AI-Powered Teaching Plan: Present and Post Evaluation

Introduction

The landscape of education is changing. Our educational system has undergone numerous changes as a result of the pandemic, including a greater dependence on technology and the use of remote and hybrid learning. Artificial intelligence then emerged, greatly improving the effectiveness and efficiency of our educational system. Artificial intelligence (AI) refers to the development of computer systems capable of doing activities that would normally need human intelligence. These tasks include learning, thinking, problem-solving, vision, language comprehension, and even interacting with the environment (Creamer, 2012). AI technologies aim to simulate and replicate human cognitive abilities, allowing machines to adapt and improve over time.

In the rapidly evolving landscape of education, Artificial Intelligence (AI) is playing an increasingly prominent role in reshaping the way we teach and learn as in Figure 1.

Figure 1.

AI in teaching

(Authors)

AI-powered teaching leverages advanced technologies to enhance the educational experience, making it more personalized, adaptive, and efficient (Picciano, 2017). This transformative approach holds the potential to revolutionize traditional teaching methods and address the diverse needs of students.

This book chapter mainly focuses on AI-powered teaching and Learning which includes, the History of AI in Teaching, Components of AI-powered teaching, the 3 P’s (Plan, Progress, and Post evaluation) of AI-powered teaching and learning journey with its benefits, Challenges, and Opportunities, analyzing the impact in Higher Education through case studies, Particularly, the impact of AI in IT majors, implications of AI-powered teaching and learning such as Psychological, Social, Cultural and Ethical, Cutting edge technologies that support the future of AI-powered teaching, Recommendations to Policymakers to navigate the challenges and key areas to be concentrated in future of AI-powered teaching. All the above sections are reviewed, and evaluated, and in-depth information has been provided in line with the goals of this chapter.

Evolution Of Ai In Teaching: A Comprehensive Historical Overview

The integration of AI in teaching has witnessed transformative changes, influencing instructional methodologies, personalization, and educational accessibility. The term “artificial intelligence” was initially coined by John McCarthy at the Dartmouth Conference in 1956, which marked the beginning of AI in education. Early AI programs, such as the General Problem Solver, laid the groundwork for problem-solving approaches in education. Notable researchers during this period include Marvin Minsky, Allen Newell, and Herbert A. Simon (Casal-Otero et al., 2023).

The 1980s marked the emergence of expert systems and Intelligent Tutoring Systems (ITS). Expert systems aimed to replicate the decision-making processes of human experts, while ITS, exemplified by systems like the Geometry Tutor, introduced personalized instruction and feedback (Picciano, 2017). The late 1990s witnessed the growth of online education platforms, setting the stage for future AI applications. While not initially AI-driven, these platforms laid the groundwork for the integration of AI into educational technologies (Moore, 2007).

The 2010s saw a surge in the integration of AI into personalized learning platforms, with companies like Knewton and Dream Box utilizing AI to adapt content based on individual student needs. Massive Open Online Courses (MOOCs) gained prominence, incorporating AI for features such as automated grading and adaptive learning. Virtual classrooms and AI-powered chatbots became prevalent in the 2010s, providing students with interactive and automated support. These technologies aimed to enhance engagement and support students in real-time (Floridi et al., 2018).