Abstract
This chapter examines the evolving landscape of higher education in the social sciences, specifically the shift from traditional classroom settings to AI-powered learning environments. It contrasts the features of traditional and online education, highlighting the advantages and disadvantages of each approach. The chapter then delves into the positive impacts of artificial intelligence (AI) on higher education, showcasing how AI can personalize learning experiences, improve student outcomes, and streamline administrative tasks. However, the chapter also acknowledges the challenges associated with integrating AI into higher education, including issues of global inequality, uneven distribution of AI resources, and ethical concerns. By addressing both the opportunities and challenges, this chapter provides a comprehensive overview of the transformative potential of AI in higher education and its implications for the social sciences.
TopIntroduction
Education is one of the most crucial instruments for societies’ economic, social, and cultural development, unveiling the potential of individuals and forming the foundational stones of societal progress. Another significant driving force behind societal development is the groundbreaking advancements in technology. Thus, the synergy between these two pivotal actors, education and technology, transforms teaching and learning practices by integrating technological developments into the education sector. In particular, advances in cloud computing, learning analytics, big data, and artificial intelligence present significant opportunities for enhancing students' learning skills (Cheung et al., 2021).
The traditional education system, dominated by a one-size-fits-all approach, is often criticized for overlooking individual differences, thus lacking the capacity to meet the diverse needs of learners. At this juncture, education systems worldwide are increasingly adopting a personalized approach that does not ignore individual differences, focusing on student-centered and needs-based education (Bhutoria, 2022). It is crucial to embrace methods and techniques to produce high-quality educational outcomes to adapt to current and future developments and solve problems effectively (Toniş et al., 2022). The challenges faced globally during the pandemic have necessitated a transformation in the education system (Van et al., 2020). During this period, institutions and educators were forced to rapidly transition from face-to-face to remote learning, making the creation of new learning environments inevitable (Carrillo & Flores, 2020). This situation reiterated that the education sector, a key factor in societal progress, must quickly adapt to unforeseen life conditions and changes in the economy and technology while meeting student demands (Alotaibi & Alshehri, 2023).
The advancements in information technology, coupled with the widespread adoption of artificial intelligence across nearly all aspects of societal life, have inevitably led to its integration into the education sector, embracing these new technologies for educational applications (Ouyang & Jiao, 2021). Compared to traditional educational models, which come with numerous challenges, artificial intelligence is considered a potent tool in the design of effective teaching and offers new and more efficient methods for educational research, positioning AI as a powerful and effective instrument in educational applications (Holmes et al., 2019; Hwang et al., 2020).
This study focuses on the evolution from traditional classroom environments to AI-driven learning spaces at the intersection of education and technology. It investigates how technological advancements in cloud computing, learning analytics, big data, and artificial intelligence have spurred a transformation within the education sector and examines the impact of this transformation on students' learning abilities. Furthermore, it will explore how the pandemic has accelerated the need for an urgent transformation in educational systems and detail the role of artificial intelligence in this process. The research aims not only to evaluate the current state of this transformation in higher education but also to shed light on future educational models.
The structure of the research will begin with an introduction, addressing the impact of technology on education, followed by an examination of the rise and characteristics of AI-driven learning environments. Subsequently, it will focus on the effects of these new learning environments on student skills and educational outcomes. Additionally, the rapid transformation in education during the pandemic and the role of artificial intelligence in this period will be assessed. Finally, the research will conclude by discussing the future trends and potential impacts of this transformation in higher education.
Key Terms in this Chapter
AI Assistant: Software designed to perform tasks or services for an individual or a group in an educational context. In higher education, AI assistants can support learning by answering questions, providing material suggestions, or assisting with administrative tasks.
Higher Education Digital Capability Framework: A model that delineates critical capabilities and pinpoints strategic areas for focus and development in higher education to enhance digital transformation. It covers recruitment, curriculum design, assessment, and career planning.
Intelligent Tutoring System (ITS): Advanced computer systems that provide immediate and personalized instruction or feedback to learners, typically without requiring intervention from a human teacher. ITS systems adapt to the needs of individual students, often using AI to tailor the learning experience.
Digital Transformation Strategy: A plan developed by educational institutions to integrate digital technologies into their operations, which includes updating the institution's vision, mission, and objectives to align with digital goals.
Digital Maturity Assessment: A framework used by organizations, including educational institutions, to evaluate their level of technological advancement and integration. It measures the organization's readiness and capability to adopt and utilize digital technologies effectively.
Traditional Learning: A conventional education system where teaching predominantly occurs in classroom settings. This method typically involves direct instruction from a teacher to students who passively receive information through lectures and note-taking, often focused on memorization and repetition.
ChatBot: An AI-driven program designed to simulate human-like conversation based on user inputs. In educational settings, chatbots can function as virtual assistants to provide information, facilitate learning, support administrative tasks, and enhance student engagement by offering instant responses to queries.
Digital Learning Environments (DLEs): Platforms and applications that facilitate digital learning, characterized by integrating technology with educational processes to provide dynamic, personalized, and flexible learning experiences.
Artificial Intelligence (AI): The science and engineering of making intelligent machines, particularly intelligent computer programs, which involves the automation of intelligent behavior and machine learning.
Digital Transformation: The process of using digital technologies to radically change how an organization operates and delivers value to its customers. In the context of higher education, it involves incorporating digital tools and platforms to enhance learning and administrative processes.