{"id":75633,"date":"2025-01-23T00:26:56","date_gmt":"2025-01-23T05:26:56","guid":{"rendered":"https:\/\/world.edu\/?p=75633"},"modified":"2025-01-23T00:28:29","modified_gmt":"2025-01-23T05:28:29","slug":"ai-in-education-what-those-buzzwords-mean","status":"publish","type":"post","link":"https:\/\/world.edu\/ai-in-education-what-those-buzzwords-mean\/","title":{"rendered":"AI in education: what those buzzwords mean"},"content":{"rendered":"

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You\u2019ll be hearing a great deal about artificial intelligence (AI) and education in 2025.<\/p>\n

The UK government unveiled its \u201cAI opportunities action plan<\/a>\u201d in mid-January. As part of the plan it has\u00a0awarded<\/a>\u00a0funding of \u00a31 million (about US$1.2 million) to 16 educational technology companies to \u201cbuild teacher AI tools for feedback and marking, driving high and rising education standards\u201d. Schools in some US states are\u00a0testing<\/a>\u00a0AI tools<\/a>\u00a0in their classrooms. A\u00a0Moroccan university<\/a>\u00a0has become the first in Africa to introduce an AI-powered learning system across the institution.<\/p>\n

And the theme for this year\u2019s United Nations\u00a0International Day of Education<\/a>, observed annually on 24 January, is \u201cAI and education: Preserving human agency in a world of automation\u201d.<\/p>\n

But what does AI mean in this context? It\u2019s often used as a catch-all term in education, frequently mixed with digital skills, online learning platforms, software development, or even basic digital automation.<\/p>\n

This mischaracterisation can warp perceptions and obscure the true potential and meaning of AI-driven technologies. These technologies were developed by scientists and experts in the field, and brought to scale through big tech companies. For many people, the term AI reminds them of systems like OpenAI\u2019s\u00a0ChatGPT<\/a>, which is capable of writing essays or answering complex queries. However, AI\u2019s capabilities extend far beyond these applications \u2013 and each has unique implications for education.<\/p>\n

I am\u00a0an expert<\/a>\u00a0in AI, machine learning, infodemiology \u2013 where I study large amounts of information using AI to combat misinformation \u2013 knowledge mapping (discovering and visualising the contents of different areas of knowledge), and Human Language Technology (building) models that use AI to advance human language, such as live translation tools. I do all of this as the\u00a0head<\/a>\u00a0of the Knowledge Mapping Lab, a research group within the Faculty of Economics and Management Sciences, and co-director of the\u00a0Interdisciplinary Centre for Digital Futures<\/a>\u00a0at the\u00a0University of the Free State<\/a>.<\/p>\n

In this article I explain the technologies and science behind the buzzwords to shed light on what terms like machine learning and deep learning mean in education, how such technologies can be \u2013 or are already being \u2013 used in education, and their benefits and pitfalls.<\/p>\n

Machine learning: personalisation in action<\/strong><\/h4>\n

Machine learning is a subset of AI involving algorithms that learn from data to make predictions or decisions. In education, this can be used to adapt content to individual learners \u2013\u00a0what\u2019s known as adaptive learning platforms<\/a>. These can, for example, assess students\u2019 strengths and weaknesses, tailoring lessons to their pace and style.<\/p>\n

Imagine a mathematics app that asks questions based on the curriculum, then uses a learner\u2019s answers to identify where they struggle and adjusts its curriculum to focus on\u00a0foundational skills before advancing<\/a>. Although the science is still being explored, that level of personalisation could improve educational outcomes.<\/p>\n

Deep learning: assessment and accessibility<\/strong><\/h4>\n

Deep learning<\/a>\u00a0is a branch of machine learning. It mimics the human brain through neural networks, enabling more complex tasks such as image and speech recognition. In education, this technology has opened new avenues for assessment and accessibility.<\/p>\n

When it comes to assessment, AI-driven tools\u00a0can assist<\/a>\u00a0in marking, analyse handwritten assignments, evaluate speech patterns in language learning, or translate content into multiple languages in real time. Such technologies can both help teachers to lessen their administrative loads and contribute to the learning journey.<\/p>\n

Then there\u2019s inclusivity.\u00a0Speech-to-text<\/a>\u00a0and text-to-speech applications allow students with disabilities to engage with material in ways that were previously impossible.<\/p>\n

Natural language processing: beyond ChatGPT<\/strong><\/h4>\n

Natural language processing is a branch of AI that allows computers to aid in the understanding, interpretation and generation of human language. ChatGPT is the most familiar example but it is just one of many such applications.<\/p>\n

The field\u2019s potential for education is huge.<\/p>\n

Natural language processing can be used to:<\/p>\n