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Integrating and retrieving learning analytics data from heterogeneous platforms using ontology alignment: Graph-based

Mohd Hafizan Musa1,2, Sazilah Salam1,3, Siti Feirusz Ahmad Fesol4

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Summary
This summary is machine-generated.

This study introduces a new ontology for managing heterogeneous educational data, improving insights and decision-making. The Student Performance and Course ontology enhances resource management and performance evaluation for educational institutions.

Keywords:
Graph databasesGraph-Based Data Retrieval Model for Integrating Learning Analytics from Heterogeneous Platforms by Ontology DesignHeterogenous learning platformsKnowledge graphsLearning analyticsUniversity ontology

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Area of Science:

  • Computer Science
  • Educational Technology
  • Data Science

Background:

  • Educational institutions face challenges with heterogeneous data integration and retrieval.
  • Existing ontologies require improvisation to address new educational data topics.
  • Need for advanced data-driven decision-making in higher education.

Purpose of the Study:

  • To explore integrating and retrieving heterogeneous data across platforms using ontology graph databases.
  • To enhance educational insights and enable data-driven decision-making.
  • To propose an innovative ontology for managing student and course performance data.

Main Methods:

  • Developed an innovative ontology, the Student Performance and Course ontology.
  • Improvised existing entities and introduced new ones based on preliminary interviews.
  • Utilized ontology graph databases for data integration and retrieval.
  • Incorporated an evaluation matrix for performance assessment-based data retrieval.

Main Results:

  • Successfully addressed issues of data accumulation and heterogeneity.
  • Developed a scalable model suitable for processing large datasets.
  • Enabled enhanced resource management and evaluation of courses, students, and MOOCs.
  • Confirmed a data retrieval process based on performance assessment.

Conclusions:

  • The proposed Student Performance and Course ontology effectively integrates heterogeneous educational data.
  • Ontology graph databases enhance educational insights and data-driven decision-making.
  • The model offers a scalable solution for managing and evaluating educational data.