A Moodle Data Mining Technique Based Integrated E-Learning Model for Tertiary Institutions

Murtala Mohammed Alamai; Ibrahim Fa’iz Jibia; Adamu Abubakar; Salisu Umar Farouq

doi:10.56201/ijasmt.v10.no3.2024.pg1.17

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A Moodle Data Mining Technique Based Integrated E-Learning Model for Tertiary Institutions

Murtala Mohammed Alamai, Ibrahim Fa’iz Jibia, Adamu Abubakar, Salisu Umar Farouq

Abstract

In the digital age, e-learning platforms have become essential in tertiary education, offering flexible and accessible learning opportunities. This study focuses on designing an integrated e-learning model for tertiary institutions, leveraging data mining techniques within the Moodle platform to optimize educational processes. The research investigates the impact of this model on course delivery, student engagement, and learning outcomes. Utilizing a survey research design, data were collected from students at the School of Science, Federal Polytechnic, Bauchi, who were using the Moodle-based e-learning platform. The study also included a control group of students following traditional teaching methods. Convenience sampling was employed to recruit participants, ensuring the inclusion of students actively engaged with the e-learning platform. Data analysis using SPSS revealed high levels of student satisfaction and engagement with Moodle's features. Descriptive statistics and regression analyses indicated significant positive relationships between Moodle's usability, accessibility, and student engagement. Additionally, the Moodle-based model demonstrated superior learning outcomes compared to traditional methods, with higher student confidence, satisfaction, and retention rates. The findings underscore the effectiveness of integrating data mining techniques within Moodle to create a dynamic and adaptive e-learning environment. This study contributes to the advancement of e-learning practices in tertiary institutions, highlighting the potential of data-driven approaches to revolutionize teaching methodologies and enhance student learning experiences. By addressing the objectives of designing an innovative e-learning model, assessing student satisfaction, and comparing learning outcomes, this research provides valuable insights for optimizing e-learning platforms and fostering continuous improvement in academic performance.

References

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A Moodle Data Mining Technique Based Integrated E-Learning Model for Tertiary Institutions

Abstract

References

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