This presentation examines how two Irish universities implemented a collaborative strategy to transition from isolated active learning practices to a scalable ecosystem of Team-Based Learning (TBL). Supported by Pathfinder funding, the project focused on early steps to build capacity, foster cross-campus engagement, and secure institutional commitment.

The work began with a scoping phase to understand staff readiness and identify opportunities for adoption. Introductory workshops across both institutions enabled faculty to experience TBL’s core components, including readiness assurance and team application tasks, while demonstrating how digital tools, such as LAMS, can simplify design and delivery. These sessions generated strong interest among lecturers from diverse disciplines, creating a shared language for pedagogical change.

A major milestone was the launch of a 15-credit Certificate in Team-Based Learning. This program enabled participants to redesign modules, implement TBL in live settings, and join peer-learning communities. Feedback highlighted significant shifts in classroom dynamics as students became more engaged, collaborative, and motivated. Reports of increased belonging and clarity of expectations underscored TBL’s potential to strengthen retention.

Cross-institutional collaboration extended to leadership engagement. Bringing senior university leaders to observe a mature TBL ecosystem in the UK proved transformative. Leaders saw how coordinated strategies, purpose-built spaces, and digital infrastructure enable scaling to thousands of students. This experience validated the vision for an Irish TBL Hub and positioned TBL as an institutional priority.

In a context shaped by generative AI and retention challenges, TBL offers a human-centred response that cultivates judgment, reasoning, and collaboration. This presentation will share lessons from these first steps, illustrating how relational, scaffolded development and cross-campus partnerships can catalyse cultural change and lay the foundation for a national TBL hub.

Faculty effectiveness in Team-Based Learning (TBL) environments depends not only on mastery of instructional design but on the ability to coach learners, cultivate psychological safety, and manage team dynamics that drive performance. However, many educators enter TBL practice with strong content expertise and limited preparation in coaching-oriented facilitation, creating a persistent gap between TBL structure and TBL effectiveness.

This oral presentation introduces a coaching-informed framework that reframes faculty development in TBL from technique acquisition to performance coaching. Drawing on leadership coaching, Process Education, and learning-centered instructional theory, the model positions faculty as facilitators of learner autonomy, accountability, and team reasoning rather than content deliverers. The presentation synthesizes implementation insights from professional healthcare education and leadership development contexts, illustrating how coaching competencies—reflective questioning, structured feedback loops, and team performance coaching—directly influence learner engagement and team effectiveness.

Key outcomes include improved instructor confidence in facilitation, enhanced management of dysfunctional team behaviors, and stronger alignment between TBL design and learner-centered practice. The presentation concludes with transferable design principles and practical implications for scaling coaching-based faculty development across disciplines and institutional contexts.

Traditional methods of presenting clinical cases within TBL Application Exercises often involve lengthy, text-based narratives, which can be overwhelming and lead to passive learning, hindering the effectiveness of collaborative problem-solving. This project addresses the drawbacks of such static case presentations in TBL, including decreased student engagement, limited opportunities for active learning within teams, and a lack of personalized feedback for both individual and team performance.

We have introduced an innovative approach using AI-powered patient personas to create interactive and dynamic clinical simulations specifically designed for TBL Application Exercises.

These AI personas simulate real patient encounters, allowing student teams to conduct medical assessments through direct conversation, collaboratively asking questions, and exploring different diagnostic avenues. This interactive methodology significantly improves learning outcomes in TBL by enhancing student engagement and motivation through active, team participation. Furthermore, it offers a safe and controlled environment for developing crucial communication and interpersonal skills within the team context, as students practice patient-centered communication and adapt their approach based on the AI persona's responses.

The AI can also provide personalized feedback to team performance during the Application Exercise, offering insights into their collaborative diagnostic reasoning and communication techniques. Preliminary findings suggest that this AI-driven approach within TBL fosters deeper understanding of clinical concepts, improves diagnostic accuracy within teams, and cultivates essential professional skills, ultimately better preparing students for real-world clinical practice. This project demonstrates the potential of AI to revolutionize medical education and enhance the TBL framework by creating more engaging, effective, and personalized learning experiences within collaborative settings.

One of the key limitations of the TBL 4S method is the “Specific Choice” component, which constrains responses to predefined options. Despite this feature being explicitly introduced in various Creative Application Exercise (AE) workshops at past TBLC conferences, not a single participant has opted to use it. Instead, facilitators and learners alike tend to favour open-ended responses, which encourage richer, more dynamic discussions.

With advancements in technology, we are now able to leverage Generative AI to automatically summarise vast amounts of team outputs from AEs, enhancing discussion quality and engagement. Even in large-scale TBL settings with 400+ concurrent users, AI-driven summarisation and pattern recognition enable facilitators to efficiently extract key arguments and themes, ensuring that discussions remain meaningful and aligned with learning objectives.

In this presentation, we will demonstrate how Generative AI can assist facilitators in guiding discussions, optimising learner engagement, and maintaining the pedagogical integrity of TBL sessions. Through this approach, we aim to bridge the gap between structured choice and open-ended discussions, ultimately enhancing the overall effectiveness of TBL.

Introduction
Team-Based Learning (TBL) has been used in the MPharm curriculum at the University of Bradford for over ten years, enhancing engagement and achievement. Despite this, some students struggle with foundational knowledge and sustained participation. TBL generates frequent summative diagnostic data through individual readiness assurance tests (iRATs), offering the opportunity to identify disengagement earlier than traditional programmes. This study investigated whether continually monitoring iRAT scores could predict final examination performance, identify at-risk students, and inform timely interventions.

Methods
This two-year study combined quantitative analysis with structured student support. In Year 1, iRAT scores were collated and correlated with end-of-year exam outcomes, and performance was examined by student characteristics, including educational background, disability, gender, age, living area, and home versus international status.

In Year 2, iRAT scores were monitored in real time through a central tracking system. Students scoring below 40% or missing iRATs were flagged for early follow-up. Initial discussions were held with Personal Academic Tutors, with persistent low performance or non-engagement triggering a meeting with an Attainment Officer to develop an action plan.

Results
iRAT scores strongly correlated with final exam performance across two cohorts and modules. Students with low iRAT scores generally performed poorly in the exam, suggesting that gaps in foundational knowledge limited progression. Prior educational background was significant: BTEC-entry (UK vocational qualifications similar to US career and technical education) students consistently scored lower compared to A-Level (UK advanced academic courses similar to specialised Advanced Placements subjects) students. Conversations with struggling students highlighted common challenges, including ineffective revision strategies, poor time management, personal or health issues, and subject-specific difficulties.

Conclusions
iRAT performance is a reliable early indicator of exam success and can guide proactive student support. Continuous monitoring allows timely intervention and identifies groups, particularly BTEC-entry students, who may benefit from targeted academic guidance, helping improve engagement and overall attainment.

Confidence plays a central role in metacognitive regulation, yet most educational research measures it through explicit self-report. Larry Michaelsen and early adopters of Team-Based Learning (TBL) asserted that having students spread points across the options in the multiple-choice questions during the individual Readiness Assessment Test (iRAT) is an implicit measure of confidence.  Very few, if any, studies examine whether this point-spreading technique actually correlates with student confidence. This study examines whether confidence is reflected in students’ response behavior during assessment. Using data from 380 students in an undergraduate TBL courses, we required students to distribute points across multiple answer options and to report their confidence for each question. As hypothesized, we found that ordered logistic regression results indicate that point-spreading entropy is strongly associated with stated confidence: a one-unit increase in entropy corresponds to an approximately 22 percentage-point decrease in the probability of reporting higher confidence, even after controlling for course grade, gender, age, and accumulated academic credits. There is more to the story, however. Exploratory cluster analysis reveals discernible student subgroups, based on their point-spreading behavior and their academic performance. The groups identified include students who express elevated behavioral uncertainty despite average performance and students who exhibit high confidence and decisiveness despite weaker academic outcomes. The existence of clusters suggest that groups of students across observable characteristics might perform different in point dispersion instruments. Taken together, these findings suggest that students’ point-spreading behavior during retrieval contains information related to their reported confidence. In instructional contexts such as Team-Based Learning, point-spreading tasks may have heterogeneous effects in different subgroups of the student population.

Providing accommodations and applying Universal Design for Learning (UDL) are ways in which health science instructors meet the needs of increasing student diversity. The purpose of this study is to investigate the implementation of UDL and accommodations in Team-Based Learning (TBL) and to identify successful strategies, benefits, and barriers to incorporating inclusive design into curricula. 
 
A mixed-methods survey was developed by TBL practitioners and was distributed globally to practitioners of TBL. Open-ended questions assessed motivations, successes and barriers, and examples of effective and ineffective strategies for providing UDL and accommodations. Data analysis is in progress; means and standard deviations will be computed on Likert-scale items and results will be compared with qualitative responses, which will be analyzed using the constant comparative method. 
 
Across the 86 respondents, 35% had used TBL for 2–5 years, 29% for over 10 years, 26% for 6–10 years, and 11% for less than a year. Nearly half of the respondents had training in UDL (49%) and provided accommodations in TBL (56%). Respondents were most aware of time accommodations (96%), followed by reduced distraction testing (69%) and separate testing (67%). Findings revealed substantial variability in the implementation of accommodations and perceived barriers. The most commonly offered accommodations were for the individual Readiness Assurance Test (iRAT) and UDL strategies were applied to the pre-work. Preliminary thematic analysis revealed several barriers to providing accommodations, such as uncertainty surrounding how to modify team-based activities, lack of institutional support, time constraints for implementation, and ensuring fair and equitable accommodations. 
 
The results of this study provided insight into the application of accommodations and UDL strategies to TBL. Flexible options for pre-work and iRAT accommodations were commonly applied strategies that may help scaffold the use of additional accommodations and UDL strategies in TBL and other student-centered activities. 

Students are often apprehensive of group work in academic settings. Yet collaborating with others is key to deep, transformative learning and to professional work. For these reasons, collaborating effectively with others is widely championed as an essential learning outcome in undergraduate programs. Collaborating effectively requires both navigating interpersonal dynamics, cognitive dissonance, and accountability gaps (social complexity) and learning new content or skills (content complexity, task complexity). Team-Based Learning (TBL) offers a pedagogical architecture specifically designed to scaffold the development of skills students need to manage the complexity of collaborative learning and collaborative work.  

Little is known, however, about how students experience the features of TBL as tools to help them manage the complexity of collaboration. We investigated how students experience group work, TBL, and complexities of collaboration, surveying 305 students from undergraduate TBL-based classes about their views of collaborative learning and TBL at three points during the term:  start, mid-point, and end.  

Our results show,  

• at the start of term, fewer students (<23%) enjoyed group work 
• by mid-term and end of term, significantly more students (>41%, >45%) enjoyed TBL 
• students described using features explicitly built into TBL (e.g., intra-, inter-team discussion) and implicitly fostered by TBL (e.g., team decision-making) to successfully navigate complexities of collaborative learning 
• students sometimes experienced TBL as limited and described looking outside class for help with complex content 

We conclude that TBL allows students to build skills they need to navigate social, task, and content complexity, transforming dislike for group work into an enjoyment of productive complexity.  TBL fosters a learning environment that offers students supports they find helpful in navigating and leveraging complexity, but it falls short in providing students with diverse materials they may need to learn complex content; future studies could explore how to incorporate resources students seek outside class.  

As higher education pivots toward student-centered models, the integration of structured pedagogical frameworks is critical for fostering deep learning and professional competency. Drawing upon over a decade of longitudinal research, this presentation examines the intersection of Team-Based Learning (TBL) and flipped teaching as a catalyst for optimizing student engagement and performance. Central to this discussion is the "modified TBL" (mTBL) approach, which utilizes Individual and Team Readiness Assurance Tests (iRAT and tRAT) to enforce accountability and catalyze collaborative problem-solving. This study further investigates how the strategic embedding of retrieval practice within these frameworks strengthens long-term retention and provides faculty with a robust mechanism to mitigate common implementation barriers. By analyzing documented outcomes and faculty perceptions across diverse contexts—including undergraduate STEM and professional graduate programs—this session presents empirical evidence that these high-impact practices significantly improve learning gains and support seamless transitions to hybrid or online environments. 

Introduction
Healthcare professionals increasingly work with complex scenarios, where traits such as ambiguity tolerance, wonder, and intellectual humility may benefit future practitioners in their professional roles. Beyond academic outcomes, Team-Based Learning (TBL) may facilitate professional formation in these areas. This study examined baseline dispositions and TBL experiences among pharmacy students.

Methods
Students from three pharmacy cohorts at two campuses (Duluth and Twin Cities) completed a pre-survey measuring Capacity for Wonder (CfW), Tolerance for Ambiguity (TfA), Intellectual Humility (IH), and six TBL experience items using a 6-point agreement scale (n = 155 / 313). Mann-Whitney U and Kruskal-Wallis tested campus and year differences. Disposition-TBL associations used Spearman correlations with Benjamini-Hochberg false discovery rate adjustment within each TBL outcome. Regression models predicted each TBL item from CfW, TfA, and IH totals.

Results
Baseline TBL perceptions were favorable (means 4.2-5.2/6) with no significant year differences; Duluth students rated several TBL experiences higher than Twin Cities. After adjustment, CfW total was associated with enjoyment, sparked curiosity, overall positive experience, and comfort with ambiguity (rho = 0.215-0.341; q <= 0.0438). TfA total was associated with sparked curiosity, enjoyment, and considering others’ perspectives (rho = 0.211-0.295; q <= 0.0486). IH total was not associated with any outcome after adjustment. In regression models, CfW uniquely predicted enjoyment (beta = 0.262, p = 0.0024) and curiosity (beta = 0.301, p = 0.0004), and TfA uniquely predicted curiosity (beta = 0.226, p = 0.010); IH total did not contribute uniquely.

Conclusions
Wonder and ambiguity tolerance were the dispositions most consistently linked to TBL experiences, while humility total showed limited association. Students who enter TBL with greater curiosity and comfort with uncertainty tend to report a better TBL experience. These findings establish a baseline for planned post-survey analyses evaluating whether TBL exposure is associated with changes in TfA, CfW, and IH.