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Artificial Intelligence (AI) in Education at ENMU

Defining AI

AI in Higher Education Panel Discussion and Town Hall, Tuesday, March 26, 2:30-4pm, ENMU Becky Sharp Auditorium


Integrating AI into higher education is not a futuristic vision but an inevitability. Colleges and universities must adapt and prepare students, faculty, and staff for their AI-infused futures. 

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.

Consult the articles below for additional information on defining AI in education:

"AI and the Future of Teaching and Learning: Defining Artificial Intelligence," from the U.S. Department of Education Office of Ed Tech.  2022.

"A Generative AI Primer," Basgen, G. Educause Review, August 15, 2023.  

How can AI be used in education?

"There is a duality of AI on many college and university campuses. On the one hand, some higher education officials are eager to adopt AI tools that would assist with student recruitment and enrollment, but on the other hand, many faculty and other institutional staff believe the use of generative AI is a type of cheating or a breach of academic integrity. What is more ethical: guiding the use of AI tools or pretending they do not exist? Ignoring generative AI or banning its use on the academic side of higher education seems naïve and possibly misguided. Shouldn't higher education institutions be preparing graduates to work in a world where generative AI is becoming ubiquitous? In 2022, the United Nations Education, Scientific and Cultural Organization (UNESCO) recommended that member states 'work with international organizations, educational institutions, and private and non-governmental entities to provide adequate AI literacy education to the public on all levels in all countries in order to empower people and reduce the digital divides and digital access inequalities resulting from the wide adoption of AI systems.'"

Empowering our students, faculty and staff with digital literacy education directly correlates to the ENMU Mission. 

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

1. Personalized Learning: AI can adapt to a student's individual learning pace and style. By analyzing a student's strengths, weaknesses, and progress, AI can customize content delivery for optimal learning, resulting in personalized education for each student.

2. 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.

3. 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.

4. 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.

5. 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.

6. 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.

7. 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.

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.

"Integrating Generative AI into Higher Education: Considerations," Hodges and Ocak, Educause, August 30, 2023. 

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Creative Commons License This work is a remix of the original guide created by the University of New Mexico Library.  This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. You are welcome to use, remix, and share with attribution.