Call for Proposals

American Indian Higher Education Consortium (AIHEC) Curriculum Development Cohort 1

Purpose

The AIHEC – Curriculum Development

This Call for Proposals (CFP) offers 5 mini-grants for curriculum development in artificial intelligence/machine learning (AI/ML), data science, and health informatics. In partnership with AIHEC and AIM-AHEAD, faculty principal investigators (PIs) from Tribal Colleges and Universities (TCUs) will plan, design, implement, and evaluate a new course or a series of modules developed from an existing course, to include computer and information sciences, engineering, nursing, behavioral and public health, and social science disciplines. The course or series of modules will be shared on the open source AIM-AHEAD Connect platform. PIs will design interactive lessons to include videos, quizzes, progress tracking, assessments, and evaluation. By using the platform's creation tools you can add community forums and engage learners to facilitate an effective online learning experience. Hosting curriculum on the AIM-AHEAD Connect platform is essential because it creates a centralized, accessible, and culturally responsive virtual space where learners can engage with training resources, collaborate with peers, and build connections across disciplines and communities. By placing the curriculum on the Connect platform, students and faculty gain access to materials in data science, AI/ML, health, and related fields, regardless of which TCU they attend. The platform also provides interactive features that encourage discussion, knowledge sharing, and mentorship, allowing learners to apply course content within a supportive community. Working together, we will foster an environment where Indigenous knowledge, tribal data sovereignty, and community priorities can be integrated into the learning experience, ensuring the curriculum remains culturally grounded. This virtual space will expand and strengthen pathways for capacity building, innovation, and sustained impact in advancing data science and health research.

Working closely with the already established TCU Academic Community of Practice (ACP), AIHEC and AIM-AHEAD will ensure that the courses or modular series will adhere to academic standards, align with institutional goals, meet the expectations of regional accrediting bodies, and address the cultural needs of students, surrounding community, and the local workforce. A culturally responsive curriculum can be designed to integrate AI/ML and data science with technical foundations across disciplines while grounding all content in Indigenous knowledge, local priorities, and the principles of tribal data sovereignty. The following examples demonstrate, but are not limited to, how curriculum development courses and module series will be relevant to the AI/AN community: in engineering, computer and information sciences, students would gain experience in programming languages like Python and R and apply AI/ML tools to analyze data sets relevant to tribal communities to examine health outcomes. Nursing coursework would prepare students to use health informatics and predictive analytics alongside culturally safe practices, equipping them to address chronic conditions like diabetes or mental health concerns through approaches that combine biomedical data with Indigenous healing traditions and community-driven wellness initiatives. Behavioral and public health courses would provide students with skills in health promotion, enabling them to utilize AI tools for early disease detection, design culturally grounded prevention programs, and evaluate public health interventions through Indigenous frameworks. Social science courses would strengthen understanding of governance, policy, and ethics, incorporating Indigenous research methodologies, community-based participatory practices, and training in the ethical use of AI and data science to ensure that research and policy development are accountable to tribal nations. Across disciplines, this curriculum emphasizes interdisciplinary collaboration, application of data science tools, and integration of Indigenous ways of knowing, ensuring that students can use AI technologies while upholding tribal sovereignty and advancing solutions to real-world challenges in their communities.

Further, the ACP will provide guidance to ensure curriculum development of the proposed courses or modules series accomplish the following objectives: (1) provide electives in AI/ML and related content to supplement existing health sciences programs; (2) offer courses to all TCU students; (3) provide courses/modules constituting an online certificate program; and (4) prepare TCU students to pursue a related academic track at a regional college or university. Each participating TCU would agree to offer all courses created under this AIHEC and AIM-AHEAD partnership to all other TCUs through the Connect platform. Developed modules may stand alone for a certificate program or existing degree program. Each participating institution can leverage the pool of courses to offer their own personalized certification program or collaborate on a unified certification program. Funds can be leveraged by the PI for course implementation, including instructional design and technical assistance support. The TCU faculty PIs will identify course collaborators, i.e. Subject Matter Experts (SMEs) to assist in course development and implementation. The course collaborator may be a faculty member from a partnering public or private university (non-TCU), bringing SME and complementary resources to strengthen the TCU’s capacity. Through this collaboration, a course or series of modular learning units can be co-developed and carefully adapted to align with a culturally responsive curriculum that reflects Indigenous knowledge systems and community priorities. These modules would integrate topics in AI/ML, data science, and health informatics, ensuring that students gain exposure to technical skills while engaging with case studies and applications relevant to tribal communities. By leveraging both the academic expertise of the partner institution and the cultural context provided by the TCU, the curriculum can foster interdisciplinary learning, uphold tribal data sovereignty, and prepare students to apply emerging technologies in ways that directly benefit their communities. Course collaborators who are not currently affiliated with AIM-AHEAD will receive a $6,000 contract for serving as a consultant to the TCU faculty PI. Course collaborators will be vetted for experience and expertise by the AIM-AHEAD and AIHEC program coordinators. The course collaborator would be expected to commit both time and expertise throughout the process. In the initial stages, the collaborator would commit to working with the PI to design the new course within accreditation guidelines or review the existing course to add appropriate modules—this stage alone could span several weeks of work. The design phase requires focused effort to draft course syllabi, learning objectives, assignments, and projects that are both technically rigorous and culturally relevant, often involving dozens of hours to ensure balance between technical content (such as programming, machine learning, and statistical modeling) and real-world applications are meaningful to students. In addition, course collaborators may spend time working with administrators to ensure alignment and cultural responsiveness where integrating Indigenous knowledge and data sovereignty principles are essential. Beyond development, course collaborators will help refine the course or modules and update content to reflect rapidly changing technologies in data science and AI. To help track the progress of the curriculum development course or modules, the PI will create a simple spreadsheet to document the work and resources required to complete the project. Also, every two weeks, the PI and course collaborator are required to meet with AIHEC and AIM-HEAD advisors to share and discuss their curriculum development progress tracked on the spreadsheet. Taken together, the total time commitment will be extensive, with effort intensifying during key phases of curriculum development, review, and implementation. This level of engagement ensures that the curriculum is not only academically sound but also sustainable, impactful, and deeply connected to the needs of students and their communities.

Background

The AIM-AHEAD program aims to develop new artificial intelligence (AI) talents from all walks of life, support AI health research projects and collaborations with other AIM-AHEAD initiatives to improve the health of all Americans as demonstrated by the over 600 awardees the program has supported thus far. The AIM-AHEAD Coordinating Center (A-CC) was established to broaden representation in the field of AI and machine learning (AI/ML), with an emphasis on promoting health for all. Many communities have untapped potential to contribute new expertise, data, recruitment strategies, and cutting-edge science to the AI/ML field. The A-CC seeks to increase participation in AI/ML through mutually beneficial partnerships, stakeholder engagement, and outreach to advance health access for all. To learn more about AIM-AHEAD, please visit the official website.

The A-CC, a consortium of institutions and organizations that have a core mission to serve Americans impacted by inadequate healthcare resources, consists of four Cores. These Cores will have the following roles in the curriculum development process:

• Administration/Leadership Core - Direct the execution of the Curriculum Development operations and processes, support coach recruitment and program evaluation.
• Data Science Training Core - Identify knowledge gaps, develop and offer training curricula, recruit SMEs, organize networking events, execute and manage the operations of Curriculum Development mini-grants.
• Data and Research Core - Address data needs and facilitate data access for mini-grant awardees.
• Infrastructure Core - Facilitate nationwide outreach, coordination, reporting, and dissemination of research and training programs

Each Core operates as a centralized unit with dedicated responsibilities, resources, and objectives that contribute to AIM-AHEAD’s overall goals and awardee success.

The AIHEC Curriculum Development mini-grants align with the AIM-AHEAD goals by leveraging AIM-AHEAD resources to build courses or a series of modules to begin or expand data science, health informatics, and AI/ML curriculum in TCUs. Curriculum Development mini-grants are well aligned with AIM-AHEAD program objectives.

North Star I: Develop a representative AI/ML workforce with broad participation

North Star II: Increase knowledge, awareness, and national-scale community engagement and empowerment in AI/ML

North Star III: Use AI/ML to improve behavioral health, cardiometabolic health and cancer outcomes for all

North Star IV: Build community capacity and infrastructure in AI/ML to address community-centric non-clinical health factors

Applicant Eligibility Criteria

Applicants must be:

1. A US Citizen, Permanent Resident or Non-Citizen National
• US Citizen: any individual who is a citizen of the United States by law, birth, or naturalization.
• See for further information
• Permanent Resident: a status given to United States immigrants/non-citizen who can legally live in the United States. See for further information
• Non-Citizen National: a person born in an outlying possession of the United States on or after the date of formal acquisition of the United States at birth. See for further information.
2. Able to submit a W-9 tax form
3. Affiliated with a Tribal College and University that is a member of the American Indian Higher Education Consortium (AIHEC)
4. Affiliated with a Tribal College and University that offers one or more of the following programs:
• Academic programs in biomedicine
• Academic majors related to health careers
• Nursing programs
• Computer Science, information systems, or computer technology

Consistent with applicable law, the AIM-AHEAD program will not use the race, ethnicity, or sex (including gender identity, sexual orientation, or transgender status) of prospective program participants or faculty as eligibility or selection criteria.

Curriculum Development Awardee Expectations

Each Awardee will receive:

• A $17,200 stipend.
• In addition, $6,000 for a curriculum collaborator from a non-TCU institution with complementary subject matter expertise.

Curriculum Development awardees are expected to:

• Share course or series of modules on the open source AIM-AHEAD Connect platform.
• Required to write a brief report on the curriculum development process, meeting the milestones and working with the course collaborator.
• Work with course collaborators/subject matter experts who will assist TCU faculty PIs in course or module co-design and implementation.
• Course collaborators will be vetted for experience and subject matter expertise by the AIM-AHEAD and AIHEC program coordinators.
• Track the progress of the curriculum development course or modules by creating a simple spreadsheet to document the work and resources required to complete the project.
• Every two weeks, the TCU faculty PI and course collaborator are required to meet with AIM-HEAD advisors to share and discuss their curriculum development progress.
• Participate in surveys administered by the MayaTech Evaluation Team for the duration of the program as well as post-surveys following completion of the course.
• Participate in “success stories” by providing to AIM-AHEAD case studies demonstrating how individuals or groups have positively benefited from participating in the Curriculum Development program.

The Curriculum Development application process commences in October 2025. The design phase of the course or series of modules, in which learning outcomes are defined, instructional methods are selected, and course structures are developed, will begin in October 2025. PIs and curriculum collaborators will outline what students should know and be able to do by the end of the course. These outcomes guide the selection of topics, sequencing of content, and the development of assessment instruments. All courses will be developed for online delivery using the AIM-AHEAD Connect platform, a virtual community that includes help desks and access to learning management system data, and computing resources for faculty and students. All courses and materials (i.e. video recorded lectures, presentation files, reading materials, and related laboratory/project materials) must be made accessible via the Create Common License.

Evaluation

Throughout the curriculum development process, surveys will be administered at two sperate intervals. First, TCU faculty PIs will provide feedback on the process of building a course or series of modules and the experience of working with a course collaborator. The second survey, administered at 6 months, will measure course satisfaction, attitudes, beliefs, and self-efficacy. AIM-AHEAD will assist in providing evaluation for each course using online survey instruments.  AIM-AHEAD will support the entire process of releasing the Curriculum Development CFP on the InfoReady platform. AIHEC will support the award and tracking of Curriculum Development mini-grant funds. For institutions with multiple awardees, it is anticipated that one award will be granted per institution, and the institution will designate a lead PI who will be responsible for supervising all that institution’s mini-grant awardees to ensure progress and meet reporting requirements. All awardees will be required to attend and present at the AIM-AHEAD Annual Meeting. Beyond the Curriculum Development mini-grants, TCU faculty will be encouraged and supported to benefit from their participation in other AI/ML, data science, and health informatics trainings, fellowships, and access resources available on AIM-AHEAD Connect, and engage in mentorship opportunities.

Curriculum Development Application and Implementation Milestones (Tentative)

Application Components and Submission Guidelines

Applications must address the requirements below and any additional questions via the Curriculum Development Application Form. The applicant should demonstrate his/her association with an AIHEC-affiliated TCU and clearly indicate that one or more of the following academic programs are offered at the applicant’s institution: biomedical sciences, majors related to health careers, data science, nursing, and/or computer science or computer technology.

The applicant must describe his/her commitment to start or expand data science, health informatics and/or AI/ML curricula at his/her TCU and provide a substantial example of the curriculum development course or modules for review by AIM-AHEAD and NIH.

Submission Guidelines

Application Components

Applications should be submitted by October 13, 2025 at 11:59pm ET, using the InfoReady link to upload the following required documents:

• Provide your name, TCU name and address, department, position title, telephone number, email address, and your profile web page.
• Personal Statement: Describe your familiarity with (and/or interest in) AI/ML, health informatics, and data science (maximum 2 pages).
• Biosketch (5 pages limit) in NIH (more information here) or other equivalent format.  A curriculum vitae of 5 pages maximum is acceptable.
• Provide a substantial explanation and example of the curriculum development course or modules for review by AIM-AHEAD and NIH, including how the course or modules will fit in existing or newly-created degree or certificate programs and its target audience (maximum 2 pages).
• Course collaborator: Name, contact information, biosketch, and subject matter expertise for curriculum development.
• One Letter of Recommendation: signed from an appropriate key faculty supervisor demonstrating support for your participation in the program.

Required Format:

Arial font and no smaller than 11 point; margins at least 0.5 inches (sides, top and bottom); single-spaced lines.

Enter your profile information (your name, Tribal College and University, department, position title, telephone number, email address, and your profile web page) on AIM-AHEAD Connect.

Required Elements of the application

Provide a substantial explanation and example of the curriculum development course or modules for review by AIM-AHEAD and NIH (2-page maximum).

Personal Statement (2-page limit maximum)

Your narrative should address the following key areas:

Familiarity and Interest:

• Describe your familiarity with and/or interest in artificial intelligence (AI), machine learning (ML), health informatics, and data science.

Curriculum Development and Collaboration:

• Explain how you plan to collaborate with other faculty to initiate or expand AI/ML, health informatics, and data science curricula at your Tribal College or University (TCU) and beyond.
• Outline specific plans to enhance or introduce AI/ML-related content at your institution, including potential partnerships.

Institutional Need and Capacity Building

• Identify the current need for AI/ML, health informatics, and data science training at your TCU.
• Describe how your efforts will contribute to building institutional capacity in these areas.

Research and Skill Advancement

• Detail your commitment to advancing research skills at your institution, particularly in AI/ML-related fields.

Mentorship and Leadership Development

• Describe how you plan to engage at academic levels by creating mentorship programs and leadership development opportunities.
• Emphasize how you will support the growth of students and junior faculty, particularly those in AI/ML disciplines.

Each application will be independently evaluated and scored by 2 or 3 reviewers. Before evaluating applications, each reviewer must sign a Conflict-of-Interest form affirming that he/she does not have any conflicts of interest. 

The standard NIH 1 to 9 scoring scale, where 1 indicates highest enthusiasm and 9 lowest enthusiasm, will be applied to each scoring criterion. Each reviewer's overall score will equal the mean value of all criterion scores. Each reviewer also will provide at least 2 sentences describing the application’s strengths and weaknesses. This structured approach quantifies the somewhat subjective measure of "interest" but also aligns scores with the program’s strategic goals, ensuring that scores are meaningful and reflective of the applicants' potential contributions to the program.

Criteria for Curriculum Development Participation:

• The applicant clearly articulates a vision to start or expand AI/ML, data science, and health informatics topics or components in curricula at TCUs.
• The applicant provides a substantial explanation and example of the curriculum development course or modules.
• The applicant describes his/her familiarity and/or interest in AI/ML, health informatics, and data science.
• The applicant is focused on building institutional capacity in AI/ML training.
• The applicant demonstrates effort to advance research skills at his/her institution, particularly in fields related to AI/ML.
• The applicant demonstrates engagement in academic levels creating mentorship programs and leadership development for students, junior faculty and researchers, particularly fostering their advancement in AI/ML disciplines.

Outcome: The application's impact score will equal the average of the reviewers' scores. Applications will be ranked from highest interest (lowest score) to lowest interest (highest score).

Funding decisions and Notice of Award dispatch will go out to successful applicants no later than November 3, 2025.

There are currently no informational webinars scheduled.

Questions and Helpdesk

For questions related to the CFP, please contact the Helpdesk at AIHEC Helpdesk.

The Helpdesk will triage all requests and forward project-specific questions to Dr. Erika Symonette Ferguson, AIHEC Project Coordinator as needed.

Program Director

Legand Burge, PhD