Artificial Intelligence IN HIGHER EDUCATION

Walking through the upper floors of NAU’s Student Union, a student can be seen working diligently at a study space. On their laptop, they are in the process of asking Open AI’s newly released Chat GPT-4 model why their code is broken, pasting a sample of their script into the text box. Across the room, another student can be seen engrossed in a conversation with GPT, inquiring about the structural differences between triglycerides and cholesterol.

With recent discussion in the media surrounding artificial intelligence, many pose the question on what the landscape of education will look like with AI models such as Chat GPT on the horizon. In reality, artificial intelligence has already vastly permeated into education. With the aptness that trends and information spread with social media, it’s no surprise that for many students at NAU, artificial intelligence is already a mainstay in their tool-set, no different than a calculator, or a protractor.

So what does this paradigm shi in educational technology mean for institutions like NAU?

Many instructors fear that the prevalence of AI will lead to more situations of academic dishonesty, while others proponent AI as a crucial tool that can assist students to develop critical problem solving and analytical skills. From an academic standpoint at NAU, AI can help champion NAU’s vision of personalized a ention to student success by acting as a personal tutor or instructor for many students, especially for those with educational constraints and conflicting factors that may limit access to tutoring and supplemental academic support.

But what about the negatives? Critics argue that AI technology may encourage students to take a more passive approach to their coursework, especially in fields like writing or programming. For instance, why would a student bother to write their own discussion post when a AI service like Chat GPT can do it for them? This criticism is valid, and not without truth behind it. One solution being considered to address this problem is to establish barriers to prevent academic dishonesty while still providing necessary guidance and feedback. This could look something like integrating AI models into coursework and LMS so ware to offer support and feedback, but refraining from assisting unethical requests to falsify work. In fact, several startups have already emerged on the market claiming to provide these services to academic organizations.

Considering how diverse and unique educational institutions and organizations are, it’s unlikely that one single solution would be applicable to use as a broad approach to AI. However, it’s imperative to hold conversations on the topic now, as the benefits and risks of AI in the realm of instruction are becoming increasingly significant.

Coursework aside, there are many other ways in which AI can be leveraged within a university, particularly in the operational and administrative areas of an organization. One of the emerging areas AI is being leveraged across universities is in the realm of admissions and applications. Educause elaborates that AI can help universities understand the unique relationships between data sets when it comes to admissions, finding unique identifiers and probabilities that may not have been uncovered with a human eye.

Being able to leverage AI to be er influence university marketing and engagement can help bolster enrollment and engagement at NAU. Additionally, AI can potentially be leveraged in a similar way to identify key factors on student retention, analyzing data such as learning styles, preferences, and performance to find indicators of at-risk students and help the university be er tailor to multiple learning styles and methodology to be er retain students.

As we enter the renaissance of artificial intelligence, the role of higher education institutions shaping the future of academia and AI will become increasingly critical. As with any new technology, AI brings inherent risks and benefits to be addressed in education, and now is the time to identify ethical and equitable uses of artificial intelligence. In doing so, universities can recognize not only the educational impact, but the potential to drive operational efficiencies and champion student and organizational success.