Artificial Intelligence and Education
Por Sandra M. Sturla (Centro de Innovación Latinoamericana en Tecnología Educativa, CILTE)
Introduction
In an era where technological advancements continuously reshape our societies, lifelong learning has become an essential strategy for individuals to remain competitive and adaptable in the workforce. Artificial Intelligence (AI), alongside extended reality (XR) and blockchain, is playing an increasingly significant role in transforming education and training. As workplaces evolve and new occupations emerge, the skills and competencies required for professional success are changing at an unprecedented pace (ILO, 2021 in UNESCO 2024). To address this, AI-driven solutions have been developed to support personalized learning pathways and create more flexible educational opportunities.
In this article, we will explore the role of artificial intelligence in education based on UNESCO’s Artificial intelligence, blockchain and extended reality in lifelong learning (2024), summarizing its key ideas and discussing our own experience with AI integration at eABC Learning.
In the aforementioned document, the authors, Hyo-Jeong So with Chohui Lee, Ga Young Lee and Min Jeong Kim undertake a systematic analysis of 102 research articles published between 2018 and 2022 and, as a result, they highlight the growing use of AI in education, particularly in facilitating individualized learning experiences across various learning environments. However, they also point out that, despite its potential, current AI applications often overlook essential andragogical principles, such as the value of adult learners’ prior knowledge and experiences in constructing meaningful learning. Another interesting observation is that research in this field is predominantly led by computer science experts, with limited input from educational scholars, leading to gaps in the alignment between AI-driven learning tools and established educational methodologies.
One important aspect to emphasize is that access to digital learning remains unequal due to economic and infrastructural barriers. The high cost of technological devices and connectivity issues prevent many individuals from fully benefiting from AI-enhanced educational opportunities. In 2022, an estimated 34% of the world’s population lacked internet access, and digital skills were unequally distributed across different regions and social groups (GSMA, 2021; ITU, 2022; UNESCO, 2023a). These disparities highlight the urgent need for governments and educational institutions to promote inclusive policies that ensure equitable access to AI-powered learning tools and resources.
As AI continues to advance, ethical concerns regarding data privacy, bias in training datasets, and the responsible use of technology in education have also emerged. The UNESCO Recommendation on the Ethics of Artificial Intelligence (2021) underscores the importance of AI literacy and calls for public education initiatives to empower individuals in navigating the digital landscape responsibly. Addressing these ethical and practical challenges requires an interdisciplinary approach, involving collaboration among educators, researchers, policymakers, and the technology sector to align AI developments with human-centered learning principles.
This article explores the intersection of AI and education, focusing on the opportunities and challenges presented by AI-driven learning systems. Through an analysis of recent research and policy discussions, it aims to provide insights into how AI can be harnessed to support inclusive, flexible, and ethically responsible education in the digital age.
Understanding Artificial Intelligence
Defining Artificial Intelligence
Artificial Intelligence (AI) was first formally described in 1955 as “the science and engineering of making intelligent machines” (McCarthy et al., 1955, p. 2). Over time, various definitions have emerged, each attempting to encapsulate the complex nature of intelligence and its replication through technology. According to the UNESCO World Commission on the Ethics of Scientific Knowledge and Technology (COMEST), AI involves “machines capable of imitating certain functionalities of human intelligence, including such features as perception, learning, reasoning, problem solving, language interaction, and even producing creative work” (COMEST, 2019). This broad definition highlights AI’s potential to perform tasks traditionally requiring human cognition, making it a transformative force in education and beyond.
The Two Approaches to AI
AI can be categorized into two primary approaches: symbolic (or rule-based) AI and machine learning.
- Symbolic AI: This approach, dominant in the early decades of AI research, is based on predefined rules and logic. It relies on symbols and hierarchical relationships to emulate human reasoning. While symbolic AI allows for transparency in decision-making, it struggles with handling complex, unstructured data, which limits its application in dynamic learning environments.
- Machine Learning (ML): The contemporary AI landscape is largely driven by ML, which enables computers to identify patterns and make predictions based on large datasets. Unlike symbolic AI, ML does not rely on explicit rules but instead “learns” from data, continuously improving its performance through exposure to new information. This capability makes ML particularly useful in education, where personalized learning experiences can be crafted based on student progress and behavior.
Neural Networks and Deep Learning
Machine learning is powered by neural networks, a computational model inspired by the human brain. These networks consist of interconnected layers of artificial neurons:
- Input Layer: Receives raw data.
- Hidden Layers: Process data through multiple computational nodes, adjusting weightings based on prior learning.
- Output Layer: Produces the final result, such as a prediction or classification.
Deep learning, a subset of ML, employs multiple layers of neural networks to enhance learning efficiency. It has been instrumental in advancing AI applications like image classification, speech recognition, and natural language processing. These advancements have profound implications for education, allowing for adaptive learning platforms, automated assessments, and AI-powered tutoring systems.
Generative AI and Its Role in Education
Generative AI is a subset of AI that utilizes machine learning and deep learning techniques to create new content. One of the most well-known generative AI systems is ChatGPT (Generative Pre-Trained Transformer), developed by OpenAI. This technology can generate human-like text, answer questions, and facilitate discussions, making it a valuable tool in education.
Other generative AI models, such as DALL-E, Midjourney, and Stable Diffusion, generate images based on textual descriptions. These models provide innovative ways to support creative and visual learning in educational settings. However, generative AI systems have limitations, including their reliance on pattern recognition rather than genuine understanding. Consequently, the outputs they produce can sometimes be inaccurate or ethically problematic, necessitating human oversight in educational applications.
Human Intervention and Ethical Considerations
Despite its capabilities, AI’s effectiveness is largely dependent on the quality of data it processes and the context in which it is applied. Human intervention remains crucial at various stages, including:
- Data Preparation: Selecting, cleaning, and labeling data to ensure accuracy.
- Algorithm Design and Training: Developing AI models that align with educational objectives.
- Output Evaluation: Assessing AI-generated results to minimize biases and errors.
Ethical concerns also arise regarding data privacy, bias in AI models, and the responsible use of AI-generated content. UNESCO emphasizes the need for AI literacy education to empower users and reduce the risks associated with AI adoption in education (UNESCO, 2021b). Ensuring equitable access to AI-powered tools is equally critical, as digital divides persist across different regions and socioeconomic groups.
By understanding AI’s capabilities, limitations, and ethical implications, educators and policymakers can harness its potential to enhance lifelong learning while mitigating risks. The integration of AI in education must be guided by interdisciplinary collaboration, ensuring that technological advancements align with pedagogical principles and educational equity.
Opportunities and Challenges of AI in Adult Education
Opportunities
Personalized Learning Functions
Artificial intelligence offers key opportunities for lifelong learning, particularly in personalizing education and developing innovative AI literacy tools. Personalized learning enables instruction to be tailored to individual student differences, providing experiences adjusted to their needs and goals.
An example of this is the use of early warning systems in higher education to predict students’ academic performance and take timely corrective measures. During the COVID-19 pandemic, an adaptive online learning model for teachers in Kazakhstan proved to be more innovative than traditional face-to-face courses, despite lower completion rates.
AI has also shown its ability to support marginalized groups, such as immigrants learning a new language. In Canada, a writing system with automated feedback allowed English learners to continue their studies without relying on instructor availability. AI has also been implemented in informal learning environments, such as workplace-based assessments for medical students.
One of the most promising applications of AI is the personalized recommendation of educational resources. Systems like TrueLearn and eDoer use machine learning algorithms to match students with open educational resources (OER) based on their prior knowledge and engagement levels. These technologies help reduce information overload and provide access to more relevant resources for each student.
Promoting AI Literacy for All
AI literacy has become a fundamental aspect of lifelong learning, enabling citizens to understand, evaluate, and use AI critically and ethically. International documents, such as UNESCO’s Beijing Consensus, emphasize the importance of including AI literacy skills at all educational levels.
Innovative initiatives have brought AI education to informal settings, such as museums, where families can engage in game-based learning experiences to understand AI principles. Massive open online courses (MOOCs) have also been developed for public officials, providing practical and accessible content on AI applications in government administration.
Challenges
Ethical Use of AI in Adult Education
The use of AI in education raises significant ethical dilemmas, such as the lack of transparency in algorithms and the use of student data without their knowledge. UNESCO’s Recommendation on the Ethics of AI highlights the need to protect students’ personal information and ensure their right to opt out of data tracking.
A key challenge is the construction of a lifelong learning model that stores data on students’ learning activities over time. However, collecting and analyzing this data on a large scale is complex and requires solutions that balance personalization with student privacy and security.
Limitations in AI Applications for Learning
Despite the growth of AI in education, many applications remain focused on an AI-led teaching model, where students receive content without meaningful interaction. To fully leverage AI in adult education, it is necessary to move toward models where students collaborate with AI or even lead their learning process.
The design of AI-based educational systems should consider approaches that promote creativity, collaboration, and socio-emotional skills. These competencies, which are difficult to automate, will be essential in an ever-evolving job market.
Conclusion
In summary, the UNESCO report highlights the crucial role of digital education in fostering inclusive and equitable learning opportunities worldwide. By addressing challenges such as accessibility, digital literacy, and teacher training, we can ensure that technology serves as a tool for empowerment rather than a barrier. Governments, educators, and stakeholders must work collaboratively to create policies that promote digital inclusion while safeguarding ethical and human rights concerns.
The integration of artificial intelligence in education presents both challenges and opportunities. While it is essential to ensure its use is inclusive, ethical, and aligned with equity principles, AI is also a powerful tool to enhance teaching and learning processes. UNESCO emphasizes the need for appropriate regulatory frameworks and strategies that maximize AI’s benefits without compromising educational quality or student privacy.
Our Experience at eABC Learning
ULIbot: An AI-Powered Chatbot for Education
ULIbot is an artificial intelligence chatbot developed to enhance user interaction within Moodle LMS. Designed by CILTE in collaboration with e-ABC Learning, its primary goal is to provide real-time assistance to students, educators, and administrators by responding to queries instantly. By integrating natural language processing (NLP) and machine learning, ULIbot minimizes the reliance on customer support services, reducing repetitive inquiries and streamlining information retrieval. Available 24/7, the chatbot improves productivity and enhances the overall user experience, allowing learners to focus on their educational journey without unnecessary delays.
The first year of ULIbot’s implementation has shown promising results. Initially launched in April 2024 across more than 40 institutions—including universities, corporate training centers, and medical organizations—the chatbot has significantly improved response times for common inquiries. The first phase targeted Moodle administrators, with subsequent versions planned to support educators and students directly. User feedback has been crucial in refining the chatbot’s capabilities, ensuring that future iterations become even more efficient. The long-term vision includes expanding ULIbot’s functionality to act as a virtual tutor, guiding students through their learning paths and preventing dropout rates by offering timely academic support.
For those interested in exploring this topic further, you can read UNESCO’s original article at the following link: https://unesdoc.unesco.org/ark:/48223/pf0000391599.
Additionally, if you would like to learn about a concrete implementation of AI in education, you can read about ULIbot, an initiative presented at 1er Congreso Internacional en Inteligencia Artificial y Educación (CIIAE), Tandil, Argentina which explores the use of conversational agents in educational environments. More information is available here: https://cilte.org/proyecto-uli-bot-un-chatbot-de-inteligencia-artificial-en-moodle-lms-para-asistir-en-tiempo-real-a-los-usuarios/