AI in Education: Where Are We One Year Later?

AI in Education: Where Are We One Year Later?

Author: Gabrielle Likavec – Teaching and Learning Consultant, Office of Curriculum and Instructional Support

 

In late November 2022, technology made a giant leap. ChatGPT was introduced, and we learned machines could generate human-like text and even have conversations. This leap in capabilities opened doors to both unprecedented opportunities and complex challenges. In the last year, we have delved into these as individuals and as a campus community. As faculty at CMU, integrating generative artificial intelligence (AI) into academic practices offers a path to enhance teaching and learning while navigating the nuances of ethical application and potential biases.

 

The Impact of AI on Academic Practices

AI, particularly through Large Language Models (LLMs) like ChatGPT, has transformed our interaction with information and knowledge creation. These technologies enable us to generate content, facilitate personalized learning, and provide new avenues for research and analysis. However, the integration of AI into educational settings must be approached with an awareness of its limitations and the ethical considerations it entails.

 

Enhancing Instructional Support with AI

AI can be a valuable tool for faculty, assisting in creating teaching materials, inspiring course topics, and even facilitating administrative tasks. For instance, AI-powered tools can help instructors automatically generate high-quality course content, such as quizzes, lectures, assessments, and simulations. This support allows educators to devote more time to interactive and personalized teaching, enriching the educational experience for both teachers and students.

 

AI can also be used to support teachers as they design instruction and assessments to meet the needs of diverse learners. For example, AI could generate a list of real-world examples that help students relate complex concepts to their lived experiences. Or you might use generative AI to brainstorm ideas on explaining concepts in a way that is accessible to all students. This approach can be particularly helpful for a teacher who may notice a student struggling with grasping a concept.

 

Choose an LLM such as ChatGPT, Claude, CoPilot, or Perplexity, and try this example prompt:

Write a script for a 3–5-minute presentation to a university environmental science class about the significance of the UN development goals.

 

Preparing Students for an AI-Integrated World

Incorporating AI into the curriculum is not just about leveraging new tools for efficiency; it’s about preparing students for a future in which AI plays a central role in various sectors. By engaging with AI in the classroom, students can gain familiarity with how AI works and gain basic experience in formulating prompts for AI. This exposure can help students understand the power of AI and find ways to use it effectively.

 

Moreover, AI integration can address diverse learning needs, promote data-driven decision-making, and spur class discussion. Leveraging AI in the classroom can enhance teaching while preparing students for an AI-driven future. For instance, using AI to help polish and refine messaging in a structured course activity prepares students for similar activities within their careers.

 

Choose an LLM such as ChatGPT, Claude, CoPilot, or Perplexity, and try these example prompts:

Can you explain any biases that are present in the passage below?

Can you provide suggestions on how to improve the writing for a scholarly audience?

 

Personalized Learning through AI: An Expanded Perspective

AI-powered personalized learning allows learners to receive training at their own pace and when it’s most convenient for them. AI technology helps predict how people will learn, enabling the creation of material that fits each learner’s goals and past successes. This approach tailors each student’s learning experience to their needs and preferences, thereby personalizing education for every student.

 

Choose an LLM such as ChatGPT, Claude, CoPilot, or Perplexity, and try this example prompt:

Can you give me ideas on how to study for a quiz in a college-level macroeconomics class on the economic impact of blood diamonds? This is based on the lecture and this article [attached] 

 

Artificial Intelligence (AI) is revolutionizing pedagogical methods by enabling the personalization of educational content to cater to individual students’ needs. This personalization is a significant stride towards accommodating diverse learning preferences, making education more accessible and effective for students from various backgrounds. By harnessing AI, educators can create a more engaging and supportive learning environment, fostering a sense of inclusion and equity in the classroom.

 

Choose an LLM such as ChatGPT, Claude, CoPilot, or Perplexity, and try this example prompt:

I am looking for specific ways to personalize a lesson on the nervous system for a university-level anatomy and physiology course. Consider different learning preferences and provide guidance on ensuring content is accessible to all students, including those with disabilities.

 

Considerations and Limitations

In this section, we will look at the complexities of integrating AI in education, focusing on critical areas such as access and equity, the perpetuation of bias and stereotypes, and the implications for originality and authentic learning. By examining these issues, we aim to foster a more inclusive and equitable educational landscape where the benefits of AI can be universally accessed without exacerbating existing disparities.

 

Access and Equity

One of the primary concerns of AI use in the classroom is access. As generative AI becomes more embedded in tools like Microsoft 365 and Adobe, questions arise about whether all students have equal access to these advanced technologies. There’s a risk of students “paying for excellence” by purchasing subscriptions to higher-quality generative models, which could exacerbate educational inequalities. To address this, faculty must be aware of potential access issues and strive to provide equitable AI resources for all students.

 

Bias and Stereotypes

Generative AI is trained on vast datasets that often contain human-produced materials, which include historical biases and stereotypes. This is particularly concerning in educational content, where biased AI could reinforce stereotypes or provide inaccurate information to students. This raises the question of how to prevent AI from perpetuating these issues in educational content. Educators must critically engage with AI outputs, encouraging students to scrutinize AI-generated materials for bias and inaccuracies. This requires a comprehensive approach, including training ourselves to recognize and mitigate AI biases and involving students in discussions about the ethical use of AI.

 

Originality and Authentic Learning

Generative AI can be a valuable educational tool, but it also raises concerns about authentic assessment of student learning. Distinguishing between student-generated work and AI-generated content is challenging, if not impossible. It is challenging to identify AI-generated content, but we must also be aware of the inherent bias of AI detection systems. These systems are often trained on large datasets that may not accurately represent the diverse range of students in higher education. This can result in a disproportionate impact on certain student groups, such as English as a Second Language (ESL) and students with autism spectrum disorder (ASD). There is no magic solution to determining if text was written, or inspired, by AI.  Educators must develop strategies to assess learning authentically, ensuring that students are the true authors of their work and that they are developing critical thinking and problem-solving skills.

 

To address these considerations, educators must thoughtfully adapt coursework to discourage AI misuse and integrate its use in ways that enhance learning outcomes. This includes creating assignments that require higher-order thinking, fostering critical engagement with AI tools, and developing clear guidelines for the responsible use of AI in academic work. By doing so, we can harness the power of generative AI to enrich education while maintaining academic integrity and fostering an equitable learning environment.

 

Toward a Future Integrated with AI

As we look toward the future, integrating AI into academia holds the promise of transforming educational practices in ways that foster deeper learning and innovation. However, this journey requires a commitment to ongoing dialogue, ethical reflection, and equitable access to technology. By embracing AI with a thoughtful and informed approach, CMU faculty can lead the way in shaping an educational landscape that is both technologically advanced and deeply human.

 

The integration of AI in academic settings offers exciting possibilities for enhancing educational outcomes and preparing students for the future. However, it also calls for a nuanced understanding of the technology’s limitations and potential biases. As educators, we are responsible for navigating these challenges thoughtfully, ensuring that our embrace of AI advances our educational mission while upholding our values of integrity, inclusivity, and equity.

 

In a campus-wide initiative launched by the Provost, the Office of Curriculum and Instructional Support, in partnership with Innovation and Online, invites you to participate in the upcoming opportunities planned to encourage thoughtful discussion around AI within the campus community. See CIS Events for registration and session details.

 

References

Collaborating with artificial intelligence? use your metacognitive skills. THE Campus Learn, Share, Connect. (2024, January 29). https://www.timeshighereducation.com/campus/collaborating-artificial-intelligence-use-your-metacognitive-skills

Columbia. (n.d.). Resources and Technology. Columbia CTL. https://ctl.columbia.edu/resources-and-technology/resources/incorporating-generative-ai-teaching/

Gibson, R. (2023, August 14). 10 Ways Artificial Intelligence IS Transforming Instructional Design. EDUCAUSE Review. https://er.educause.edu/articles/2023/8/10-ways-artificial-intelligence-is-transforming-instructional-design

Gillani, N., Eynon, R., & Finkel, K. (2023). Unpacking the “Black Box” of AI in Education. Educational Technology & Society, 26(1), 99–111.

Gobir, N. (2023, October 3). 8 free AI-powered tools that can save teachers time and enhance instruction. KQED. https://www.kqed.org/mindshift/62462/8-free-ai-powered-tools-that-can-save-teachers-time-and-enhance-instruction

K, M. (2023, June 5). How AI is personalizing education for every student. eLearning Industry. https://elearningindustry.com/how-ai-is-personalizing-education-for-every-student

Nieves, K. (2023, June 6). 5 ways to use AI tools to meet students’ needs. Edutopia. https://www.edutopia.org/article/using-ai-tools-differentiated-instruction/

Schroeder, R. (2023, September 15). Preparing students for the AI-enhanced workforce. Inside Higher Ed | Higher Education News, Events and Jobs. https://www.insidehighered.com/opinion/blogs/online-trending-now/2023/09/15/preparing-students-ai-enhanced-workforce

Stanford University. (2023, April 21). AI tools in teaching and learning. Teaching Commons. https://teachingcommons.stanford.edu/news/ai-tools-teaching-and-learning

Leave a Reply

Your email address will not be published. Required fields are marked *