Ai-Driven Innovation In Education 4.0: An Overview Of Generative Ai Tools, Learning Analytics, And Gamified Sql Learning

Authors

  • Alfiya Mullah Author
  • Suja Jayachandran Author

DOI:

https://doi.org/10.64252/829vnm63

Abstract

Artificial Intelligence (AI) is significantly transforming educational ecosystems by redefining curriculum design methodologies and enhancing student engagement, in alignment with the core tenets of Education 4.0. This paper investigates the integration of AI-powered tools that support instructional content development, adaptive learning pathways, and data-driven teaching interventions. These innovations enable educators to personalize instruction, monitor learner progress in real time, and dynamically adapt curricula to meet diverse student needs. The study explores a wide range of AI applications—including generative AI, intelligent tutoring systems, and predictive learning analytics—that collectively support the creation of inclusive, engaging, and future-ready learning environments.

This study also emphasis on gamified learning platforms designed to teach Structured Query Language (SQL) through interactive, scenario-based challenges. Applications such as SQL Island, Lost at SQL, SQL Murder Mystery, and DataRPG are critically reviewed, with a focus on their pedagogical design, engagement strategies, and learning outcomes. The paper demonstrates how gamification and AI can be strategically integrated into curriculum design to foster active learning, skill development, and sustained motivation among students. Ultimately, the findings highlight the transformative potential of AI in creating pedagogically robust and technologically enriched educational experiences for the digital age.

Downloads

Download data is not yet available.

Downloads

Published

2025-06-10

How to Cite

Ai-Driven Innovation In Education 4.0: An Overview Of Generative Ai Tools, Learning Analytics, And Gamified Sql Learning. (2025). International Journal of Environmental Sciences, 11(9s), 1062-1066. https://doi.org/10.64252/829vnm63