By Brendan Guenther
As we navigate the rapidly evolving landscape of artificial intelligence in higher education, a new frontier is emerging that may enhance the relevance of these platforms to learning. While chat-based generative AI platforms have stirred up great interest across the sector, the introduction of project-based AI features marks a significant leap forward in our journey towards AI-augmented learning.
Imagine a student embarking on their first literature review. In the past, this process involved hours of painstaking research, note-taking, and synthesis. With platforms like Google’s Notebook LM, SciSpace, or Anthropic’s Claude Projects, our students can curate a collection of relevant papers and articles. An AI chatbot that is both augmented by, and constrained to these resources provided by the student becomes a research tool. These advanced AI environments don’t just store this information, as my reference manager once did, they maintain context across multiple sessions and allow for nuanced, project-specific interactions.
As our student dives deeper into their research, they might query the AI in various ways, all while remaining focused on their specific project. I used to use notecards like this, often adding new relevant metadata as possible themes or ways to slice my resources emerged in my analytical process. The AI, drawing from the curated collection, can help the student test for patterns, suggest connections between seemingly disparate pieces of information, and may help the student identify new avenues of inquiry. This contextual bounding ensures the literature review doesn’t become a linear process through use of a chatbot that produces ever more misinformation. Rather it might encourage a dynamic, iterative exploration of the bounded realm of knowledge selected by the student.
Picture an undergraduate class composed of small teams engaged in a semester-long project on climate change. The students use an AI platform to collect and analyze data from various sources – scientific papers, news articles, policy documents, and more. The AI helps them synthesize this information, offering different perspectives and analytical approaches. It challenges them to think critically, to question assumptions, and to explore the interconnections between different sources and factors. The potential for project-based learning within these new project-focused versions of AI seems interesting, yet also fraught with an ever-deeper level of concerns and questions than the first-generation Gen-AI chatbots surfaced.
As we embrace these seemingly powerful tools, we must also grapple with the ethical considerations they raise. At Michigan State University, we’ve developed comprehensive guidelines for the responsible use of AI in academic settings. These guidelines emphasize the importance of transparency, equity, and academic integrity. Faculty may need to consider these differently in the context of project-based tools.
Instructors are encouraged to develop and clearly communicate course-level AI policies. What role can AI play in project-based assignments? How should AI-assisted work be attributed? Clearly with project-based tools, instructors must address these concerns in the design of the assignment and provide guidance on how to properly use these tools, and when to discard them for traditional research and composition methods. Care must also be taken to help students provide a diverse set of artifacts, conscious of the bias they may introduce to the project by working within their own selected pool of resources.
I’m cautiously optimistic as I watch this new frontier in GenAI emerge. Concerned about the pace of adoption, the uneven availability, and the painful lessons we are sure to learn from early adopters. However, I think this is the tip of the iceberg in terms of relevant innovations that will provide richer and more purpose-built project contextual generative AI. So, I’m hopeful that in time, we will grow accustomed to and skilled in the evaluation and use of such tools as teachers. Such that we create learning environments for students that would have been impossible to imagine several years ago.
Brendan Guenther (he/him) is MSU’s Chief Academic Digital Officer working at the intersection of digital transformation and academic entrepreneurship.