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Harnessing Artificial Intelligence to Create Personalized Educational Trajectories

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This research article discusses the development and testing of solutions for creating personalized educational trajectories for students using artificial intelligence technologies. It focuses on improving the educational process by generating tailored recommendations for elective courses based on data mining and machine learning methods. The study involved 4,769 students, with a significant percentage utilizing the recommendations provided.
  • main points
  • unique insights
  • practical applications
  • key topics
  • key insights
  • learning outcomes

  • • main points

    • 1
      Comprehensive methodology using data mining and machine learning for personalized education.
    • 2
      Significant empirical results demonstrating the effectiveness of the recommendation system.
    • 3
      Focus on improving student engagement and satisfaction through tailored course recommendations.

  • • unique insights

    • 1
      The use of both collaborative and content filtering techniques to enhance recommendation accuracy.
    • 2
      The hybrid approach combining different filtering methods to optimize recommendations.

  • • practical applications

    • The article provides a practical framework for implementing AI-driven recommendation systems in educational settings, enhancing personalized learning experiences.

  • • key topics

    • 1
      Artificial Intelligence in Education
    • 2
      Personalized Learning
    • 3
      Recommendation Systems

  • • key insights

    • 1
      Innovative application of AI for personalized educational trajectories.
    • 2
      Empirical validation of the recommendation system's effectiveness.
    • 3
      Integration of collaborative and content filtering for enhanced recommendations.

  • • learning outcomes

    • 1
      Understanding the role of AI in personalizing educational experiences.
    • 2
      Knowledge of methodologies for developing recommendation systems.
    • 3
      Insights into practical applications and case studies in education.
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“ Introduction

The integration of artificial intelligence (AI) technologies in education has opened new avenues for enhancing the learning experience. This article explores how AI can be utilized to build individual educational trajectories for students, focusing on personalized learning paths that cater to their interests and needs.

“ Problem Statement

The challenge lies in providing students with the autonomy to shape their educational journeys. The Moscow City University has implemented elective modules that allow students to select courses that align with their personal and professional aspirations. This study aims to improve the educational process by developing a recommendation system that offers tailored suggestions for elective courses.

“ Methodology

The research employs data mining and machine learning methods to analyze both numerical and textual data. Collaborative filtering and content filtering techniques are utilized to generate personalized recommendations for students. A digital profile for each student is created, incorporating various parameters such as academic performance and extracurricular involvement.

“ Results

The testing of the recommendation system involved 4,769 first- and second-year students across several elective course selection periods. The system successfully generated personalized recommendations, with 41.43% of students utilizing these suggestions, indicating a positive reception and effectiveness of the system.

“ Discussion

The findings highlight the importance of personalized learning experiences in enhancing student engagement and satisfaction. The recommendation system not only aids students in making informed choices but also fosters a sense of ownership over their educational paths. Future improvements may include refining the algorithms and expanding the dataset for better accuracy.

“ Conclusion

In conclusion, the development of a recommendation system based on AI technologies significantly contributes to the formation of individual educational trajectories. By providing personalized course recommendations, the system enhances the educational experience and supports students in achieving their academic and career goals.

 Original link: https://cyberleninka.ru/article/n/ispolzovanie-tehnologiy-iskusstvennogo-intellekta-dlya-vystraivaniya-individualnyh-obrazovatelnyh-traektoriy-obuchayuschihsya

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