Abstract
This chapter explores the dynamic relationship between lifelong learning and AI, highlighting AI's impact on education. It discusses how AI enhances personalized learning, fosters continuous skill development, and addresses ethical considerations like data privacy. The chapter critically assesses challenges such as scalability and resource access in AI's current role in lifelong learning. It also explores the implications of AI integration, including evolving roles for educators and the need for upskilling. Overall, it provides a concise understanding of the connection between lifelong learning and AI, urging stakeholders to embrace AI's transformative potential while considering its ethical implications in education.
TopIntroduction
Technology is becoming a more important mediator of the human activity that underpins learning and work due to the continuous digitalisation of workplaces and educational environments. The rise of digitalisation and the increased emphasis on lifelong learning also coincide. Digitalisation alters human communication, teaching, and learning circumstances from the education standpoint (Håkansson Lindqvist et al., 2024). Many distinct technical developments in education have been seen as signalling the end of traditional education as it exists today. One of the century's most significant innovations has been using artificial intelligence (AI) in education (Becker et al., 2018). Artificial Intelligence (AI) has advanced astoundingly in the last several decades. It is challenging to characterise artificial intelligence (AI) due to the numerous modifications and different development and implementation paths (Luckin & Holmes, 2016). Both (a) human-like thinking and (b) rational behaviour are commonly included as beginning points in definitions (Russell & Norvig, 2010). AI is a phrase used to describe machines (computers) that mimic human cognitive processes like learning and problem-solving or that can handle complexity just as effectively as specialists in human fields.
There is no denying that the widespread adoption of AI in educational practices has offered educators and learners many opportunities for professional and personal growth (Xu & Ouyang, 2021). Diverse viewpoints on the use of AI in education have been documented in the literature (Fahimirad & Kotamjani, 2018; Reiss, 2021), spanning from nonteaching components to personalisation of teaching and learning. Hwang et al. (2020) distinguished four essential functions of artificial intelligence (AI) in education, supported by an applications-based viewpoint that presents AI as an intelligent tutee, learning companion, intelligent instructor, or adviser to policymakers. Artificial intelligence will have a significant impact on education, and AI-based teaching software now often tailors learning to individual needs, connects learners, provides access to digital materials, supports distributed learning, and engages students in meaningful ways. A much greater in-depth understanding of human cognition is needed to use these new insights about human learning in digital learning environments. This includes employing constructivist and active learning methodologies, which have proven significantly more successful. As the integration of personalised and adaptive learning continues to accelerate, smart devices and intelligent technologies are making it possible for an innovative learning environment to successfully support the growth of both. AI methods are critical for assessing collaborative activity, supplying a deeper understanding of human learning, and creating representations and reasoning about these novel cognitive discoveries. AI will revolutionise the field of education. Education aids students in acquiring and expanding upon the body of information a civilisation has amassed. At the same time, artificial intelligence (AI) offers methods for comprehending the workings behind cognition, knowledge, and intelligent action.
Key Terms in this Chapter
Personalised Learning: Tailoring educational content and approaches to individual learners' needs and preferences, often facilitated by technology, to create a more adaptive and effective learning experience.
Ethical Challenges: Moral dilemmas or concerns arising from applying technologies like artificial intelligence require consideration of values, fairness, and responsible use.
Education: The process of acquiring knowledge, skills, values, and attitudes, typically facilitated through teaching, training, or research, with the goal of personal and societal development.
Lifelong Learning: The ongoing, voluntary, and self-motivated pursuit of knowledge for personal and professional development throughout one's life, fostering adaptability in an ever-changing world.
AI Ethics: The study and practice of ethical considerations and principles related to artificial intelligence, addressing issues such as bias, privacy, accountability, and the societal impact of AI technologies.
AIED (Artificial Intelligence in Education): The integration of artificial intelligence technologies into educational settings to enhance learning experiences, personalise instruction, and address long-term educational challenges.
Teaching Strategies: Approaches and methods employed by educators to facilitate learning, including techniques for engaging students, promoting critical thinking, and achieving educational objectives.
21st-Century Competencies: Skills and attributes necessary for success in the modern world, including critical thinking, creativity, collaboration, and adaptability, in response to the demands of the 21st century.
Feat (Fairness, Ethics, Accountability, Transparency): A framework emphasising the importance of fairness, ethics, accountability, and transparency in developing and deploying AI systems.