Tailoring knowledge: Adaptive content recommenders in personalized learning environments (10 min)

Education in educational institutions and companies has increased the need for the advancement of online education while putting a student at the center of learning and creating additional requirements for improvements for future education. The traditional "one-size-fits-all" approach, with the changing needs of individuals and educational institutions, does not meet the needs of individual modern learners. Furthermore, artificial intelligence (AI) and educational data mining have expanded the technological capabilities of learning systems increasing at the same time the possibility for adaptive and personalized learning content. The key to achieving a system that can provide adaptability and personalization of learning content lies in the effective monitoring of student activities and achieved learning outcomes. In this presentation aims to represent several conducted research and developed systems focused on personalized learning at Belgrade Metropolitan University. The focus will be placed on an intelligent software system with the possibility of dynamically generating adaptive and personalized learning content using learning objects. The objectives of this system are to increase learning quality, improve student success rates, and harness each student's unique learning potential. Based on the student’s performance this system dynamically creates a knowledge base that connects learning outcomes, learning content, and expert system rules. This system works with lessons consisting of carefully selected sets of learning objects, categorized by knowledge level. The primary goals are to harness each student's individual learning potential and enhance the quality and efficiency of education while reducing students’ dropout rates. To achieve these goals, the system continuously tracks student progress and employs predictive analytics to identify potential issues early on, offering additional materials, increased interaction, or interventions to prevent disengagement. This proactive approach allows for the provision of additional learning materials, increased interaction with instructors, or the implementation of intervention methods to prevent student disengagement.

Participants' prior knowledge / Potrebno predznanje: not applicable

Learning outcomes / Ishodi učenja:
- participants will be able to recognize the shortcomings of the traditional "one-size-fits-all" approach to education and understand the importance and advantages of personalized learning in online learning systems
- participants will gain an understanding of how intelligent software systems, based on dynamic content recommendation, can contribute to developments of personalized learning