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'''AI-based technologies,''' or artificial intelligence, are those that use artificial intelligence and machine learning algorithms to enable interactions between learners and teachers. AI-based [[Educational technology|educational technologies]] are often also known as '''machine learning''' algorithms. Common applications of AI in education are '''content generation, chatbots, digital agents, and complex analysis'''. <br />
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==Definition==<br />
'''Artificial intelligence (AI)''' [[Educational technology|technologies]] in education are computer software applications that can identify patterns in large amounts of [[data]]. They take an input of some kind (for example [[Text and hypertext|text]] or an image) and output a result based on how the AI software is programmed.<br />
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AI is based on '''algorithms''', or sets of computer-based rules that process information that is input to give a specific desired output. The computer is given some kind <br />
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AI technologies are also often called '''machine learning (ML)''' approaches. Machine learning is a way to describe the process that computers can "learn" how to interpret data and find patterns so that they output a desired result (based on how these computers are programmed).<br />
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==Additional Information==<br />
AI and machine learning is used in educational contexts to have computers do complex tasks when they are given certain inputs, like text, images, or multimedia. For instance, in the case of AI-based educational '''chatbots''', when a participant inputs text into a chatbot window, the AI software will ideally return text back to the participant in a way that resembles a person talking. <br />
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AI and ML technologies are most often used to identify patterns in data so that the technology can make a decision and return the desired result. <br />
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AI and ML applications are most often used in education to analyze text, interpret language, and generate responses to a participant interacting with the computer. In other words, the goal is to have the computer to ''understand'' what the participant is saying and provide a useful response back to the participant. The computer can also make decisions based on what is input, such as interpreting commands from a participant.<br />
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A good example of AI/ML technologies in everyday life are the voice command and virtual assistant software from Amazon Alexa, Apple's Siri, and Google Assistant. A user will give a voice command and then the computer analyzes the speech, identifies what was said, and then completes an appropriate response. In many cases, the computer will also respond back to the user telling them what they did, in plain language.<br />
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Some applications of AI/ML in education have seen the technologies used for [[Dialogue in learning|'''conversation''']] among learners and computers. As [[social learning]] generates high degrees of understanding in learning contexts, it is desirable to provide [[Dialogue in learning|conversational opportunities]] to learners, especially when there are no other peers available. AI/ML researchers seek to develop learning products where learners can [[Interaction|interact with computers]] in a realistic way and hold sustained conversations - all while the computer is understanding, processing, and appropriately responding to the learner.<br />
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Common applications of AI/ML in education include:<br />
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*'''Generative content creation''', in which the AI software creates new text, images, or other media based on prompts and input given to it by the user. In modern Large Language Model (LLM) AI software, the content that is created is very convincing, appearing much like human-generated writing and art.<br />
*'''Chatbots''' in which a computer is able to understand and respond to conversations with human participants<br />
*'''Digital agents''', which are computer programs that independently and continuously operate and are programmed to do tasks for learners or teachers, or to play a specific role in the learning experience (such as by playing a character in an educational roleplaying game).<br />
*'''Categorization''' of data and inputs to help people sort and analyze information<br />
*'''Virtual assistants''' to help with classroom organization, planning, and orchestration<br />
*'''Identifying patterns and analyzing data''' within analytics systems and large data sets, particularly on how people use educational technology<br />
*'''Personalized learning and teaching''' of concepts to learners when the teacher is not around by understanding learner's responses and determining appropriate next course of action<br />
*'''Grading''' of written and other types of assignments, where the computer interprets text and grades based on an established set of rules and rubrics (i.e., this was commonly found in the written portion of the GRE graduate school admissions test and many other tests)<br />
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It is anticipated that AI/ML applications for education will expand greatly in the near future, as computing power improves and the technologies that support developing AI/ML also improve. <br />
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It is also speculated that AI/ML will play a prominent role in [[Web3|web3 applications]] by providing digital characters or "beings" in [[virtual reality]] spaces or the [[metaverse]]. As the technology for language processing improves, virtual characters and digital agents may become commonplace in such virtual environments.<br />
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==Tips and Tricks==<br />
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*AI/ML is still in its infancy in education in comparison to the commercial world, but it is not a new field of research. Not many applications have been developed, but there is a long running research field in education related to artificial intelligence and machine learning. Because education works a lot with informational sources in text and video, it would be very valuable to have AI/ML tools that can help manipulate informational resources and connect learners with information.<br />
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==Related Concepts==<br />
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*Educational technology<br />
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==Examples==<br />
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*None yet, check back soon!<br />
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==External Resources==<br />
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None yet, check back soon!</div>Drriel