Artificial Intelligence in Education: Transforming Learning and Teaching

Introduction

In an age where artificial intelligence (AI) seamlessly integrates into daily life, its infusion into educational contexts represents promising opportunities but also significant challenges. For example, a recent news report highlighted the experience of a University of North Georgia student who fought back against a policy that landed her on academic probation with the possibility of losing her scholarship (Menezes, 2024). The student used an online tool to revise her work, Grammarly, that utilizes Generative AI (Gen-AI) for spelling and grammar errors. The University of North Georgia previously supported the use of Grammarly, advertising its service to students, but the situation led to a seesaw of confusion, with the university removing, and then again, advertising the resource. A spokesperson for the platform responded, stating, “Education is wrestling right now with how they need to evolve the way they assess writing” (See Menezes, 2024, para. 13).

The story is but one example of the broader struggle within education to integrate such innovative technologies—a journey marked by transformative benefits and concomitant disruptions. Readers may reflect on the many technological advancements that have emerged over the years, reshaping the educational landscape. These innovations range from the advent of the Texas Instruments (TI) calculators to desktop and laptop computers, the emergence of the internet, the introduction of electronic readers (eReaders), distance learning, the implementation of learning management systems (LMS), and the widespread adoption of smartphones and tablets. This evolution also includes the use of interactive smartboards, digital media, and virtual simulations in classrooms. In fact, almost 20 years ago, The International Society for Technology in Education (ISTE) emphasized that:

As AI becomes increasingly embedded in our daily lives—from smartphones to streaming services—the educational sector struggles to keep pace, often hindered by a lack of understanding and research-based practices (Delello et al., 2024; Yau et al., 2023).

As we examine the realm of recent technological breakthroughs, this chapter focuses on the profound impact of AI and Gen-AI in education. We also explore the role of biometrics in AI, offering a perspective as to how these technologies are reshaping the educational landscape. Further, the chapter surveys a variety of applications and provides examples of AI in education, highlights current impacts and potential future developments, and then examines transformative and disruptive implications from related case studies. The final section brings forth considerations around future trends for education, ethical considerations, policy and regulations, and suggested resources for future reading.

Review Of The Literature

From its origins in rule-based systems, AI has undergone a transformative journey, progressively adopting machine learning (ML) and deep learning models (DLMs) to enhance its ability to process and interpret complex data. This progression has led to the advent of generative artificial intelligence (Gen-AI), a model designed to generate new content, as opposed to predicting outcomes from a specific dataset (Zewe, 2023). Gen-AI has the capability to generate text, images, sounds, code, and other media using models in response to prompts. In fact, “2024” has been declared the “year of generative AI,” as noted by Hockenbary (2024, para. 1). The transformative impact of AI in education stems from its core ability to recognize and interpret patterns. This capability is integral to both basic rule-based algorithms and more complex machine learning (ML) and deep learning models (DLMs). Such AI systems excel in handling large datasets, which underpin technologies like adaptive learning platforms and intelligent tutoring systems. These systems utilize pattern recognition to personalize and enhance the educational experience.