Wimmer & Eberly Active Learning Incubator (WEALI) Fellowship for the Development of Teaching
To encourage and foster the professional development of instructors as educators.
Which active learning strategies work best in particular educational contexts? …for whom? …and why?
Applications due Monday, March 30, 2026, 11:59pm.
Active Learning Incubator Fellows may receive up to $5000 and copious in-kind support from a team of Eberly Center colleagues to:
- participate in a monthly special interest group (SIG) of instructor-scholars discussing peer-reviewed literature on active learning and instructors’ experiences (August 2026 - May 2027);
- design, pilot, and refine inclusive teaching strategies using active learning in a Fall 2026 CMU course enrolling a minimum of 19 students;
- transfer and implement one or more refined active learning strategies to a Spring 2027 CMU course enrolling a minimum of 19 students (Note: Fall 2026 and Spring 2027 courses may differ because active learning strategies are transferable, but neither course may be one the applicant is teaching for the first time);
- measure the impacts on students’ learning and attitudes in the Spring 2027 course; and
- disseminate research findings in the following ways: on the Eberly Center Teaching as Research website, at an Eberly Center event, AND via a submission of a scholarly article to a peer-reviewed journal/conference.
Who is Eligible?
- All CMU instructors of record (faculty, staff, postdoc, graduate students) teaching on the Pittsburgh or Doha campuses are eligible to apply.
- We especially encourage applications from early career faculty members. “Early career” faculty members include those with a continuing appointment (i.e., teaching, tenure, research, or library track instructors) teaching at ÓÕ»óÂÜÀò who have five or fewer years of teaching experience at the university level as the instructor of record, either at Carnegie Mellon or elsewhere.
- Active Learning Incubator proposal ideas must be implemented in a Fall 2026 and a Spring 2027 CMU course (these can be different courses) with expected enrollments of at least 19 students each semester.
- Prior experience with active learning strategies or educational research is NOT required.
- Strong interest in learning about, implementing, and collecting outcomes data on active learning strategies, whether or not your ideas for implementing active learning are fully formed.
- We are interested in seeing the quality of your ideas, and will not be evaluating the quality of your writing. Proposals prepared by generative AI will not be reviewed.
Funding
Fellowship award payments occur in three stages, following successful completion of expected fellowship milestones in Fall 2026 ($1500) and Spring 2027 ($1500) and when dissemination requirements are met ($2000).
Relevant Dates
Expectations for Fellows
Fellows commit to work closely with Eberly Center colleagues as they:
- regularly attend SIG meetings;
- design and teach a Fall 2026 and a Spring 2027 CMU course, with the option of teaching in an Eberly Center classroom designed for active learning (1308 or 1309 Tepper Quad);
- receive individual consultations in Summer 2026, Fall 2026, and Spring 2027 on the implementation of:
- inclusive active learning strategies to target specific, challenging learning objectives, including one to two classroom observations of key class sessions;
- relevant technology-enhanced learning tools to facilitate active learning during class sessions; and
- teaching as research methods and study designs;
- collect, analyze, and interpret data on student outcomes (with Eberly Center assistance) measured in Spring 2027;
- communicate Spring 2027 research findings and lessons learned as enumerated above after Spring 2027.
Application Process
The request for proposals for the 2026-2027 Academic Year is . The deadline for applications is Monday, March 30, 2026, 11:59pm.
Preview the application questions...
Instructor details
Questions 1-3
S27 Course Context
During S27, participants will implement a teaching as research (TAR) study, developed in F26 in collaboration with Eberly Center colleagues. The following questions will be used to evaluate the alignment/suitability of a S27 course that you teach for a TAR study that applies what you learned, piloted, and/or refined earlier in this program.
4. What S27 course number would you (as an instructor or record) propose for this project?
(NOTE: This course cannot be a new prep; i.e., you must have taught this course at least once at ÓÕ»óÂÜÀò prior to S27. This would be the course in which you conduct a teaching as research study, applying what you learned from your F26 teaching experience.)
5. What is the course title for this S27 course?
6. What is the typical enrollment per section of your S27 course (MUST be at least 19 students per section)?
7. How many sections of your S27 course do you expect to teach?
8. Do you expect to teach your S27 course with any co-instructors?
If yes, please identify who they are.
9. What measurable competency(ies) do many of your students struggle with in the S27 course proposed above?
10. Historically, have you observed differences in student learning outcomes in this S27 course (e.g., do some student groups perform differently than others overall or on particular assignments)?
If yes, please briefly describe the observed differences in student learning outcomes (including the relevant assessment/assignment).
11. The previous time you taught the S27 course, what types of in-class instruction and practice did students receive to help them achieve the competency(ies) listed in item 9 above? Check all that apply
- Lectures or guest lectures
- Quizzing and/or testing on the material
- Whole-class discussions
- Small group activities during class (e.g., discussions, think-pair-share, problem solving, role playing, simulations, debates, working in project teams)
- Individual practice activities during class (e.g., clicker questions, individual writing exercises)
- Hands-on laboratory experiences
- Individual presentations
- Group presentations
- On- or off-campus field trips
- Other____
Potential impact of active learning (or a particular implementation strategy) in S27
12. What are 2-3 new active learning interventions (or modifications to strategies you have already tried) that you would be willing to implement during your S27 class sessions that would target (and potentially enhance the development of) the competency(ies) listed in item 9 above? You may refer to .
13. How do you predict that your use of active learning will affect student learning or equity of outcomes in your course?
14. How would you make the implementation of active learning inclusive and accessible for all students?
15. How could you include a comparison group within a course section or across sections (or semesters) to help measure impacts of an active learning intervention (please see the for examples)?
S27 Course Deliverables
16. Which of the following types of assessments/student deliverables are a part of your S27 course? (please check all that apply)
- Quizzes
- Exams
- Papers, essays or written reflections
- Homework assignments or problem sets
- Projects (completed individually)
- Projects (completed in a group)
- Presentations (completed individually)
- Presentations (completed as a group)
- Other ___
F26 Course Context
During F26, participants will practice and refine implementation of active learning strategies in preparation for a S27 TAR study. In F26 and S27, you may teach different courses or the same course. The goal is that your F26 practice will be transferable to your S27 course. The following questions will be used to evaluate the alignment/suitability of a F26 course that you teach to practice and refine active learning strategies with Eberly Center support and feedback.
17. What F26 course number would you (as an instructor or record) propose for this project (i.e., as an opportunity to pilot and refine active learning techniques)?
18. What is the course title for this F26 course?
19. What is the typical enrollment per section of your proposed F26 course (MUST be at least 19 per section)?
20. How many sections of your F26 course will you teach?
21. Do you expect to teach your F26 course with any co-instructors?If yes, please identify who they are.
22. Do students in your F26 course struggle with the same measurable competency(ies) identified in item 9 above (i.e., in your S27 course)?
If yes, which one(s)?
23. To what extent would the active learning strategies identified in item 12 above be transferable (i.e., you could also implement them) for your F26 course?
Informational Interview
24. Due to limits on the number of fellows we can support, finalists may be invited to have a brief informational interview with an Eberly Center colleague to provide additional information to help determine the alignment of their course with this fellowship experience. Please suggest 3 dates/times when you could meet for 30 minutes on Zoom during the month of April 2026.
Any questions about the program may be directed to eberly-assist@andrew.cmu.edu.
Applicants may request a consultation with an Eberly colleague on their project idea and evaluation plan prior to submitting a proposal. Please request a consultation at least one week prior to the submission deadline.
2026-2027 Active Learning Incubator fellows
Jonathan Tsay
Assistant Professor
Psychology
Dietrich College
85-170 Foundations of Brain and Behavior (14-week undergraduate course)
Tsay aims to study the utility of practice exercises before and after active in-class instruction to find the most effective combination of pre-, post-, and in-class active learning. With his graduate teaching assistant, Indranil Nyamsuren, Tsay created a series of online workbooks containing both course content and practice questions to supplement in-class exercises, which include small group discussions and inquiry-based classroom demonstrations. Students will complete workbook questions before, after, or both before and after in-class exercises, with control groups only receiving in-class practice.
Jungwan Yoon
Lecturer
English
Dietrich College
76-107 Writing about Data (7-week undergraduate course)
Yoon modified the in-class active learning activities that build towards the Literature Review & Proposal assignment in her Writing about Data course. While the class already implements active learning, she is interested in whether completing the activities individually versus collaboratively would affect the quality of students’ literature reviews (e.g., synthesis, thematic grouping, critical evaluation).
Bo Zhan
Lecturer
Language, Cultures and Applied Linguistics
Dietrich College
82-278/76-278 Japanese Film and Literature: The Art of Storytelling (14-week undergraduate course)
In her fall incubator semester, Zhan is exploring whether students can better analyze and articulate cultural representation in Japanese film and literature through the use of targeted active learning activities. Currently, she devotes a significant amount of class time to reviewing films and class discussion. However, students do not always leave with a deep understanding of what culture is or the ability to make thoughtful cross-cultural comparisons. In Spring 2027, she plans to incorporate active learning more frequently to target these learning objectives, through activities such as think-pair-share, concept mapping, and reflection.
2025-2026 Eberly Active Learning Incubator Fellows
Alexandra Newby
Assistant Teaching Professor
Chemical Engineering
College of Engineering
Spring 2026
06-262 Mathematical Methods of Chemical Engineering (14-week undergraduate course)
Research Question
- To what extent does regular and varied use of active learning affect mathematical performance compared to a predominantly lecture-based class?
Active Learning Teaching Intervention
Newby redesigned her course to provide early and regular active learning opportunities throughout the semester. She provided intentional framing and strategies to increase transparency around active learning. In each class session, students engaged with multiple active learning experiences. Active learning activities took the form of think-pair-share, concept mapping, small group exercises, and exit tickets.
Study Design
Newby delivered the same course content during the Spring 2025 (control) and Spring 2026 (treatment) versions of her course. In the control semester, Newby used lecturing as the primary pedagogical strategy, including demonstrations, working through problems on screen, and instructor-led concept mapping. In the treatment semester, each class started with an active warm-up activity, some lecture time was replaced with at least one additional active learning experience in which students practiced or discussed the material directly, and each class ended with an exit ticket. Additionally, Newby converted the concept mapping to be completed by students.
Julie Saunders
Assistant Teaching Professor
Human Computer Interaction Institute
School of Computer Science
Spring 2026
05-360/05-660 Interaction Design Fundamentals (14-week undergraduate and graduate course)
Research Question
- To what extent does the quality of teams’ design creations change when a class is taught with more extensive active learning?
Active Learning Teaching Intervention
Saunders increased active learning opportunities for her students by “flipping” her course content. In other words, prior to class sessions, students independently engaged with course material through online learning modules. This allowed students to spend more time engaged in active learning activities during class. Specifically, students practiced evaluating and improving on design principles, providing scaffolding for subsequent student creative work and critiques. Additionally, Saunders spent more time debriefing activities with students to formatively assess and reinforce learning.
Study Design
Saunders delivered the same course content during the Spring 2025 (control) and Spring 2026 (treatment) versions of her course but with different amounts of active learning and different pedagogical implementation of the activities. During the control semester (Spring 2025), Saunders spent part of class time lecturing on course content and then students individually created designs and practiced giving and receiving critiques. In the treatment semester (Spring 2026), Saunders moved lecture content to online learning modules to shift from lecture-based instruction to individual asynchronous active learning. She was then able to spend more class time on scaffolded, collaborative active learning experiences and lead more extensive debriefs. Here, active learning provided targeted practice and feedback on fundamental skills before students attempted more authentic design creations.
Xiaoying Tu
Assistant Teaching Professor
Heinz College of Information Systems and Public Policy
Spring 2026
90-728 Introduction to Database Management (7-week graduate course)
Research Question
- To what extent does regular collaborative active learning affect students’ performance on Structured Query Language (SQL) database tasks compared to previous independent active learning?
Active Learning Teaching Intervention
Previously, Tu’s students completed activities individually (Spring 2025), which he converted into peer-to-peer learning opportunities (Spring 2026) to test the impact of collaborative active learning. For instance, for his in-class polling questions, students historically responded independently and then heard an instructor-led debrief of the correct answer. In the modified format, students first answered individually, then discussed with a peer, and then heard an instructor-led debrief.
Study Design
In both iterations of the course, Tu provided students with lower- and higher-stakes active learning experiences. The lower-stakes activities included in-class SQL exercises with interactive polling. The higher-stakes activities included an in-class coding lab and final exam review exercises. In the treatment course (Spring 2026), students completed these collaboratively with a peer. In the comparison course (Spring 2025), students completed these activities individually without discussing with a peer. In both semesters, students completed assignments and exams on the same course content.
Sample Size: Control (86 students); Treatment (62 students)
Data Sources:
- Average rubric scores for isomorphic questions:
- 7 in-class multiple-choice interactive poll questions (“early” measure)
- 3 midterm exam questions (“mid” measure)
- 1 problem-based final exam question (“final” measure)
Findings:
- RQ1: Students in the collaborative active learning treatment semester (Spring 2026) significantly outperformed students in the comparison semester (Spring 2025).
Figure 1. After controlling for cumulative QPA, collaborative active learning (AL) led to significantly better SQL task performance in the Spring 2026 treatment semester than did individual active learning in the Spring 2025 comparison semester, F(1,145) = 20.92, p < .001, η2p = .13. The main effect of time was also significant, F(1.699,246.331) = 3.91, p = .03, η2p = .03, such that mid performance was higher than both early and final (ps < .001), and early did not differ from final (p = .56). The time x condition interaction was not significant, F(1.699,246.331) = .01, p = .73, η2p = .01, indicating that the pattern of performance over time was similar whether the students were learning collaboratively or independently. Error bars are 95% confidence intervals for the means.
Eberly Center's Takeaways:
- RQ1: Converting existing active learning from independent to collaborative learning experiences significantly improved students’ SQL task performance. In both conditions, lower performance on final exams compared to midsemester measures may be due to differences in the challenge of the SQL questions and/or the high-stakes and cumulative nature of the final exam. Additionally, the positive impact of collaborative active learning occurred in both the morning section of the course that met two times per week and the evening section of the course which met during a single, longer session. Importantly, this small but powerful adjustment to how class time was spent did not require a change to learning objectives, course content, or assessments. These results suggest that instructors can help support their students’ learning by embedding regular active learning opportunities that allow students to learn from each other.
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