EMERGai
Application
Thank you for your interest in the Expanding the Methods of Education Researchers with Generative AI (EMERGai) Institute. You can submit your application through our Qualtrics form.
We recommend that you review the frequently asked questions below for details about eligibility, the institute structure, stipends, and expectations.
While you can start, pause, and return to this the application form at a later time, we recommend that you prepare your application and submit it in full when you are ready. To help with this process you can download a copy of the application form. You will also need
- Your completed research project proposal, by filling out this template
- Your CV as a PDF (3 pages maximum)
All applications must be submitted by 11:59 PM ET on April 1, 2026. If you have any questions, please contact Clayton Whetung (Research Assistant) at whetu001@umn.edu.
Frequently Asked Questions
The primary goal of the EMERGai Institute is to support early- and mid-career STEM education researchers from resource-limited colleges and universities in effectively, ethically, and responsibly applying Generative Artificial Intelligence (GenAI) tools and processes in their research workflow, including literature review, data collection, data analysis, interpretation, and writing. The institute achieves this by guiding each scholar through the application of GenAI to a STEM education research project of their choice. Please read the FAQs on our website for specific details.
- Early- and mid-career STEM education researchers (e.g., postdoctoral researchers through associate professors, anyone who conducts research as part of their role, or equivalent roles). We define early-and mid-career researchers as those within 14 years of receiving their highest terminal degree.
- Employed at US resource-limited institutions
We define early-and mid-career researchers as those within 14 years of receiving their highest terminal degree.
We define resource-limited colleges and universities as those operating with constrained budgets, smaller/limited endowments, and little infrastructure or support services for advanced research. This may include institutions located in rural or remote regions and smaller public or private colleges or universities with limited capacity for large-scale research initiatives.
We recognize that career paths in academia are not always linear. Extended postdoctoral appointments, career changes, breaks, or late starts to tenure-track positions can mean that years since degree may not fully reflect your career stage. If you are close to the cutoff, we encourage you to apply. Please address your circumstances in your application materials so that reviewers can consider your situation. Note that you will need to confirm your eligibility in the first page of the application form in order to proceed.
We do not maintain a list of resource-limited institutions. Instead, we include a question in the application form that asks you to self-identify and explain how your institution meets this description. We define resource-limited institutions as those operating with constrained budgets, smaller or limited endowments, and little infrastructure or support services for advanced research. This may include institutions in rural or remote regions and smaller public or private colleges or universities with limited capacity for large-scale research initiatives. If you believe your institution fits this description, we encourage you to apply and explain your reasoning in the application. If you are unsure, consider whether factors like limited research funding, minimal grant support infrastructure, high teaching loads, or lack of dedicated research staff affect your ability to conduct research. These are some of the constraints we have in mind, but you may be facing others that are relevant to your context.
No, graduate students are not eligible for this institute.
The institute will accept up to 25 participants.
No. The institute is designed to support researchers at all levels of GenAI familiarity. Prior experience is not a requirement.
No. The institute will provide all participants with no-cost access to GenAI tools with enterprise-grade data protection suitable for research use. This access will be available for the duration of the institute and beyond.
The workshop is free to those selected to participate.
Participants will receive a $1,500 honorarium to support travel and accommodations for the in-person workshop. Participants with higher travel costs (e.g., greater distances or limited regional airport options) may request up to an additional $500, for a total of up to $2,000.
NC State University will provide an honorarium to participants. Non-U.S. citizens are eligible to apply provided they are currently employed by a U.S.-based institution. However, honorarium payments to foreign nationals are subject to eligibility requirements based on visa and tax status. If you are a foreign national, please confirm your eligibility to receive an honorarium from a U.S. institution. If you are a foreign national employed at a U.S. institution and are unsure of your eligibility to receive an honorarium your status may require reimbursement rather than honorarium.
The institute has two phases: a week-long in-person workshop in the summer, followed by an online community of practice during the academic year.
Scholars will propose a STEM education research project as part of their application. If selected, they are expected to attend the in-person workshop, fully participate in the online community of practice, and complete their proposed research project by May 2027.
The application form includes space to upload a research proposal. Download the research proposal template, complete all sections (e.g., research context, research questions, methods, data status), and upload it through the application form.
We understand that your proposed project may involve unpublished work or ideas in early stages of development. Application materials are kept confidential and reviewed only by the institute selection committee. Reviewers are committed to the ethical treatment of shared ideas and will not use, share, or build upon your work.
The in-person workshop follows a progressive structure that moves through the research lifecycle: from building foundational GenAI literacies as they apply to research contexts, to literature review and synthesis, to research methods and data collection, to data analysis, and finally to developing sustainable practices for continued learning. Throughout the week, scholars apply what they learn directly to their own proposed research projects, making concrete progress each day. The curriculum emphasizes hands-on practice, ethical reasoning, and a thoughtful and appropriately skeptical approach to GenAI. All sessions accommodate scholars working with different methods, data sources, and project stages.
During the academic year, scholars participate in virtual gatherings that extend what they learned in the workshop and receive support in completing their proposed project. Gatherings include webinars, facilitated discussions, collaborative exploration, and tool discovery — co-designed with participants based on the group's needs and interests.
Yes. The curriculum is designed to support a broad range of research methods, including quantitative, qualitative, mixed methods, and design-based approaches. You do not need to change your methodology to participate.
Yes. The online community of practice is specifically designed to support you as you apply GenAI within a research project of your choice.
The in-person experience will take place in Raleigh, NC on July 20–24, 2026. Participants should plan to arrive on July 19.
The online community runs from August 2026 through May 2027. Scholars will participate in virtual gatherings featuring webinars, facilitated discussions, and collaborative exploration. Expect approximately 1-2 hours per month.
The application closes at 11:59 PM ET on April 1, 2026.
Successful applicants will be notified by April 24. Selected scholars will need to confirm their participation by April 30.
EMERGai is a partnership between the University of Minnesota and NC State University.
This material is based upon research supported by the National Science Foundation, the Bill & Melinda Gates Foundation, Schmidt Futures, and Walton Family Foundation under the NSF Award, Grant No. 2526452.
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation, the Bill & Melinda Gates Foundation, Schmidt Futures, or Walton Family Foundation