EVALUATING THE IMPACT OF AN INTELLIGENT TUTORING SYSTEM ON STUDENT PERFORMANCE AT MANGOSUTHU UNIVERSITY OF TECHNOLOGY: A CROSS-SECTIONAL QUANTITATIVE STUDY

Sibonelo Thanda Mbanjwa

doi:10.51168/sjhrafrica.v6i3.1626

Authors

Sibonelo Thanda Mbanjwa Mangosuthu University of Technology P.O. Box 12363 Jacobs 4026 Durban South Africa

DOI:

https://doi.org/10.51168/sjhrafrica.v6i3.1626

Keywords:

Artificial Intelligence, Nature Conservation, Personalized Learning, Intelligent Tutoring Systems, Student Engagement, AI Ethics, Field-Based Learning

Abstract

The integration of Artificial Intelligence (AI) in education has transformed traditional learning methods. This study examines the implementation of AI-driven learning technologies, specifically Intelligent Tutoring Systems (ITS), in the Nature Conservation Department at Mangosuthu University of Technology (MUT). The study evaluates the impact of ITS on student engagement, academic performance, and efficiency in grading. A cross-sectional quantitative approach was employed, with data collected from 450 students through structured surveys and academic performance records. Statistical analyses, including descriptive statistics and regression analysis, were used to assess engagement levels, knowledge retention, and grading efficiency. The findings indicate that AI-driven personalized learning tools significantly improved student engagement and academic performance. Seventy-eight percent of students reported increased engagement when AI systems customized content to their learning styles. Sixty-two percent demonstrated an improved understanding of complex topics, while ITS real-time feedback was valued by 85% of students, leading to a 74% improvement in knowledge retention. AI-assisted grading reduced marking time by 40%, increased accuracy (92% of faculty members), and ensured that 60% of students received detailed feedback faster. However, challenges were identified, including technological barriers (12% of students), AI literacy training requirements (20%), and ethical concerns about data privacy (15%). The study concludes that AI-driven ITS significantly enhances learning outcomes in conservation education, increasing engagement, retention, and grading efficiency. However, addressing technological accessibility and ethical concerns is crucial for optimal implementation. Institutions should invest in digital infrastructure, provide AI literacy training, and implement ethical safeguards to maximize the benefits of AI in education.

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