Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Application of ChatGPT in Higher Education and Research – A Futuristic Analysis
44
Zitationen
2
Autoren
2023
Jahr
Abstract
Purpose: The purpose of conducting research on the "Application of ChatGPT in Higher Education and Research – A Futuristic Analysis" is to critically examine the evolving role of advanced AI language models like ChatGPT in shaping the future of education and research. This research seeks to anticipate how ChatGPT and similar technologies will impact pedagogy, academic support, and scholarly inquiry in the years ahead, shedding light on their potential benefits and challenges. By analyzing current implementations and forecasting future possibilities, this research aims to inform educators, institutions, and researchers about the transformative opportunities and ethical considerations associated with the integration of AI-driven chatbots and language models in higher education and research settings. Methodology: This is exploratory research and makes use of the information obtained from scholarly articles through Google Scholar and AI-based GPTs to analyse, compare, evaluate, and interpret the concept of application of ChatGPT in Higher Education and Research. Results/Analysis: A systematic analysis is carried out on the futuristic and effective use of ChatGPT for higher education, advanced research, scholarly publication, and possible threats of it on higher education industry. Originality/Value: A systematic analysis is carried out to interpret: (1) the diverse applications of ChatGPT in various academic disciplines, including basic sciences, engineering, health sciences, agriculture, management, and social sciences within higher education, (2) how ChatGPT contributes to different types of research, including exploratory, empirical, and experimental research endeavours. Type of Paper: Exploratory Research.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.339 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.211 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.614 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.478 Zit.