Development of a Data Analytics and Visualization System for the Digital Profile of AITU Graduates (based on iGPA, SCI, and ROS indicators from AITU Digital University)

Project Supervisor: Gulzhan Soltan, Associate Professor of the Department of Computer Engineering

Project Goal: Development of a functional model of a data analytics system and the application of visualization methods for the digital profile of AITU graduates, based on the integrated GPA indicators of students at Astana IT University.

1. Conduct a literature review on the research topic, including analysis and study of modern data analytics and visualization methods;
2. Collect and analyze initial data from the Digital University system;
3. Develop a functional model to structure the processes of data collection, processing, and visualization;
4. Build a mathematical model to analyze relationships between indicators;
5. Develop interactive dashboards for the convenient presentation of results;
6. Test and implement the system in the AITU educational process;
7. Publish the research results.

is to create a functional model of a data analytics system that allows a comprehensive approach to the analysis and visualization of educational data based on the integrated IGPA (Integrated Grade Point Average) indicator, which combines the academic, research, and social achievements of students. Interactive dashboards will allow easy tracking of each student’s progress and assessment of their potential, which will help improve the quality of education.

It is expected that the proposed data analytics and visualization system will improve the efficiency of educational process management, enable effective use of IGPA data for analyzing students’ individual progress and potential, and enhance the quality of their professional training.

1. A detailed analysis of scientific sources was conducted, including a systematic review of studies on the application of artificial intelligence, educational analytics, and digital profiles in higher education. Special attention was given to critical analysis of methodologies, sample sizes, applied metrics, practical applicability of results, and identifying gaps in empirical validation and model robustness under real educational conditions.
2. Data collection and initial processing from the Digital University information system were performed. Data were collected and processed for three main components of the comprehensive IGPA assessment: GPA (academic performance), iROS (research activity), and SSCI (social activity). Information was aggregated and visualized using Power BI, which made it possible to monitor changes in indicators across cohorts and academic programs.
3. A functional model was developed, describing data flows, processing stages, and visualization implementation for dashboards in Power BI.

4. A mathematical model was constructed to analyze the relationships between indicators, accounting for all necessary criteria for student success: academic, research, and social. To support further analysis and segmentation of students based on IGPA, a clustering model was developed using the k-means algorithm (KMeans). The same algorithm was used to identify clusters of academic disciplines. In this study, k = 5 clusters were defined, allowing courses to be divided into five main semantic groups.

5. An interactive dashboard was developed for the convenient presentation of results. The interactive dashboard visualizes key performance indicators related to student activities. The total number of students represented on the dashboard is 9,785.

6. Functional and mathematical models were tested based on processed data obtained from the Digital University system. Testing results demonstrated the effectiveness of the models for analyzing individual student progress.

7. As a result of the project, an article was submitted for publication in a journal «Scientific Journal of Astana IT University», and a copyright certificate was obtained.

Gulzhan Soltan

Project Supervisor, PhD in Engineering, Associate Professor, Department of Computer Engineering

Zharkyn Bekqaliyev

Project Contributor, 1st year Master’s student, Astana IT University

Alen Issayev

Project Contributor, 2nd year student, Astana IT University