AI Applications in Education
Artificial Intelligence (AI) refers to algorithms and software in machines or computers that can perform complex or human-like tasks. A key feature of AI systems is that they are designed to adapt or learn from large amounts of data and optimise their performance. This has powerful applications in analysis and automation.
For education this technology enables the possibilities of adaptive learning; tuning content to a student’s ability, and personalised learning; giving the student opportunities to have more autonomy over their own learning and understanding how they learn best. AI could be applied in a wide range of cases from helping adult learners upskill, to empowering children to have more say in their educational journey.
This section describes emerging AI technology and some of its potential applications that could impact educational experiences through the use emerging digital technologies and AI. These general technologies can be adapted or designed for specific use cases or combined to develop new multi-modal tools.
Current Technology
| Terminology | Description | Current Uses | Potential Educational Uses |
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Adaptive Recommendation Algorithms
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Algorithms or software systems which provide suggestions based on a user’s behaviour and interactions on a digital platform. | Recommendation algorithms are currently used in online shopping, social media, and content streaming platforms. | Adaptive and personalised learning recommendations for activities or content, real-time feedback, aid in differentiation of tasks for students. |
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Natural Language Processing
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Algorithms or software, typically using neural network models, that enable computers to interpret and generate human language. | Analysis of text, chatbots, translation between languages, voice command and speech recognition and language generation. | Generation of customised reading passages, writing prompts and co-writing, personalised explanations, voice to text (for accessibility), and feedback through chatbot conversations. |
| Computer Vision | Algorithms or software, typically using neural network models, which enables computers to interpret and identify images or videos. | Labelling and categorising objects or images, facial recognition, motion, or object detection (e.g., in self-driving cars) | Handwriting to text conversion, security, attendance monitoring, facial analysis for engagement. |
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Image Creation
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Computer generated images of still or animated content using software. | Visual content creation in art, media, movies, and video games | Generation of customised images, student-driven content generation, creative practice. |
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Virtual and Augmented Reality
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Computer-generated models or environments which alters a user’s perception through visual immersion or overlays. | Virtual reality (VR) headsets for gaming or training simulations, social media filters, Google maps, virtual avatars of people. | Digital tours, immersive storytelling experiences, 3D models and simulations, teacher training and PLD, virtual tutors. |
On the Horizon
| Terminology | Description | Current and Near Future Uses | Potential Educational Uses |
| Emotional AI (Affective AI) | Affective computing systems aim to recognise or stimulate human emotional responses. | Sentiment analysis of text, facial recognition for expression analysis, eye-tracking for monitoring attention, measurement of physiological signals (e.g., heart rate) to infer emotional state. | Identification of at-risk or high-needs students, surveillance and monitoring of behaviour, emotionally adaptive learning platforms, facilitating social emotional learning. |
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Internet of Things
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Integrated networks of smart devices embedded with sensors and software which collect and exchange data for autonomous monitoring or tasks. | Smart home technology which allows control of appliances remotely, real-time monitoring of manufacturing, logistics or transportation. | Data sharing across institution wide system used for monitoring and decision-making, automated flagging or tracking (e.g., attendance, behavioural). |
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Neurotechnology
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Devices which can interface with the activity of the human nervous system. | Medical devices, control of prosthetics (or other computer systems), imaging or monitoring of brain activity, brain stimulation using electrical or magnetic fields. | Analysis of brain function, regulation of mood states, interpretation and influence of actions, thoughts, or memories. |
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Artificial General Intelligence
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Artificial intelligence that can apply knowledge or skills across a wide range of tasks, unlike narrow AI which is only applicable to a specific domain. | Research areas in this space include reasoning of language models, flexible learning and adaptation, embodied cognition, and consciousness. | Personalised (embodied) conversation, coaching, tutoring, artificial friendship, or relationship building, co-construction of knowledge with machines. |
Last updated: December 21, 2023