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Artificial Intelligence (AI) in Education

Welcome & how to use this guide

Artificial intelligence is a growing area of interest in higher education. This guide aims to review & recommend resources to help faculty with understanding AI in general and start exploring questions about how they want to know about AI.

Use the left-hand column to navigate to your area of interest.

Want to talk with us about AI in education?

Request a consultation with JMU Libraries or the Center for Faculty Innovation (CFI):

  • Use the Libraries’ Consultation and Instruction Request form (select “other”). One of the Libraries’ instructional designers will be able to consult with you learning objectives, instructional strategies, and assessment, with respect to AI in education.
  • Use the CFI’s Teaching Consultations form. The CFI offers individual, departmental, and peer observations to help faculty with teaching.

Definition of AI

Artificial Intelligence (AI) refers to the simulation of human intelligence processes by machines, particularly computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions), and self-correction.

AI is often categorized into two types:

  1. Narrow AI: Also known as weak AI, this type of AI operates under a limited set of constraints and is designed to perform a narrow task, such as voice recognition or driving a vehicle. Most AI that we interact with today, like virtual assistants (e.g., Siri or Alexa), are considered narrow AI.

  2. General AI: Also known as strong AI, this type of AI possesses the ability to perform any intellectual task that a human being can do. It can understand, learn, adapt, and implement knowledge in a way that's not limited to a specific domain. 

AI technologies, such as machine learning, enable systems to learn and improve from experience. They can perform tasks without being explicitly programmed, instead learning from input data and refining their performance over time.

What is generative AI?

Generative artificial intelligence (gAI) is a technology that allows computers to generate text, speech, images, code, etc. that are human-like. ChatGPT, Bard, and Bing are a few examples of gAI tools.

How can AI be used in education?

Artificial Intelligence (AI) has significant potential in reshaping education, making it more personalized, efficient, and inclusive. Some examples include:

  1. Accessibility: AI technologies can help make education more accessible for students with disabilities. For instance, speech-to-text and text-to-speech technologies can aid students with hearing or speech impairments, while AI-driven personalized learning systems can cater to students with learning difficulties. Auto-generated captioning in Zoom is one example of AI in education now.
  2. Graphic design: Options in Microsoft Powerpoint and other systems now use AI to suggest templates and layout for visual layout and graphic design.
  3. Virtual Reality (VR) and Augmented Reality (AR): Though not AI per se, these technologies often leverage AI for creating immersive learning experiences, making education more engaging and interactive.
  4. Personalized Learning: AI can adapt to a student's individual learning pace. By analyzing a student's strengths, weaknesses, and progress, AI can customize content delivery for optimal learning, resulting in personalized education for each student.
  5. Tutoring and Support: AI-driven tutoring systems can provide additional support to students, helping them in subjects where they might struggle. These intelligent tutoring systems can explain concepts, answer questions, provide feedback, and even assess students' understanding of a subject.
  6. Efficiency for Educators: AI can automate administrative tasks such as grading and scheduling, freeing up time for educators to focus on instruction and student interaction. AI can also assist in detecting plagiarism in assignments.
  7. Data-Informed Insights: AI can analyze vast amounts of data to provide insights into learning patterns and trends, helping educators and policy-makers make informed decisions to improve teaching methods, curriculum design, and overall educational policies.
  8. Lifelong Learning and Upskilling: With the rapid pace of technological advancement, continuous learning has become essential. AI-powered platforms can provide personalized, on-demand learning for people at all stages of their career, making it easier for individuals to acquire new skills and adapt to changing job markets.

While AI presents these remarkable opportunities, it's crucial to navigate potential challenges such as data privacy and security, ensuring AI's equitable use, and addressing concerns around the depersonalization of education. As with any technology, the goal should be to use AI to enhance human effort in education, not replace it.

Faculty will need to consider these possibilities as they think about curriculum, teaching, and learning, as they prepare students for an increasing AI-integrated future as citizens and in the workforce.

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