AI in Teaching and Learning Scholars Program

The AI in Teaching and Learning Scholars program (ATLS) aims to build a supportive community of faculty who will engage in systematic classroom-based investigation of the impact of AI innovation on teaching and learning. Five Scholars are accepted into the program through an application process.

Participants will design and carry out a study in a course that they teach, present their work, and develop an essay about their work that can be featured on the CATLR website and other media channels.

The 2025-2026 program will focus on the evidence-informed innovation with AI in teaching and learning around four themes (see below). It will run from the middle of October 2025 through the end of September 2026.  

ATLS is a highly collaborative program. Scholars meet online as a group every other week as they design their studies, document and discuss them as they are underway, and identify findings. Because this is a cohort program, you will have an opportunity to share your investigation-in-progress with your Scholar colleagues in order to better make sense of the evidence you gather and refine your work so that it can be shared more broadly in presentations and publications.

We invite participants who are interested in investigating one or more of the following priorities related to AI in teaching and learning: 

• AI-Enhanced Processes for Individualized Learning and Development:
  • Using AI tools to develop specific proficiencies and competencies (e.g., simulations, opportunities to practice key skills)
  • Investigating innovative uses of AI that are intended to help students increase their self-efficacy, motivation, engagement, and learning
  • Personalized AI supports that improve the learning experience and mitigate risks for all students, especially multilingual learners, international students, students with limited prior access to technology, and students with disabilities
• Experiential Learning and Real-World AI Applications: 
  • Integrating AI within community-engaged or industry-partnered projects
  • Co-creating AI tools or resources with students that address pressing needs of populations and communities beyond the classroom
  • Evaluating the impact of student-developed AI tools in applied contexts
• Critical AI Literacies:
  • Systematic examination of teaching and learning strategies intended to cultivate AI literacies (e.g., data, ethics, judgment, creativity)
  • Collaborative approaches in which students and educators critically evaluate AI capabilities, limitations, and biases as they relate to course topics
  • Fostering responsible AI use and digital citizenship
  • Collaborating with students to develop publicly-shared resources for supporting and increasing AI literacy 
• Human-Centered Pedagogy in AI-Enhanced Learning Contexts:  
  • Learning experiences in which interpersonal connectedness and care are motivating factors that influence students’ decisions to use AI appropriately (e.g., teams, peer feedback)
  • Learning experiences where students connect with each other in ways that are exciting and offer opportunities to do things that matter to them within and beyond the classroom 
  • Eliciting and integrating the student perspective on AI into a course (e.g., student-led focus groups, pre-course assignment design with students, co-creation of AI guidelines)
  • Examining the value of faculty-student relationships and mentoring

PROGRAM BENEFITS:

• Receive support from CATLR and Scholars in your study design and implementation.
• Develop your networks in a collaborative community of Northeastern educators.
• Conduct research within your own teaching that can be shared through scholarly conferences, publications, and other media channels.

EXPECTATIONS AND TIME COMMITMENT:

• Attend meetings online with fellow Scholars and the CATLR team during the academic year (60 minutes, every other week). Meetings also often involve pre-work, such as planning exercises and documentation of progress.
• Complete human subjects research training to gain a certificate. Author and submit an IRB proposal for your project by the second week of November 2025.
• Use an online journal in Canvas to document and reflect on your work, receive/provide peer feedback, and store works-in-progress (private within the Scholars group). 
• Conduct a systematic, evidence-based SoTL study of your students’ learning in a course that you teach in winter/spring 2026.
• Author an essay that shares your work publicly with the Northeastern community and share your work at CATLR’s annual conference. See a previous Scholars booklet for examples.
• Participate in CATLR events to share your insights and tips with other educators who are interested in learning about SoTL and conducting their own SoTL projects after completing the program.

STIPEND:

Scholars will receive a stipend of $5,000 per person for full participation in the program.

ELIGIBILITY: 

The ATLS program is open to full-time faculty who teach for-credit courses at Northeastern University. Scholars meetings take place virtually, and we welcome applicants from across all of the Northeastern network. 

ABOUT THE SCHOLARS PROCESS 

We ask that you enter the ATLS program with questions and curiosities about AI in relation to your students and their learning, as opposed to a defined idea for a project (see application details below). You will work with your Scholar colleagues to consider the origin of your questions and curiosities, and the literature that might inform your line of inquiry, as you bring your Scholars project into focus for implementation within your class in Winter or Spring 2026. Over the summer of 2026, you will engage in data analysis and dissemination with the support of CATLR and your Scholar colleagues. 

APPLICATION PROCESS AND SCHEDULE: 

The deadline for applications is September 22, with awards announced early October. Access the application form (opens in new window).

The form will request the following information. Essay portions of the application have a 250-word limit.

• You will carry out your study in a course that you teach. Which of your winter/spring 2026 course(s) will lend themselves to a SoTL/DBER study?
• Have you explored innovative uses of AI in your teaching and learning? If so, how?
• Have you conducted research, presented, and/or published on AI in teaching and learning? If so, please describe your work.
• Which priorities for AI in teaching and learning listed above in the call for application are most interesting to you?
• Please share 2-3 potential areas of investigation within your teaching context and the needs/challenges your work might address.
• Why do you think your potential areas of investigation are important to teaching and learning in the age of AI? How do you see them aligning with the priorities for the Scholars program?
• ATLS is a highly collaborative program. What do you think you would bring to, and how would you benefit from, the Scholars community of practice?
• Your CV or resume
• A letter or email message of support from your department chair or supervisor.

If you have any questions, please email Gail Matthews-DeNatale at [email protected].

Note: ATLS supersedes the Teaching and Learning Scholar Program (access the T&L Scholars program archive that opens in a new tab).