Leveraging AI to Personalize and Humanize Online Learning: Transforming Transactional Interactions Into Meaningful Engagements

Introduction

The global shift towards online education has reached an unprecedented scale, a trend only accelerated by the COVID-19 pandemic that saw temporary closures affecting 70% of the global student population (Vlasova, 2022). In the post-pandemic era, a 2021 survey revealed that 73% of students wanted to take some courses fully online, reflecting a change in attitudes and acceptance of online learning (McKenzie, 2021). By 2023, this sentiment had grown stronger, with 79% of online students and graduates strongly affirming the value of their online degrees (White, 2023). With such a demand on the part of students, the global e-learning market, already on an impressive growth trajectory, is expected to reach $336.98 billion by 2026 (Patra & Sahu, 2020). Moreover, the reasons cited in favor of online and distance education have remained consistent since before the pandemic. For instance, a 2019 survey identified affordability, reputation, and quick paths to degrees as key factors driving students to online programs (Singh & Sharma, 2021). Fast forward to 2023, and the prevalence of online education has continued to expand dramatically, reflecting not only the technology-driven revolution in learning but also the evolving needs and preferences of students (Alenezi, 2023).

In the shifting sands of education, where learning management systems (LMS) have increasingly replaced physical classrooms, the integration of digital platforms within the educational landscape has seen a notable surge. This chapter aims to explore the multifaceted implications of this transition, particularly focusing on how it has expanded opportunities for personalized learning while also raising questions about maintaining quality and integrity in education. Indeed, the rapid progression of technology has led to more sophisticated virtual learning environments (Hutson, Steffes, & Weber, 2023), educators are continually innovating with content delivery methods (Lytras et al., 2022), and there is a notable shift towards flexible learning modalities aligning with student preferences (Addae, 2022; Alanzi & Alhalafawy, 2022; Armellini et al., 2022). Despite the entrenched nature of online classes in the higher education framework, this chapter scrutinizes the remaining concerns about their quality and integrity, with a particular emphasis on overcoming the impersonal nature of online learning to ensure a richer, more engaging educational experience. As we delve into the strategies and tools that can humanize online learning, including the potential of emotionally intelligent AI, the aim is to provide a comprehensive guide for educators to navigate and enhance the digital learning landscape.

While the embrace of online education within higher education institutions has been extensive and growing, this trend has not been without its share of criticisms and challenges. Concerns persist over the quality and rigor of online instruction. Skeptics question whether the depth and rigor of traditional classroom experiences can be maintained in an online format, particularly in subjects that typically require hands-on practice and in-person mentoring (Malik & Zhu 2023; May et al., 2022). Such critiques were especially pronounced with the unprecedented and unexpected move to online and distance education during the pandemic (Pozo-Rico et al., 2020; Sutiah et al., 2020; Whalen, 2020). One of the main concerns over the quality and rigor of online learning is the issue of cheating and academic integrity. The remote nature of this learning modality creates opportunities for academic misconduct such as cheating and plagiarism, leading to implementation of plagiarism detecting software such as Turnitin and exam proctoring with live services such as ProctorU (Adzima, 2020; Janke et al., 2021; Noorbehbahani et al., 2022). However, these concerns over quality, rigor, and academic integrity have often resulted in the focus of online education design, development, and deployment being on creating a controlled environment rather than fostering authentic learning experiences, thus potentially stifling innovation and limiting opportunities for deeper engagement and understanding (Rippy & Munoz, 2021).