Competences-driven and GenAI-supported hybrid personalized learning

Dragan Domazet [0000−0001−8095−5146]
Belgrade Metropolitan University
Tadeuša Košćuška 63, 11000 Belgrade, Serbia
dragan.domazet@metropolitan.ac.rs
DOI: 10.46793/eLearning2025.008D

 

Abstract. The paper presents a conceptual model of the system for personalized learning of students, in which lessons and their topics are divided into mandatory and optional, and are searched according to the competencies they provide to the student. The area of competences is divided by the depth of the competences (the depth of knowledge and skills they provide) and by the breadth (the number of teaching topics of each teaching unit). During implementation, the area of competences can change both in depth and breadth, depending on the needs of students and employers. Each student has his own specific repository of links to learning objects, located in the university’s repository, which is used for learning, as well as for verification and evaluation of what has been learned.

A hybrid procedure for the preparation of teaching materials is applied. The teacher prepares the application of the GenAI tool in accordance with the univer-sity’s standards and checks the generated results. Two approaches to the applica-tion of generative artificial intelligence are used for the preparation of teaching materials: 1) application of prompt engineering for GenAI tools; 2) application of automated preparation of prompts for GenAI tools. All forms of verification of achieved competences (tests, assignments, exams, etc.) are personalized because each student can have different optional topics in his competence portfolio of each course.

The goal is to significantly increase the efficiency of preparing teaching materi-als and verifying what has been learned, which is necessary in the case of personalized learning because it requires a larger number of optional topics and dif-ferent depths of their study, and more work for their implementation Therefore, the application of GenAI tools is a necessity in the case of personalization of learning and verification of what has been learned.

Keywords: Personalized learning · AI in education · Hybrid preparation of teaching materials

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Izvor: Proceedings of the 16th International Conference on e-Learning (ELEARNING2025)