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Exploring the Potential of Cloud-Based Artificial Intelligence in Personalized Education in Secondary Schools in Gombe Local Government Area, Gombe State

  • Project Research
  • 1-5 Chapters
  • Abstract : Available
  • Table of Content: Available
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  • NGN 5000

Background of the Study

Cloud-based Artificial Intelligence (AI) refers to the integration of AI technologies within cloud computing platforms, enabling the delivery of powerful, scalable, and flexible learning tools that can be accessed remotely. In education, the combination of cloud computing and AI offers unprecedented opportunities to deliver personalized learning experiences to students. By utilizing cloud-based AI systems, educators can provide students with customized learning paths, real-time feedback, and resources tailored to their individual learning needs and progress.

In secondary schools in Gombe Local Government Area, Gombe State, the adoption of cloud-based AI for personalized education has the potential to address various challenges such as overcrowded classrooms, diverse learning abilities, and limited access to educational resources. The ability to deliver AI-driven, personalized learning experiences through the cloud can significantly enhance the quality of education, making it accessible and effective for all students, regardless of their location or socio-economic background.

Statement of the Problem

Despite the promising benefits of cloud-based AI in personalized education, its integration into secondary schools in Gombe Local Government Area remains underdeveloped. Schools in the region face barriers such as lack of awareness, limited technological infrastructure, and resistance to new educational practices. This study seeks to explore the potential of cloud-based AI in personalized education and assess how it can improve teaching and learning outcomes in Gombe's secondary schools.

Objectives of the Study

  1. To explore the potential of cloud-based AI in providing personalized education in secondary schools in Gombe Local Government Area.

  2. To assess the impact of cloud-based AI on student learning outcomes and engagement.

  3. To identify the challenges and benefits of integrating cloud-based AI into personalized education in secondary schools.

Research Questions

  1. How can cloud-based AI provide personalized education in secondary schools in Gombe Local Government Area?

  2. What impact does cloud-based AI have on student learning outcomes and engagement?

  3. What are the challenges and benefits associated with integrating cloud-based AI into personalized education?

Research Hypotheses

  1. Cloud-based AI can effectively provide personalized education in secondary schools in Gombe Local Government Area.

  2. The use of cloud-based AI improves student learning outcomes and engagement in secondary schools.

  3. There are both challenges and benefits associated with integrating cloud-based AI into personalized education.

Significance of the Study

This study will provide valuable insights into the use of cloud-based AI in personalized education, offering potential solutions for overcoming educational barriers in secondary schools in Gombe Local Government Area. The findings will contribute to the global conversation on the role of AI in transforming education, especially in regions with limited resources.

Scope and Limitations of the Study

The study will focus on secondary schools in Gombe Local Government Area, Gombe State, and examine the potential of cloud-based AI in personalized education. Limitations include access to cloud-based AI resources and the level of technological readiness in schools.

Definitions of Terms

  • Cloud-Based AI: The use of artificial intelligence technologies hosted on cloud platforms, providing scalable and accessible learning solutions.

  • Personalized Education: Tailoring the learning experience to meet the individual needs, skills, and preferences of students.

  • Student Learning Outcomes: The measurable academic achievements and skills that students acquire during their educational process.





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