E-tutor: Comprehensive Student Productivity Management System for Education

Silva, Kumuditha; Induwara, Rashmin; Wimukthi, Malshan; Poornika, Sathsarani; Arachchillage, Udara Srimath S. Samaratunge; Jayalath, Thilini

doi:10.1109/icac57685.2022.10025237

Cited by 2 publications

References 17 publications

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Artificial intelligence in intelligent tutoring systems toward sustainable education: a systematic review

Lin,

Huang,

2023

Smart Learn. Environ.

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Sustainable education is a crucial aspect of creating a sustainable future, yet it faces several key challenges, including inadequate infrastructure, limited resources, and a lack of awareness and engagement. Artificial intelligence (AI) has the potential to address these challenges and enhance sustainable education by improving access to quality education, creating personalized learning experiences, and supporting data-driven decision-making. One outcome of using AI and Information Technology (IT) systems in sustainable education is the ability to provide students with personalized learning experiences that cater to their unique learning styles and preferences. Additionally, AI systems can provide teachers with data-driven insights into student performance, emotions, and engagement levels, enabling them to tailor their teaching methods and approaches or provide assistance or intervention accordingly. However, the use of AI and IT systems in sustainable education also presents challenges, including issues related to privacy and data security, as well as potential biases in algorithms and machine learning models. Moreover, the deployment of these systems requires significant investments in technology and infrastructure, which can be a challenge for educators. In this review paper, we will provide different perspectives from educators and information technology solution architects to connect education and AI technology. The discussion areas include sustainable education concepts and challenges, technology coverage and outcomes, as well as future research directions. By addressing these challenges and pursuing further research, we can unlock the full potential of these technologies and support a more equitable and sustainable education system.

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Artificial intelligence in intelligent tutoring systems toward sustainable education: a systematic review

Lin,

Huang,

2023

Smart Learn. Environ.

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Integration of Metaverse and Machine Learning in the Education Sector

Shanthalakshmi Revathy,

Mangaiyarkkarasi

2024

Advances in Computer and Electrical Engineering

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E-Tutor is revolutionizing education through technology, offering personalized learning with integrated study materials, video lectures, interactive quizzes, and metaverse features. Research indicates a 35% increase in student engagement and a 20% improvement in comprehension scores with E-Tutor. Utilizing machine learning and user feedback, it ensures adaptive learning while upholding data privacy and transparency. E-Tutor embraces trends like gamification and augmented reality, aiming to transform the educational landscape. It promotes collaboration and addresses diverse learning needs, with user surveys showing a 40% rise in collaborative learning efficiency and a 25% reduction in learning disparities among students. Committed to continuous innovation, E-Tutor empowers learners by leveraging technology responsibly to achieve impactful learning outcomes.

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E-tutor: Comprehensive Student Productivity Management System for Education

Cited by 2 publications

References 17 publications

Artificial intelligence in intelligent tutoring systems toward sustainable education: a systematic review

Artificial intelligence in intelligent tutoring systems toward sustainable education: a systematic review

Integration of Metaverse and Machine Learning in the Education Sector

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