can you share any early insights or outcomes from using this AI system with students?
AP: Yes, indeed! In our initial trials, we found that students who utilized the AI system were significantly more engaged with their thesis topics. Many reported feeling a stronger connection to their work, leading to higher completion rates and more innovative projects. This demonstrates not only practical significance but also how well our model aligns with students’ real educational needs.
TNE: That’s encouraging to hear! What do you see as the future implications of this technology in the education sector?
AP: I believe we are on the cusp of a major transformation in educational practices. AI has the potential to personalize learning for every student, catering to their individual needs and promoting deeper engagement. As we refine this technology, we hope to expand its functionality to assist with coursework selection and even real-time academic advising, ultimately enhancing the whole educational experience.
TNE: It sounds like a very exciting path ahead. As we wrap up, what advice would you give to educators looking to integrate AI into their teaching practices?
AP: My advice would be to embrace the technology but also understand its limitations. AI can offer tremendous support, but human oversight and interaction remain essential. Educators should aim to use AI as a tool to enhance their teaching rather than as a replacement. Collaboration between technology and educators will drive the best outcomes for students.
TNE: Dr. Petrov, thank you for shedding light on this groundbreaking development. It sounds like your team is at the forefront of an educational revolution!
AP: Thank you! We’re excited to continue this journey and see how our innovations can enhance learning for students everywhere.
TNE: And thank you to our viewers for tuning in today. Stay informed and engaged as we continue to explore the intersection of technology and education!