SPARK Lab
Student Perspectives on AI Research & Knowledge
The SPARK Lab will work with individual students who wish to take a leadership role, either for their own personal or professional development, and ensure they have sufficient time and academic schedule to center themselves around a collective project or lab administration. Leaders will be asked to collaborate with their team (even if that is a team of one), provide bi-weekly updates to the PI and chart their short and long-term goals they hope that the program will satisfy. All labor in the SPARK Lab will be aligned as much as possible with each member’s strengths, passions and pursuits. The PI benefits only if each member can satisfy their individual interests and intellectual growth. This will not be a factory or assembly line. It will serve exclusively as a generator for each student’s scholarly ambitions around learning and AI. All disciplines are welcome and encouraged to apply.
Student Research
- Evaluate the utility of AI for specific aspects of learning
- Critically analyze the role of AI formats and their impact on student trust of technology
- Design and implement interventions to gauge student trust in AI for learning
Guidelines / Policies
Our lab operates on two principles/policies:
- Students will drive and lead projects. They can certainly support existing projects, but the only lines of inquiry we pursue will be ones that are meaningful to the lab members.
- Any projects must include specific conclusions around improving student learning and must involve student perceptions in some form or another.
Interested students, staff and faculty are encouraged to contact Dr. David Nelson (nelson8@purdue.edu).
Pathways to Scholarly Project Completion
Guides for fellow students, guides for instructors who wish to respond to AI (within specific disciplines, in partnership with faculty and instructors). Students would complete a reflective analysis of the choices made, how the literature supports the claims in the guides, and how the guide will specifically improve student learning. Students will also attend an organized scholarly session at Purdue or elsewhere so they can convey their research to a professional audience.
Both dynamic and static opportunities to connect with their peers and instructors at Purdue about their pedagogical choices in the AI Era. This could be something as simple as an open house session with practical and evidence-based suggestions for learning with and in response to AI. Or it could be a more formal faculty learning community where these students would facilitate reflective opportunities for faculty to ideate on AI in their course design. These would require literature reviews and synthesis of emerging scholarship around AI and learning. Students will also attend an organized scholarly session at Purdue or elsewhere so they can describe their work and the potential benefits to instructors who might wish to replicate their suggested approaches.
Assuming leadership roles and advancing existing student initiatives like BoilerByte. Crafting new projects for peers or instructors in response to changing needs and technological advancements. Projects would require students to pursue a specific line of scholarly inquiry or respond to an expressed scholarly problem, with analysis of the effectiveness of their program on that line of inquiry/problem. Students might engage directly with Purdue administrators in their college, the JMHC, or Teaching & Learning broadly to share and discuss the likely benefit to Purdue students and instructors when considering AI in pedagogical and learning choices.
Partnering with faculty and instructors as associates in course design/administration to foster improved teaching with and in response to AI. Students may also conduct original lines of inquiry around AI and pedagogy with these faculty affiliates, gathering and evaluating data around the effectiveness of specific interventions or practices in a specific course or set of courses.