International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 04 | Apr 2024
p-ISSN: 2395-0072
www.irjet.net
AI AS A TUTOR Elda Mariya Joy1, Anania Santhosh2, Ancila Ansari3, Ardra Suresh4, Ashna Suresh5 1Asst.Professor,Dept.of Computer Science and Engineering,Sree Narayana Gurukulam College of
Engineering,Kadayiruppu,Kerala,India
2,3,4,5 Dept.of Computer Science and Engineering,Sree Narayana Gurukulam College of
Engineering,Kadayiruppu,Kerala,India ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - This survey paper presents a comprehensive
Wang and Ai-ling Qiao examines strategies for developing effective online learning models, with a focus on the crucial role of online tutors. Given the emphasis on utilizing information technology to improve education in China, the
exploration of Artificial Intelligence (AI) systems functioning as tutors, encompassing related works, comparisons, and future scope. The review delves into various methodologies, algorithms, datasets, and applications employed in AI tutor systems. It synthesizes existing literature to shed light on the evolution of these systems, providing insights into challenges faced and advancements achieved. Through comparative analyses, the paper discusses and contrasts different approaches, offering a critical perspective on their effectiveness. The survey also outlines potential future directions and areas for improvement in AI-based tutoring. Aimed at scholars, professionals, and enthusiasts, the paper serves as a valuable resource to stimulate further innovation and understanding in the dynamic field of AI tutoring.
authors analyze common challenges in web-based learning. They propose that online tutors are critical to drive student engagement and learning outcomes. The paper suggests online tutors should facilitate structured learning experiences by designing meaningful tasks and moderating collaborative discussion forums. Additionally, tutors should provide customized support based on the specific curriculum and needs of individual learners. Overall, the authors recommend that online instructors embrace their role as guides and enablers of self-directed online learning. With proper tutor participation, web-based education can become more impactful. The paper aims to encourage teachers to actively support students in online environments, in order to enhance the effectiveness of technology-enabled instruction. Further research could continue investigating optimal online teaching strategies.
Key Words: AI Tutoring, Intelligent Tutoring Systems (ITS), Personalized Learning,Online Learning, Tutoring Systems Evaluation, Student Engagement. 1. INTRODUCTION
The research paper [2]"Understanding the Factors Influencing Higher Education Students” Intention to Adopt Artificial Intelligence-Based Robots" by Mohammed A. M. Algerafi, Yueliang Zhou, Hind Alfadda, and Tommy Tanu Wijaya, investigates Chinese higher education students' willingness to adopt AI-based robots for educational purposes. Applying the Technology Acceptance Model (TAM) 3, the study proposes 14 hypotheses, revealing that 12 were accepted. The results suggest a positive inclination among students to embrace AI-based robots in education. However, job relevance and robot anxiety were found to have insignificant impacts on perceived usefulness and ease of use, respectively. The study offers valuable insights for university administrations, robot developers, policymakers, and administrators in designing and implementing AI-based robots to meet contemporary educational needs.
In the contemporary landscape of education, the infusion of Artificial Intelligence (AI) has ushered in a paradigm shift, revolutionizing the way we perceive and engage with learning. One of the remarkable manifestations of this transformation is the emergence of AI tutors, intelligent systems designed to guide and support learners in their educational journey. As traditional teaching methods undergo a digital metamorphosis, AI tutors stand at the forefront, offering personalized, adaptive, and data-driven approaches to education. This review delves into the multifaceted realm of AI as a tutor, exploring the diverse methodologies, applications, and implications of these intelligent systems. By examining related works, drawing comparisons, and outlining future prospects, we aim to provide a holistic understanding of the current state and potential advancements in AI-driven educational tutoring.
The research paper [3] "Artificial Intelligence in Education: A Review" by Lijia Chen, Pingping Chen, and Zhijian Lin, explores the impact of Artificial Intelligence (AI) on education. Focusing on administration, instruction, and learning, the study utilizes a qualitative approach and literature review to assess AI applications. It reveals the
2. LITERATURE SURVEY In the paper [1] “ The Research on the Role of Online Tutor and the Learning Activity Organization Strategies" by Nan
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