Role of AI in Academic Research

Role of AI in Academic Research

Hari Kishan Kondaveeti, Samparthi V. S. Kumar, Atchuta Venkata Naga Manusree, Valli Kumari Vatsavayi, Preethi Ananthachari
Copyright: © 2024 |Pages: 17
DOI: 10.4018/979-8-3693-1798-3.ch001
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Abstract

Artificial intelligence (AI) is rapidly transforming academic research, accelerating discovery, improving efficiency, and opening up new avenues across various disciplines. This chapter introduces AI and discusses its broad range of applications, both within and outside of academia. The chapter then presents the applications of AI in academic research. It covers various AI tools, such as Scite, Elicit, etc., and a comparative analysis of their capabilities and limitations. The chapter also discusses some ethical issues that must be considered when using AI in academic research. It concludes with a discussion on the future of AI in academic research and the potential benefits and challenges that lie ahead. This chapter is intended for a broad audience, including academic researchers, students, and those who are interested in learning more about the role of AI in academic research.
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Automated Grading And Assessment Ai

AI is helpful to give grades to the students when they submit the quizzes or exams to the professors in online mode then AI scans the data and verifies it This AI is useful whether there is a high number of students or the complexity of the quizzes or exams. Because of this AI, we can get immediate results after the quizzes or exams. Automated grading ensures a high level of consistency in evaluation because the algorithms apply the same criteria to all submissions. This helps in fair grading. Many educational institutions integrate automated grading systems with their learning management systems, creating a seamless experience for both instructors and students. (Fleming et al., 2010).

Personalized Learning AI

AI is helpful for students to directly talk or chat with a chatbot AI clarifies doubts and can learn lessons with the help of AI (Pataranutaporn et.al.,2021). In this Personalized Learning AI, AI first scans the personality of the student or user and then helps with his problems or queries according to them. Personalized learning AI, relies on data analytics to collect data and analyze students’ progress. Instructors use this data to make informed decisions about identifying areas of improvement, adjusting instructional strategies, and offering extra support when it is needed. Personalized Learning AI, often involves giving students choices in how they demonstrate their understanding of concepts and encouraging them to pursue topics that align with their interests. These platforms use AI and machine learning to analyze students' interactions with educational content and dynamically adjust the difficulty and pace of instruction to match individual needs (Zhang et al., 2020), (Shemshack et al., 2020).

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