A-SOiD, an active-learning platform for expert-guided, data-efficient discovery of behavior.

To identify and extract naturalistic behavior, two methods have become popular: supervised and unsupervised. Each approach carries its own strengths and weaknesses (for example, user bias, training cost, complexity and action discovery), which the user must consider in their decision. Here, an active-learning platform, A-SOiD, blends these strengths, and in doing so, overcomes several of their inherent drawbacks. A-SOiD iteratively learns user-defined groups with a fraction of the usual training data, while attaining expansive classification through directed unsupervised classification. In socially interacting mice, A-SOiD outperformed standard methods despite requiring 85% less training data. Additionally, it isolated ethologically distinct mouse interactions via unsupervised classification. We observed similar performance and efficiency using nonhuman primate and human three-dimensional pose data. In both cases, the transparency in A-SOiD's cluster definitions revealed the defining features of the supervised classification through a game-theoretic approach. To facilitate use, A-SOiD comes as an intuitive, open-source interface for efficient segmentation of user-defined behaviors and discovered sub-actions.

Active reinforcement learning versus action bias and hysteresis: control with a mixture of experts and nonexperts.

Active reinforcement learning enables dynamic prediction and control, where one should not only maximize rewards but also minimize costs such as of inference, decisions, actions, and time. For an embodied agent such as a human, decisions are also shaped by physical aspects of actions. Beyond the effects of reward outcomes on learning processes, to what extent can modeling of behavior in a reinforcement-learning task be complicated by other sources of variance in sequential action choices? What of the effects of action bias (for actions per se) and action hysteresis determined by the history of actions chosen previously? The present study addressed these questions with incremental assembly of models for the sequential choice data from a task with hierarchical structure for additional complexity in learning. With systematic comparison and falsification of computational models, human choices were tested for signatures of parallel modules representing not only an enhanced form of generalized reinforcement learning but also action bias and hysteresis. We found evidence for substantial differences in bias and hysteresis across participants-even comparable in magnitude to the individual differences in learning. Individuals who did not learn well revealed the greatest biases, but those who did learn accurately were also significantly biased. The direction of hysteresis varied among individuals as repetition or, more commonly, alternation biases persisting from multiple previous actions. Considering that these actions were button presses with trivial motor demands, the idiosyncratic forces biasing sequences of action choices were robust enough to suggest ubiquity across individuals and across tasks requiring various actions. In light of how bias and hysteresis function as a heuristic for efficient control that adapts to uncertainty or low motivation by minimizing the cost of effort, these phenomena broaden the consilient theory of a mixture of experts to encompass a mixture of expert and nonexpert controllers of behavior.

Simultaneous multidimensional impacts of active learning revealed in a first implementation in the MENA region.

Enhancing science education in developing countries has been a focal point of many studies and efforts, but reform has mainly been driven by top-down approaches that often face impediments. A shift to active learning pedagogies can potentially address these challenges, but it has thus far been predominantly implemented and understood in developed countries. Thanks to the growing accessibility of open education resources and ubiquitous technologies, education reform can now be carried out from the bottom up. Here, we present the results of a two-year implementation of active learning in five core physics and astronomy courses comprising 2,145 students from the Middle East and North Africa (MENA) region. Simultaneous improvements are observed in both students' performance and their perception of the quality of learning; means improved by 9% (0.5 SD) and 25% (1.5 SD), respectively. The performance gap between students in the bottom quartile and those in the top quartiles was narrowed by 17%. The failure rate was reduced to a third of that in traditional classes; this is 36% better than the results in developed countries, indicating a greater need for active pedagogies by MENA students. Our findings reveal a multidimensional positive influence of active learning, the viability of its grassroots implementation with open resources, and its sustainability and reproducibility. We suggest that wider implementation can boost education-driven economic growth by 1% in per capita gross domestic product [GDP], substantially cut costs of repeating courses, and produce a more competent STEM workforce-all of which are urgently needed to stimulate development and growth.

Efficient sampling-based Bayesian Active Learning for synaptic characterization.

Bayesian Active Learning (BAL) is an efficient framework for learning the parameters of a model, in which input stimuli are selected to maximize the mutual information between the observations and the unknown parameters. However, the applicability of BAL to experiments is limited as it requires performing high-dimensional integrations and optimizations in real time. Current methods are either too time consuming, or only applicable to specific models. Here, we propose an Efficient Sampling-Based Bayesian Active Learning (ESB-BAL) framework, which is efficient enough to be used in real-time biological experiments. We apply our method to the problem of estimating the parameters of a chemical synapse from the postsynaptic responses to evoked presynaptic action potentials. Using synthetic data and synaptic whole-cell patch-clamp recordings, we show that our method can improve the precision of model-based inferences, thereby paving the way towards more systematic and efficient experimental designs in physiology.

Outcomes of the MAMA Training: A Simulation and Experiential Learning Intervention for Labor and Delivery Providers to Improve Respectful Maternity Care for Women Living with HIV in Tanzania.

Respectful maternity care (RMC) for women living with HIV (WLHIV) improves birth outcomes and may influence women's long-term commitment to HIV care. In this study, we evaluated the MAMA training, a team-based simulation training for labor and delivery (L&D) providers to improve RMC and reduce stigma in caring for WLHIV. The study was conducted in six clinical sites in the Kilimanjaro Region of Tanzania. 60 L&D providers participated in the MAMA training, which included a two-and-a-half-day workshop followed by a half-day on-site refresher. We assessed the impact of the MAMA training using a pre-post quasi-experimental design. To assess provider impacts, participants completed assessments at baseline and post-intervention periods, measuring RMC practices, HIV stigma, and self-efficacy to provide care. To evaluate patient impacts, we enrolled birthing women at the study facilities in the pre- (n = 229) and post- (n = 214) intervention periods and assessed self-reported RMC and perceptions of provider HIV stigma. We also collected facility-level data on the proportion of patients who gave birth by cesarean section, disaggregated by HIV status. The intervention had a positive impact on all provider outcomes; providers reported using more RMC practices, lower levels of HIV stigma, and greater self-efficacy to provide care for WLHIV. We did not observe differences in self-reported patient outcomes. In facility-level data, we observed a trend in reduction in cesarean section rates for WLHIV (33.0% vs. 24.1%, p = 0.14). The findings suggest that the MAMA training may improve providers' attitudes and practices in caring for WLHIV giving birth and should be considered for scale-up.

ChemSpaceAL: An Efficient Active Learning Methodology Applied to Protein-Specific Molecular Generation.

The incredible capabilities of generative artificial intelligence models have inevitably led to their application in the domain of drug discovery. Within this domain, the vastness of chemical space motivates the development of more efficient methods for identifying regions with molecules that exhibit desired characteristics. In this work, we present a computationally efficient active learning methodology and demonstrate its applicability to targeted molecular generation. When applied to c-Abl kinase, a protein with FDA-approved small-molecule inhibitors, the model learns to generate molecules similar to the inhibitors without prior knowledge of their existence and even reproduces two of them exactly. We also show that the methodology is effective for a protein without any commercially available small-molecule inhibitors, the HNH domain of the CRISPR-associated protein 9 (Cas9) enzyme. To facilitate implementation and reproducibility, we made all of our software available through the open-source ChemSpaceAL Python package.

From UK-2A to florylpicoxamid: Active learning to identify a mimic of a macrocyclic natural product.

Scaffold replacement as part of an optimization process that requires maintenance of potency, desirable biodistribution, metabolic stability, and considerations of synthesis at very large scale is a complex challenge. Here, we consider a set of over 1000 time-stamped compounds, beginning with a macrocyclic natural-product lead and ending with a broad-spectrum crop anti-fungal. We demonstrate the application of the QuanSA 3D-QSAR method employing an active learning procedure that combines two types of molecular selection. The first identifies compounds predicted to be most active of those most likely to be well-covered by the model. The second identifies compounds predicted to be most informative based on exhibiting low predicted activity but showing high 3D similarity to a highly active nearest-neighbor training molecule. Beginning with just 100 compounds, using a deterministic and automatic procedure, five rounds of 20-compound selection and model refinement identifies the binding metabolic form of florylpicoxamid. We show how iterative refinement broadens the domain of applicability of the successive models while also enhancing predictive accuracy. We also demonstrate how a simple method requiring very sparse data can be used to generate relevant ideas for synthetic candidates.

Active Learning-Based Guided Synthesis of Engineered Biochar for CO2 Capture.

Biomass waste-derived engineered biochar for CO2 capture presents a viable route for climate change mitigation and sustainable waste management. However, optimally synthesizing them for enhanced performance is time- and labor-intensive. To address these issues, we devise an active learning strategy to guide and expedite their synthesis with improved CO2 adsorption capacities. Our framework learns from experimental data and recommends optimal synthesis parameters, aiming to maximize the narrow micropore volume of engineered biochar, which exhibits a linear correlation with its CO2 adsorption capacity. We experimentally validate the active learning predictions, and these data are iteratively leveraged for subsequent model training and revalidation, thereby establishing a closed loop. Over three active learning cycles, we synthesized 16 property-specific engineered biochar samples such that the CO2 uptake nearly doubled by the final round. We demonstrate a data-driven workflow to accelerate the development of high-performance engineered biochar with enhanced CO2 uptake and broader applications as a functional material.

The outcomes of team-based learning vs small group interactive learning in the obstetrics and gynecology course for undergraduate students.

INTRODUCTION: Team-based learning (TBL) is a well-established active teaching method which has been shown to have pedagogical advantages in some areas such as business education and preclinical disciplines in undergraduate medical education. Increasingly, it has been adapted to clinical disciplines. However, its superiority over conventional learning methods used in clinical years of medical school remains unclear. The aim of this study was to compare TBL with traditional seminars delivered in small group interactive learning (SIL) format in terms of knowledge acquisition and retention, satisfaction and engagement of undergraduate medical students during the 6-week obstetrics and gynecology clerkship. MATERIAL AND METHODS: The study was conducted at Karolinska Institutet, a medical university in Sweden, and had a prospective, crossover design. All fifth-year medical students attending the obstetrics and gynecology clerkship, at four different teaching hospitals in Stockholm (approximately 40 students per site), in the Autumn semester of 2022 were invited to participate. Two seminars (one in obstetrics and one in gynecology) were designed and delivered in two different formats, ie TBL and SIL. The student:teacher ratio was approximately 10:1 in the traditional SIL seminars and 20:1 in the TBL. All TBL seminars were facilitated by a single teacher who had been trained and certified in TBL. Student knowledge acquisition and retention were assessed by final examination scores, and the engagement and satisfaction were assessed by questionnaires. For the TBL seminars, individual and team readiness assurance tests were also performed and evaluated. RESULTS: Of 148 students participating in the classrooms, 132 answered the questionnaires. No statistically significant differences were observed between TBL and SIL methods with regard to student knowledge acquisition and retention, engagement and satisfaction. CONCLUSIONS: We found no differences in student learning outcomes or satisfaction using TBL or SIL methods. However, as TBL had a double the student to teacher ratio as compared with SIL, in settings where teachers are scarce and suitable rooms are available for TBL sessions, the method may be beneficial in reducing faculty workload without compromising students' learning outcomes.

International short-term placements in health professions education-A meta-narrative review.

INTRODUCTION: In order to be prepared for professional practice in a globalised world, health professions students need to be equipped with a new set of knowledge, skills and attitudes. Experiential learning gained during an international placement has been considered as a powerful strategy for facilitating the acquisition of global health competencies. The aim of this review was to synthesise the diverse body of empirical research examining the process and outcomes of international short-term placements in health professions education. METHODS: A systematic review was conducted using a meta-narrative methodology. Six electronic databases were searched between September 2016 and June 2022: Medline, Embase, CINAHL, PsycINFO, Education Research Complete and Web of Knowledge. Studies were included if they reported on international placements undertaken by undergraduate health professions students in socio-economically contrasting settings. Included studies were first considered within their research tradition before comparing and contrasting findings between different research traditions. RESULTS: This review included 243 papers from 12 research traditions, which were distinguished by health profession and paradigmatic approach. Empirical findings were considered in four broad themes: learner, educational intervention, institutional context and wider context. Most studies provided evidence on the learner, with findings indicating a positive impact of international placements on personal and professional development. The development of cultural competency has been more focus in research in nursing and allied health than in medicine. Whereas earlier research has focussed on the experience and outcomes for the learner, more recent studies have become more concerned with relationships between various stakeholder groups. Only few studies have looked at strategies to enhance the educational process. CONCLUSION: The consideration of empirical work from different perspectives provides novel understandings of what research has achieved and what needs further investigation. Future studies should pay more attention to the complex nature of the educational process in international placements.

Livestreaming clinical experience to remotely located learners: A critical narrative review.

CONTEXT: Medical education relies on real patient learning (RPL) to provide medical students with essential clinical experience. However, growing demand for clinical placements continues to be a challenge in providing sufficient RPL opportunities. The COVID-19 pandemic forced academic institutions to rethink the delivery of traditional clinical training and innovations in online clinical learning experiences, specifically livestreamed clinical experiences, have emerged which show promise in addressing the capacity limitations of traditional placements. Although previous reviews have explored the use of livestreamed clinical experiences during the pandemic, there is a lack of rigorous theoretical framing to support these innovations. OBJECTIVES: The aim of this review is two-fold: to examine the effectiveness of livestreamed clinical experiences through an experience-based learning (ExBL) theory perspective and to provide practical recommendations to optimise and implement these innovations. METHODS: A review of literature was conducted to identify journal articles published between September 2019 and January 2023 reporting on innovations relating to livestreamed clinical experiences. The search focused on undergraduate and postgraduate medical education but relevant evidence from other healthcare professions were also included due to a limited evidence base. Strengths and weaknesses were derived from the literature and analysed in relation to ExBL components. RESULTS: Principal strengths of livestreamed clinical experiences included expanded access to RPL opportunities and medical specialties, enhanced standardisation of learning experiences and positive perceptions from students regarding convenience. Clinical educators found these innovations enabled teaching at scale. Patients did not perceive such innovations to negatively impact their standard of care. Limitations included the inability to practice physical examination skills, challenges in ensuring learner engagement and connectivity issues. CONCLUSION: Livestreamed clinical experiences have the potential to effectively expand placement capacity and provide high-quality educational experiences for medical students. Although certain limitations exist, technological and pedagogical adaptations can help overcome these challenges. The application of theoretical frameworks to future online innovations will be fundamental to ensure effective clinical learning.

An Experiential Learning Opportunity in Norway: Computation for Bioengineering and Mechanical Engineering Students.

The global learning initiative at Northeastern University is focused on fostering intercultural communication skills. The Dialogue of Civilization (DOC) program serves as a mechanism to achieve such a goal by offering faculty-led international experiences. In this paper, we have presented a detailed account of a DOC program that took place in Norway. The primary objective of the program was to teach mechanical engineering and bio-engineering students computational skills while stimulating critical thinking about the cultural and social aspects of technology and engineering in Norway. The program focused on two courses: a technical course and a special topics course. The technical course introduced students to finite element analysis, with practical applications and site visits in Norway to enhance experiential learning. In the special topics course, the interplay between modern technologies, like green energy, state policies, and the rights and traditions of the indigenous Sámi people was explored. The course highlighted both the progressive social policies in Norway and the historical discrimination against the Sámi. Student feedback was positive and experiential learning components such as guest lectures and site visits were particularly appreciated. Additional surveys showed that students' self-confidence was higher following the DOC program. In addition, female-identifying students had higher confidence in their future success after completion of this program as compared to their male-identifying counterparts. Our paper is expected to serve as a resource for educators seeking to integrate technical education with intercultural experiences and discussions on social and cultural impacts in engineering.

The Evolution of Active Learning in Response to the Pandemic: The Role of Technology.

Active learning has consistently played a significant role in education. Through interactive tasks, group projects, and a variety of engaging activities, students are encouraged to forge connections with the subject matter. However, the pandemic has necessitated that educators adapt and refine their active learning techniques to accommodate the online environment. This has resulted in stimulating innovations in the field, encompassing virtual simulations, online collaboration tools, and interactive multimedia. The COVID-19 pandemic has rapidly transformed the landscape of teaching and learning, particularly in higher education. One of the most prominent shifts has been the widespread adoption of active learning techniques, which have increased student engagement and fostered deeper learning experiences. In this chapter, we examine the evolution of active learning during the pandemic, emphasizing its advantages and challenges. Furthermore, we delve into the role of advances in artificial intelligence and their potential to enhance the effectiveness of active learning approaches. As we once focused on leveraging the opportunities of remote teaching, we must now shift our attention to harnessing the power of AI responsibly and ethically to benefit our students. Drawing from our expertise in educational innovation, we provide insights and recommendations for educators aiming to maximize the benefits of active learning in the post-pandemic era.

Application of Network-Based PBL Model Combined with Role-Playing Method in Geriatric Nursing Teaching.

Objective: To evaluate the effectiveness of using a combination of problem-based learning (PBL) and role-playing methods in geriatric nursing education through online networks. Methods: The research objects of this paper were selected from nursing students, and the number of participants was 200. The research objects were selected from March 2019 to September 2021. The learning situation and related data of the above students were retrospectively analyzed. According to the teaching methods, the students were divided into groups. The students who received traditional teaching methods were included in the control group, with a total of 100 participants. The students who received network-based PBL mode combined with role-playing teaching were included in the observation group, with a total of 100 participants. The assessment results and learning effect evaluation of the two groups of students were compared, and the level of learning engagement and changes in critical thinking between the groups were compared. Results: The scores of basic theoretical knowledge, clinical practice skills, and clinical case analysis of students in the observation group were higher than those of the control group (P < .001). The evaluation index of nursing students' learning effects was analyzed. The proportions of enhancing teacher-student interaction, improving team cooperation ability, improving autonomous learning ability and learning interest, improving analysis and problem-solving ability, improving theory combined with practice ability, improving communication and expression ability, improving work self-confidence, improving knowledge and vision, improving literature retrieval and evaluation ability in the observation group were higher than that in the control group (P < .001). After the teaching work, the overall learning input score, cognitive input score, behavior input score, emotional input score, learning harvest score, and learning satisfaction score of students in the observation group were higher than those of the control group (P < .001). After teaching, the scores of finding the truth, open mind, analytical ability, systematic ability, critical thinking self-confidence, curiosity and cognitive maturity of the students in the observation group were higher than those in the control group (P < .001). Conclusion: The combined application of network-based PBL mode and role-playing method can significantly improve the teaching effects of geriatric nursing, with popularization value.

Applied Research of Case-based Learning Teaching in Nephrology Medicine for Professional Postgraduate Students in Clinical Medicine.

Objective: To explore the influence of case-based learning (CBL) teaching methods in comparison to the traditional lecture-based learning (LBL) model in clinical teaching of nephrology for master's degree students in clinical medicine. Methods: Clinical medicine master's degree students who were trained in the Department of Nephrology, The First Affiliated Hospital of Nanjing Medical University from December 2015 to December 2021 were selected as the study objects. The selected students were divided into two groups: the LBL group comprised 16 graduate students who received the traditional LBL model from December 2015 to December 2018, and the CBL group comprised 18 graduate students who received the CBL teaching methods from January 2019 to December 2021. Both groups participated in the professional theoretical knowledge assessment, including objective and subjective questions and calculating the total score), and the examination of clinical skills communication ability, preparation of handling materials, anesthesia techniques, operational skills, aseptic techniques, and postoperative management), at the time of discharge from the department. The independent learning ability (self-management ability, information ability, and learning ability) of students of the two groups after teaching was then assessed, and the satisfaction of the two groups with their respective teaching mode (including satisfaction with the teaching format, teaching effectiveness, interest stimulation, independent learning and the improvement of teamwork ability) was assessed by the questionnaire on the degree of satisfaction of the two groups. Results: The assessment scores of professional theoretical knowledge in the CBL group were significantly higher than those in the LBL group in objective questions, subjective questions, and total scores (P1 = .028; P2 = .036; P3 = .041). The CBL group scored higher than the LBL group in the assessment of communication skills, preparation of operative items, anesthesia technique, operative skills, aseptic technique, and postoperative handling skills, but the differences were not statistically significant (P1 = .071; P2 = .260; P3 = .184; P4 = .127; P5 = .352; P6 = .584). The self-management ability, information ability, and learning ability scores of students in the CBL group were significantly higher than those in the LBL group (P1 = .006; P2 = .013; P3 = .003). Students in the CBL group were significantly higher than those in the LBL group in terms of satisfaction with teaching form, teaching effect, interest stimulation, improvement of independent learning ability, and satisfaction with teamwork ability (P1 = .015; P2 = .008; P3 = .010; P4 = .024; P5 = .022). Conclusions: The CBL teaching model can improve and enhance the clinical thinking ability of clinical medicine master's degree students in nephrology, and stimulate their interest in learning. Professional master's degree students have a high degree of satisfaction with the CBL model.

Short-Term Effects of an eHealth Care Experiential Learning Program Among Patients With Type 2 Diabetes: Randomized Controlled Trial.

BACKGROUND: Type 2 diabetes is a chronic disease with a significant medical burden. eHealth care integrates medicine and technology to enhance the outcomes of such patients; however, adequate eHealth literacy (eHL) is necessary for that to happen. Fostering eHL is crucial for patients with diabetes to engage with eHealth care and receive quality care and timely support. Experiential learning theory can enhance patients' eHL and skills to use eHealth care technology in their daily care. OBJECTIVE: This study explored the effectiveness of an eHealth care experiential learning program in improving eHL, patient health engagement, and eHealth care use status among patients with type 2 diabetes in 3 months. METHODS: In this randomized controlled trial, patients under case management services from various clinics in Taiwan were randomly assigned to either the intervention group receiving the 6-session eHealth care experiential learning program or the control group receiving the usual care. Data were collected using structured questionnaires at 3 time points: pretest, postintervention, and 3 months after the intervention. Descriptive data were presented using frequency distribution, percentage, mean, and SD. The outcomes were analyzed using a generalized estimating equation method by intention-to-treat analysis. RESULTS: A total of 92 participants (46 in each group) were recruited in this study. Of these, 86 completed the course and follow-up evaluations with a mean age of 62.38 (SD 12.91) years. After completing the intervention, the intervention group had significantly higher posttest scores in eHL (ß=19.94, SE 3.52; P<.001), patient health engagement (ß=.28, SE 0.13; P=.04), and eHealth use (ß=3.96, SE 0.42; P<.001) than the control group. Furthermore, the intervention group maintained these significant improvements in eHL (ß=18.19, SE 3.82; P<.001) and eHealth use (ß=3.87, SE 0.49; P<.001) after 3 months. CONCLUSIONS: Participating in the eHealth care experiential learning program resulted in significant improvements in eHL, patient health engagement, and eHealth use among patients with type 2 diabetes. Our interventional program can inform future clinical practice and policies to strengthen self-management skills and facilitate the use of health technology in caring for patients with chronic diseases. TRIAL REGISTRATION: ClinicalTrials.gov NCT05180604; https://clinicaltrials.gov/ct2/show/NCT05180604.

Twelve tips for using the Understanding by Design® curriculum planning framework.

BACKGROUND: Health professions faculty engaged in curriculum planning or redesign can struggle with developing courses or programs that align desired learner outcomes, such as competencies to be applied in a clinical setting, with assessment and instruction. AIMS: Our medical school implemented the Understanding by Design (UbD) framework to achieve alignment of outcomes, assessments and teaching during the renewal of our four-year curriculum. This article shares our strategies and practices for implementing UbD with teams of faculty curriculum developers. DESCRIPTION: The UbD framework is a 'backward' approach to curriculum development that begins by identifying learner outcomes, followed by the development of assessments that demonstrate achievement of competencies and concludes with the design of active learning experiences. UbD emphasizes the development of deep understandings that learners can transfer to novel contexts. CONCLUSIONS: We found UbD to be a flexible, adaptable approach that aligns program and course-level outcomes with learner-centred instruction and principles of competency-based medical education and assessment.

The tools of the future are the challenges of today: The use of ChatGPT in problem-based learning medical education.

What is the educational challenge?Incorporation of large language model (LLM) or generative artificial intelligence (AI) software poses a challenge to various areas of medical education, including problem-based learning (PBL). LLMs, such as ChatGPT, have incredible potential to transform educational systems and enhance student learning outcomes when used responsibly.What are the proposed solutions?ChatGPT can provide several ways to support students and assist facilitators with course responsibilities. Here we address factors of implementation and describe how ChatGPT can be responsibly utilized to support key elements of PBL.How was the solution implemented?Providing reasonable access is an essential element of novel software implementation. Additionally, training for both faculty and staff is vital to foster responsible usage, provide base-line proficiency, and guide users to critically evaluate the quality of output.What lessons were learned that are relevant to a wider audience?The use of LLMs or other generative AI is dramatically rising in the world. Appropriate and conscientious incorporation of AI into educational programs can foster responsible use and potentially enhance student learning.What are the next steps?Assessment of learning outcomes, student self-efficacy, group dynamics, and stakeholder feedback are required to measure the effects of ChatGPT in the PBL curriculum. Additionally, software programs competitive with ChatGPT are currently under development and will also need to be investigated for their potential role in education.

Expanding the scope of problem-based-learning at Hackensack Meridian School of Medicine; integrating domain-general skills with domain-specific content.

The Master Adaptive Learner is a model used to develop students to become self-regulated and adaptable lifelong learners to practice medicine in a complex and ever-changing environment. The Hackensack Meridian School of Medicine (HMSOM) proposes a new course, Patient Presentation Problem-Based Learning Curriculum (PPPC), a dynamic and integrated course that goes beyond the scope of traditional Problem-Based-Learning (PBL). PPPC allows students to build domain-general skills in tandem with domain-specific content learned during a pre-clerkship curriculum. An integrated case provides weekly scaffolding, such that the course takes place throughout the week and is not isolated from the rest of the curriculum. Students receive iterative feedback and structured assignments which allows development of self-directed learning skills along with integration and consolidation of weekly curricular content. A layered analysis approach was used to outline the philosophies, principles and techniques that link to our course objectives. Techniques used could easily be translated to other pre-clerkship curriculum to promote development of self-directed learning and clinical reasoning skills, as well as promote more meaningful learning of basic, clinical, and health system science content.

'You don't see what I see': Co-designing simulation to uncover and address cognitive bias in healthcare.

EDUCATIONAL CHALLENGE: Each year, adverse events are reported in healthcare, of which many relate to healthcare workforce cognitive bias. The active involvement of workforce and consumers in the review and co-design of effective training for the healthcare workforce to recognise, monitor, and manage unconscious bias is required. PROPOSED SOLUTION: We used participatory action research to co-design an innovative, interprofessional simulation based on 'real world' clinical incidents and lived experiences to improve the delivery of safe, high quality, consumer-focused healthcare. Following ethics approval, content analysis of serious adverse patient safety events involving cognitive bias was conducted. These data informed audio-recorded interviews with the healthcare workforce and consumers to explore their experiences of cognitive bias. Following thematic analysis, key themes of communication, stigma, diagnostic overshadowing, and fragmented systems were uncovered. Guided by consumers, these themes were interwoven into a simulation scenario that included real places, stories, and verbatim quotes delivered through mixed media artefacts. This heightened the immersive and experiential learning that aimed to uncover unconscious bias and help learners recognise its impact on clinical decisions and practice. POTENTIAL BENEFITS AND NEXT STEPS: To our knowledge, this is the first interprofessional, co-designed simulation to specifically address cognitive bias in current and future healthcare workforce. Plans to translate this research into a practical framework on how to work with key stakeholders (including consumers) to identify 'real-world' health service risks and co-design targeted simulations to address these gaps are described, including lessons learned.