Abstract
Generative AI systems are increasingly present in our daily lives, helping us make crucial decisions. They use machine learning algorithms and tools, fed with millions of data collected from the web, producing entirely new information and generating variations. And this is not just limited to texts — it can produce images, audio, videos, even code, or new programming languages. There are several fields where generative AI can have a considerable impact in the coming years. In this context, the issues proposed in this chapter are: What is generative AI? What is prompt engineering? How to transform education using generative AI and prompt engineering in creating synthetic content? To respond to the research problem, the following objective will be achieved: Investigate how to transform education using generative AI and prompt engineering in the creation of synthetic content. It is concluded that generative AI tools can also help create more efficient exercises. Teachers and educators can use technology to create instructional materials and present summaries of concepts.
TopIntroduction
Within the continuum of human civilization, technological innovations possess profound significance due to their extensive and deep-seated transformative effects. Amidst the precipice of the fourth industrial revolution, a terminology conceptualized by Klaus Schwab, the Founder and Executive Chairman of the World Economic Forum, generative artificial intelligence and immediate engineering emerge as quintessential technological paradigms poised to profoundly transform educational landscapes (Stone et al., 2022). Projections suggest that by 2030, a substantial one-third of professions necessitating a bachelor’s degree will be supplanted by automated systems or sophisticated software (Stone et al., 2022). The speed of technological progress is quickly meeting the previously ambitious standards set for artificial intelligence (AI). According to the AI job replacement theory, the impact of artificial intelligence on the workforce is reshaping occupational roles and this transformation presents both an avenue for innovative advancement and a potential hazard (Huang & Rust, 2018). Certain professions face the potential of becoming obsolete, whereas emergent jobs are projected to arise (Wisskirchen et al., 2017). AI technologies harbor the potential to create new job opportunities and enhance overall productivity (Lazaroiu et al., 2022; Oliinyk et al., 2021). Therefore, the exponential ascent of AI underscores the imperative for a workforce endowed with pertinent competencies to both bolster and navigate this burgeoning domain. Consequently, an AI-integrated era necessitates a citizenry proficient in data literacy, equipped to discern, utilize, interpret, and articulate data insights, and engage constructively in policy discourses influenced by AI (Hoeschl et al., 2017).
Specifically, AI emerges as an instrumental tool within the educational domain, facilitating personalized pedagogical approaches and enhancing learning efficacy (D’Mello et al., 2007; Luckin et al., 2016) and a prompt-based conversational pedagogy that promotes communication and engagement and effectively facilitates teaching and learning may be built by addressing a conversational generative AI carefully, with defined goal, tone, role, and context (Bozkurt & Sharma, 2023). The advent and ascension of the digital era have ushered in a myriad of technological breakthroughs, each systematically reconfiguring frameworks and norms in various domains; nonetheless, the application of Generative AI (GAI) in educational contexts remains in its nascent stages, and the efficacy of AI-generated media in augmenting human learning has yet to be comprehensively explored (Leiker et. al., 2023). OpenAI's tools, such as Dalle-2 and ChatGPT, not only challenge previous notions of AI limitations by enhancing the efficiency of creative media and pedagogical content but also benefit from recent advancements in generative machine learning, especially generative adversarial networks, which have revolutionized the authentic synthesis of digital content (Goodfellow et al., 2014). Technologies underpinned by GAI, which are being integrated across a spectrum of sectors encompassing entertainment, customer services, and marketing (Whittaker et al., 2021), have also notably influenced education, esteemed as a fundamental pillar of societal advancement, reflecting its seamless alignment with these technological shifts.
Key Terms in this Chapter
COVID-19: An infectious condition brought on by the coronavirus that causes severe acute respiratory syndrome (SARS-CoV-2). The most typical symptoms include fatigue, dry cough, and fever.
Educational Transformation: It is the change that takes place in the methodologies applied to the teaching-learning process. These changes are associated with social issues, values and practices that affect the way we teach and learn.
Technology: The term is a product of science and engineering that involves a set of instruments, methods and techniques aimed at solving problems. It is the practical application of scientific knowledge in various areas of research.
Artificial Intelligence: It is a branch of study that focuses on creating software or computers that can execute jobs that are normally performed by humans by artificially duplicating the cognitive capacities of human intelligence.
Education: It is a social practice aimed at developing human beings, their potential, skills and competences. Education, therefore, is not restricted to schools. Education is everyone's right and is aimed at full human development through the teaching-learning process.
Prompt Engineering: the term refers to the practice of creating and optimizing input requests by selecting appropriate words, phrases, sentences, punctuation and separator characters to effectively use LLMs (Large Language Models).
Digital Transformation: It consists of a structural change in the economy, organizations and society in general, caused by the comprehensive application of digital technologies and disruptive technologies.