Generative AI, particularly ChatGPT, has significant potential to transform educational pedagogy through natural language processing capabilities, though implementation requires careful consideration of both technological and ethical implications.

Objective: The main goal of this study was to examine the prospective uses of Generative AI (GenAI) for Natural Language Processing (NLP) synthesis and its potential role as a conversational agent in educational settings, with a focus on developing an actor network model for both current ChatGPT and future generative AI applications in academic pedagogy.

Methods: The researchers employed design science methodology to create a scientific artifact – the Actor Network Theory (ANT) model for educational AI applications. The study analyzed ChatGPT's transformer architecture and NLP capabilities, particularly examining how it processes and generates human-like text. The researchers designed a framework showing how AI educational robots with NLP capabilities can function within a National Research and Education Network (NREN), creating personalized learning routes and providing feedback based on student performance data. The methodology included extensive scholarly and scientific investigations to design the structure and framework for ChatGPT in educational settings.

Key Findings:

• ChatGPT represents a significant technological achievement in natural language processing that can optimize teaching and learning in 21st-century educational environments.
• The study identified that ChatGPT's capacity to understand and produce human-like language through NLP enables it to replicate advanced human communication patterns learned from training data.
• ChatGPT can be utilized for developing instructional strategies, increasing student engagement and collaboration, and encouraging experiential, hands-on learning.
• The Actor Network Theory (ANT) model developed by the researchers demonstrates how AI agents can operate as computational entities, interacting with both internal and external environments to address learning challenges.
• Intelligent tutoring systems powered by GenAI can create personalized learning experiences by analyzing student performance, offering immediate feedback, and providing tailored guidance.
• The study found that appropriate implementation of ChatGPT in education can lead to shortened learning sessions, increased student engagement, and improved learning outcomes.

Implications: The findings suggest that integrating GenAI into educational settings has far-reaching implications for teaching and learning approaches:

• The technology can revolutionize how educational institutions operate by enabling personalized coaching and adaptive learning strategies.
• ChatGPT can assist in creating high-quality educational content, including lesson plans, quizzes, and summaries based on specific learning objectives.
• The integration of robotics and NLP algorithms can enhance students' cooperation, communication, and critical thinking abilities.
• Educational institutions can use ChatGPT to automate customer service, personalize student interactions, and enhance communication with partners worldwide.
• The research highlights the need for educators to be prepared for a future where generative AI predominates and significantly impacts teaching methodologies.
• As Society 5.0 evolves with human-robot collaboration, educational models must adapt to incorporate these technological advancements effectively.

Limitations: The study acknowledges several limitations and challenges:

• The research did not provide extensive quantitative data on the effectiveness of ChatGPT in real educational settings.
• The authors note that none of the 25 research articles published between 2022 and 2023 on ChatGPT contained a structure and framework for the Chat Generative Pre-trained Transformer model, indicating a gap in comprehensive technical analysis.
• There are concerns regarding biases in the data used to train AI models, as well as issues related to security, privacy, and the potential impact on human creativity.
• The ANT technique assumes that if one active player leaves the network, it will negatively affect all other active players, which may not account for the complex and evolving nature of educational networks.
• The paper acknowledges that educational robots are still developing, and connections with people that go beyond isolated exchanges in prearranged scenarios have yet to be achieved.

Future Directions: The researchers suggest several areas for future research:

• Identify the proper devices and components for designing effective educational robots.
• Further investigate the development of AI-mediated education automation in connection with Research in Education and Network (NREN) for process modernity.
• Explore the distinction between algorithmic generation and human creativity as the separation of human and artificial intelligence becomes more pronounced.
• Examine the intricate patterns and structures of human language to improve how generative AI understands and produces text that resembles human communication.
• Investigate how to effectively implement educational robots that encourage learning to provide academically struggling students with the insights they need to succeed.
• Address ethical considerations related to the use of ChatGPT in educational settings, including responsible deployment and potential societal impacts.

Title and Authors: "Generative Artificial Intelligence (AI) Educational Pedagogy Development: Conversational AI with User-Centric ChatGPT4" by Ugochukwu Okwudili Matthew, Kafayat Motomori Bakare, Godwin Nse Ebong, Charles Chukwuebuka Ndukwu, and Andrew Chinonso Nwanakwaugwu.

Published On: December 13, 2023

Published By: Journal of Trends in Computer Science and Smart Technology, December 2023, Volume 5, Issue 4, Pages 401-418