Dr. Riaz Kurbanali Israni1, Yuvraj Kaushik Jani2

Associate Professor, Department of Electrical Engineering,

School of Engineering, R K University, Rajkot, Gujarat, INDIA

Assistant Professor, Department of Electrical Engineering

Unitedworld Institute of Technology, Karnavati University, Gandhinagar, Gujarat, INDIA

E-mail: riaz.israni@rku.ac.in

DOI: https://doi.org/10.70372/jeltp.v2.i3.23

Abstract

Engineering Education 4.0 (EE-4) represents the latest paradigm in engineering pedagogy, uniting time-honored instructional methods with cutting-edge technologies most notably artificial intelligence (AI). As AI underpins the Fourth Industrial Revolution, it is imperative that engineering curricula inculcate both theoretical understanding and practical proficiency in AI concepts and applications. This responsibility falls squarely on educational institutions, which must ensure that graduates emerge not only conversant with AI but capable of leveraging its capabilities to address complex, real-world challenges. In this study, we first establish a robust framework for evaluating engineering knowledge within AI-enhanced instruction by adapting the Technological, Pedagogical, and Content Knowledge (TPACK) model. This framework guides the design and deployment of AI-based instructional tools and provides a metric for assessing their pedagogical effectiveness. We then implement an AI-driven platform utilizing the conversational agent ChatGPT as a testbed for facilitating student engagement with authentic engineering problems. A cohort of undergraduate students at RK University, Rajkot, was invited to interact with the platform over the course of a semester, applying AI-guided insights to laboratory exercises, design projects, and collaborative assignments. Quantitative and qualitative analyses were performed to compare the framework’s predicted levels of tool efficacy against observed student outcomes. Results indicate that, while theoretical evaluations of the AI tool forecast high pedagogical value, empirical evidence demonstrates that student performance improved commensurately, fulfilling the core objectives of Engineering Education 4.0. These findings underscore the obligation of engineering programs to integrate AI tools systematically, thereby preparing graduates to navigate and shape the rapidly evolving technological landscape.

Keywords — TPKS, Artificial Intelligence, ChatGPT, Engineering Education System, Industrial revolution 4.0

The exponential growth of scientific knowledge and its rapid transformation into technological innovations have become hallmarks of the modern era. These advancements offer immense potential to improve quality of life, drive economic growth, and address critical global challenges [1]. However, their responsible implementation especially in domains like education poses significant challenges that demand deliberate planning, ethical foresight, and inclusive practices.

Artificial Intelligence (AI) stands at the forefront of this transformation, with its integration into education systems having the power to reshape how students learn, engage, and solve problems. Yet, the extent to which AI will positively impact education depends largely on how thoughtfully it is designed, implemented, and governed. Without a clear framework, AI risks reinforcing existing educational disparities or compromising human-centric teaching values [2].

In the context of engineering education, where problem-solving, innovation, and adaptability are core competencies, integrating AI is not just beneficial it is essential. However, this integration must be guided by a balanced approach that maximizes AI’s potential while upholding principles of quality, equity, and ethics.

This work is necessary to explore and validate practical, ethical, and pedagogical frameworks for AI integration in engineering curricula [3]. By fostering collaboration among educators, technologists, and policymakers, and grounding decisions in empirical evidence, this research aims to ensure that AI becomes a transformative tool that enriches learning outcomes, prepares students for future industry demands, and contributes positively to the evolving landscape of education [4].

AI was indeed introduced as a formal discipline in 1956 at the Dartmouth Conference by John McCarthy and his colleagues [4]. The aimed was to explore the idea of creating machines that could simulate human intelligence. AI is indeed an interdisciplinary field. It draws upon knowledge and techniques from various domains like, computer science, information theory, control theory, philosophy, psychology, neurophysiology and linguistics [5]. Researchers and policymakers are working together to ensure responsible AI which helps to enlarge the educational and industrial advancement [6].

ChatGPT is a language model developed by Open AI, based on the GPT (Generative Pre-trained Transformer) architecture. It is designed to generate human-like text and engage in natural language conversations with users. ChatGPT is a sibling model to InstructGPT and shares similar capabilities, but it is specifically fine-tuned for generating text-based responses in a conversational context [7].

ChatGPT has been trained on a diverse range of internet text, which allows it to provide

GPT-1 (June 2018):

GPT-2 (February 2019):

GPT-3 (June 2020):

Deployment in Applications:

Fig. 1

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5. CONCLUSIONAuthor Bio

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