Named after the Greek god of messengers, Hermes watches the education landscape: spotting new opportunities, pressure-testing the ventures we're building, and tracing every read back to the real-world signals behind it.
The evidence library: the raw signals the pipeline is watching across the education ecosystem. Every idea is built from these.
A series of racist costume parties at Bowdoin shows the contradiction colleges have to navigate – encouraging open, reasoned debate, while creating a safe campus for all students.
After my niece died by suicide, I began researching how Chinese immigrant families feel about their children’s mental health and why they often avoid care.
Title IX’s language is clear that the 1972 law does not cover the admissions decisions private colleges and universities make.
Systematic Review (SR) is a prosperous study type in modern medicine and beyond. Many SR authors complement their primary database searches by supplementary techniques. Among these, citation-based techniques known as citation searching (CS) are widespread. Unranked Direct CS (UDCS) to identify directly cited and citing literature of seed references is currently most prevalent. Ranked (In)direct CS (RICS) additionally collects co-cited and co-citing literature combined with a ranking and cut-off procedure. However, RICS workflows remain non-standardized and tedious, and associated benefits unclear. This work aims to create a framework for the prospective international comparison of supplementary UDCS and RICS. To prime RICS research, we developed the open-source Co*Citation Network application and assessed parallel supplementary UDCS and RICS retrospectively in three completed SRs and prospectively in one case study. Automated RICS collected and ranked cited, citing, co-cited, and co-ci
Participatory qualitative methods such as Photovoice are increasingly used to link research with social action. Recent advances in artificial intelligence (AI) may enhance data analysis, inference, and action planning within such participatory approaches. This study explored medical students perceptions of social justice using conventional Photovoice analysis and assessed the potential contribution of generative AI (genAI). Nine students joined a six-week seminar, "Exploring the Concept of Social Justice Using Photovoice." An initial two-hour session covered ethics, the Photovoice framework, and photography techniques. Participants then captured images reflecting their views on social justice, wrote narratives, and engaged in guided group discussions. Human researchers and students conducted a three-stage Photovoice analysis: 1) selecting photographs, 2) contextualizing them with participant narratives, and 3) inductively coding themes. To explore how AI might support data analysis, th
ObjectivesElectronic Health Records (EHRs) impose a significant time burden on physicians, often requiring work to be completed outside of scheduled hours. While this burden is well-documented, how it evolves throughout emergency medicine (EM) residency remains poorly understood. This study aimed to quantify EHR usage patterns, analyze the composition of after-shift work, and characterize the development of EHR efficiency across EM training. MethodsWe conducted a retrospective cohort study of EM residents (postgraduate year [PGY] 1-4) using 5.5 years of EHR audit log data (2020-2025) at a single academic institution. We analyzed EHR time per new patient encounter, stratified by postgraduate year, and categorized activities into domains such as documentation, chart review, and orders. EHR work was measured both during and after scheduled shifts. ResultsThe analysis included 144 unique residents and 167,010 new patient encounters across 15,386 shifts. Encounter-attributed EHR time per en
IntroductionEarly exposure to otolaryngology (ENT) procedural skills in undergraduate medical education is limited by patient safety concerns, restricted clinical opportunities, and the cost of commercial simulators. As a result, essential ENT skills are often underrepresented in structured, hands-on curricula for medical students. MethodsWe developed a low-cost, multistation ENT simulation curriculum consisting of five reproducible task trainers: ear examination and otologic procedures, mirror laryngoscopy, rigid and flexible endoscopic navigation, introductory mastoid drilling, and emergency cricothyrotomy. The curriculum was delivered as a 2-hour, faculty-led workshop during a third-year medical student otolaryngology rotation. Learners rotated through stations in small groups. Pre- and post-workshop surveys assessed self-reported anatomical familiarity, procedural confidence, and educational value using a 5-point Likert scale, with additional qualitative feedback collected. Results
It’s no longer uncommon for scheduled university commencement speakers to have their invitations rescinded following backlash over their politics.
A new memo blocks graduate students from writing theses or dissertations on certain topics, raising questions about academic freedom and the purpose of higher education.
OBJECTIVESTo examine whether psychological safety and power distance are associated with medical researchers well-being, and whether these associations operate through team inclusiveness and conflict. DESIGNCross-sectional survey study. SETTINGA biomedical research institute at a major UK university. PARTICIPANTS133 medical researchers from 17 teams, including 20 principal investigators and 113 team members. MAIN OUTCOME MEASURESJob satisfaction, life satisfaction, intrinsic motivation, and psychological detachment. Mediators were dimensions of team inclusiveness and team conflict. RESULTSPsychological safety had no significant direct associations with job satisfaction, life satisfaction, intrinsic motivation, or psychological detachment, but showed several indirect associations through researchers team experiences. It was indirectly associated with higher job satisfaction, life satisfaction, and intrinsic motivation primarily through greater integration of differences, inclusion in de
Exaggerating phrases and talking in a sing-song way can actually help, not make it harder, for young children to master speaking a language.
BackgroundMedical residents and physicians face high rates of burnout, psychological distress, and impaired professional functioning. Big Five personality traits are stable characteristics that may explain variation in vulnerability and coping, but evidence in this population remains inconsistent. We aimed to synthesise associations between Big Five traits and stress-related outcomes, coping, and performance in medical residents and physicians. MethodsSystematic review and meta-analysis (PROSPERO CRD42023483408). PubMed, Embase, MEDLINE (Ovid), Cochrane Library, Scopus, and Web of Science were searched from inception to November 15, 2023, updated through January 2026. Eligible studies were primary research in English involving medical residents and/or practising physicians, assessing at least one Big Five trait and a validated measure of stress, coping, or performance. Two reviewers independently screened records; data were extracted by one reviewer and checked by a second. Risk of bia
Accurate and objective evaluation of surgical skill and performance is critical for advancing training and improving patient outcomes. Current assessment methods increasingly rely on video analytics and depend on labor-intensive, frame-by-frame manual annotation by experts. In this work we developed a surgical video annotation platform (AnnotX) that used a Python backend running a pretrained promptable video segmentation foundation model, i.e., Segment Anything 3 (SAM 3) for per frame segmentation and temporal segment propagation. With a few interactions per class, the model generated a high-quality mask on a key frame and propagated it through the sequence. The platform automatically exported per-class binary masks and color overlays for every frame, together with deterministic metadata and a standardized study folder structure to support auditability and downstream analysis. On deidentified laparoscopic surgery videos, the system processed typical clips in minutes and reduced expert
M.D.-Ph.D. programs in the United States have traditionally followed a "2-n-2" curricular model, with the graduate phase occurring between the pre-clerkship and clerkship portions of medical training. While well established, this format can limit trainee autonomy in shaping their physician-scientist training trajectories. In response, some programs have introduced a "3-n-1" model, allowing students to complete clerkships before beginning Ph.D. training. Our institution implemented multiple flexible curricula in 2017. Understanding why trainees choose one pathway is important as programs consider implementing more adaptable training structures. To investigate these factors, we surveyed M.D.-Ph.D. students at our institution, which offers multiple flexible curricular alternatives, about contributions to their curricular decisions. Responses supported that trainees weigh considerations across medical education, scientific development, and integrated physician-scientist training domains. A
Most American adults will say that they most valued teachers who really knew them, cared about them and made learning relevant to their lives.
New research shows that for every 10 boys identified with autism, only about two girls in a comparable situation were identified.
Young people don’t all contribute in the same way, and understanding the broader picture is the starting point for adults who want to support them.
The Smith College investigation marks the first time the Trump administration is considering whether trans students should gain admission to certain schools.
Homeschooling trends are on the rise, bucking the narrative that most of its growth was caused by the pandemic.
New research suggests that bullying prevention work should address the broader classroom environment, not just students’ individual characteristics and behaviors.
BackgroundMultiple-choice questions (MCQs) are widely used in medical education, but are criticized for cueing and guessing. Very short answer questions (VSAQs), which require students to generate responses independently, may better assess knowledge. While VSAQs demonstrate higher item discrimination within individual exams, their effectiveness in distinguishing academic performance across multiple assessments remains unclear - representing a key gap in the validation of VSAQs under Messicks framework, specifically the category of "relations to other variables". This study examines whether VSAQs or MCQs more effectively distinguish students of varying performance levels across multiple summative examinations. MethodsWe analyzed retrospective data from six mixed-format examinations with VSAQs and MCQs of three cohorts of first- and second-year medical students. Academic performance was measured using grade point average (GPA) across assessments. Linear regression assessed the relationsh
Congress passed a law in 1990 mandating the return of all Native American items that federally funded institutions took without consent. Progress since then has been slow.
Most states have some sort of requirement for a minimum number of lockdown drills a year, but there is no set federal guidance.
While these Southern states made some gains in reading, they weren’t evenly felt across different student populations.
BackgroundSurgical phase recognition is a critical prerequisite for context-aware operating rooms and automated skill assessment. While artificial intelligence (AI) benchmarking has progressed for simpler procedures, applying surgical phase recognition to complex, anatomically demanding operations like transabdominal preperitoneal (TAPP) laparoscopic inguinal hernia repair (LIHR) remains uncharted, limiting the scalability of AI-driven analysis in this globally frequent surgery. MethodsWe introduced a workflow analysis framework for TAPP utilizing SurgFormer, a vision transformer architecture. The model was evaluated on an institutional dataset annotated via the Theator platform, with ethical approval from the Research Ethics Board (REB) of the McGill University Health Centre (MUHC). To mitigate data scarcity, we employed a three-stage sequential transfer learning strategy, leveraging weights from Kinetics-400 and Cholec80 before domain adaptation to visual complexities of LIHR. Result
Standardized patients (SPs) are central to clinical communication training but are constrained by cost, scalability, and reliance on trained actors. We present AI standardized patients (AI-SPs), large language model-driven simulators governed by a three-layer information architecture that modulates disclosure according to learner skill. We validate this approach across three phases. In Phase 1, blinded expert evaluation of 350 simulated consultations from five frontier LLMs showed that learner skill level, rather than model choice, drove performance variation (2 = 0.31 vs 0.06), indicating that pedagogical quality emerges from architec-tural design rather than model scaling. In Phase 1b, 155 live student consultations revealed systematic failures in eliciting safety-critical information, generating automated curriculum diagnostics without expert observation. In a three-arm pilot randomized controlled trial (Phase 2, n = 58), AI-SP training achieved skill gains non-inferior to human SP
BackgroundOnline professional learning offers a scalable alternative to traditional face-to-face learning, but there are doubts regarding how well it works and when it works best. This review assessed the effectiveness of online professional learning interventions on healthcare professionals knowledge and skill acquisition. MethodsWe conducted a systematic review and meta-analysis of randomised controlled trials that compared online professional learning against static controls or face-to-face controls. We searched MEDLINE Complete, Scopus, Embase, CENTRAL, and PsycINFO from inception to January 31, 2025. Eligible studies included practising healthcare professionals in any clinical setting that measured knowledge or skill acquisition related to patient care. Data was extracted in duplicate, with disagreements resolved through discussion or by a third reviewer. We used multilevel meta-analyses to estimate the overall effect size and conducted moderation analyses for pre-specified factor
ObjectivesAcademic medical institutions are the gatekeepers of the physician workforce and shape the future of medicine by regulating medical school admissions as well as residency training. Although broadly the field of medicine is seeing more representation from traditionally underrepresented groups, the critical decision-making platform of academic medicine continues to be uncharacteristically homogeneous, represented mainly by white males. This is even more pronounced in surgical subspecialties, such as academic neurosurgery. This study aims to quantify this phenomenon, uncover its driving factors, and define opportunities for improvement. MethodsUsing a mixed research methodology, academic neurosurgical faculty in the U.S were identified, and their demographic data was collected. An internet search using Google Scholar and Scopus was conducted to determine scholarly activity using number of publications and h-index. ResultsWe found a significant increase in female faculty in acade
BackgroundIncreasing relevance of genetics and molecular biology in medicine necessitates greater genetic literacy among current and future healthcare workers. To assess the literacy level, a validated genetic literacy questionnaire is needed. Therefore, a standardised Indonesian-language genetic literacy questionnaire is essential. AimsWe aimed to translate and validate three genetic literacy questionnaires (PUGGS, iGLAS, and UNC-GKS) for use among Indonesian medical students. We then evaluated genetic literacy levels using one of the validated questionnaires. MethodsThe PUGGS, iGLAS, and UNC-GKS questionnaires were translated into Indonesian and then reviewed by an expert panel for translational accuracy and conceptual appropriateness. Back-translation was performed to confirm validity. Initial Indonesian versions of the questionnaires underwent cognitive pre-testing with 12 undergraduate medical students. After refinements, the questionnaires were validated among 34 first-to third-y
BackgroundManual video-based evaluation of surgical skills can be time-consuming and delays trainee feedback. Artificial intelligence (AI) offers opportunities to automate aspects of assessment while maintaining clinician oversight. We developed an interpretable spatiotemporal model that classifies surgical expertise directly from endoscopic video in standardized training tasks and generates saliency-based "highlights reels" showing the most influential frames. MethodsAn RGB pipeline combining InceptionV3 for spatial feature extraction and a gated recurrent unit (GRU) for temporal modeling was trained on the JIGSAWS dataset. The model outputs novice, intermediate, or expert labels. A rolling-window, low-latency evaluation at 30 fps with a stride of 10 frames was used. A motion-augmented variant fused RGB with optical-flow features. Spatial and temporal saliency maps highlighted key decision-making regions. ResultsThe RGB model achieved 95% accuracy (F1: 92% expert, 86% intermediate, 99
Improving diversity in U.S. Alzheimers disease (AD) research is a pressing need. By 2050, Hispanic and Latino Americans will comprise 30% of the population. Hispanics are 1.5 times more likely and Blacks are twice as likely to develop AD compared to Whites, yet both remain vastly underrepresented in clinical trials research. Aging and AD research mentorship of underrepresented STEM undergraduates is designed to promote entry into related professions by students committed to decreasing disparities in AD research participation and clinical care. The NIA-funded MADURA program recruited 93 students from backgrounds historically underrepresented in STEM majors and/or from NIH-defined disadvantaged backgrounds. Trainees were placed in aging/AD research labs and received weekly training and mentorship from faculty research PIs and other types of supervisors (postdoctoral researchers, graduate students, research assistant staff...) Our study examined student ratings of the program and mentor b
Objective Structured Clinical Examinations (OSCEs) are widely used to assess medical students clinical skills, including non-technical abilities such as communication and empathy. However, the potential influence of individual psychological traits--such as personality dimensions, empathy, and stress-related mindset--on OSCE performance remains understudied. This study investigated associations between personality traits, empathy levels, stress mindsets, and performance in OSCEs among medical students. An online questionnaire (including the Big Five Personality Traits Inventory 2, the Jefferson Scale of Physician Empathy (Medical Student version), the Growth Mindset Scale, the Stress Mindset Measure) was provided to all fifth-year medical students enrolled at the Universite Paris Cite for six weeks before undertaking graduation summative OSCEs. Their scores were correlated with OSCE performance using Spearmans correlation and linear regression analyses. A total of 99 questionnaires were
BackgroundPeriodontal disease (PD) and diabetes mellitus (DM) have a well-established bidirectional relationship, affecting glycaemic control and chronic disease outcomes. However, the extent to which medical training supports physician awareness of this association remains unclear especially in resource-limited settings. ObjectiveTo assess exposure to oral health education and to identify predictors of awareness of PD-DM association among physicians. MethodsA cross-sectional study was conducted among 146 physicians managing diabetic patients at a tertiary teaching hospital in Ghana. A structured questionnaire assessed exposure to oral health education, periodontal disease knowledge (score range 0-5), and awareness using a 5-item Likert scale (score range 5-25). Multivariable linear regression identified predictors of awareness. ResultsAlthough 62.1% reported exposure to oral health content during undergraduate training, 59.2% rated its quality as poor. Mean awareness score was 20.6 (S
BackgroundHigh workload among healthcare workers has increasingly been correlated with poor patient outcomes, inefficient operational and financial outcomes, and burnout. Despite growing literature exploring causes of attending physician workload, there is limited understanding of trainee-specific measures. ObjectiveWe aimed to characterize elements contributing to trainee workload and perceived challenges and satisfiers to the trainee workday as a foundation for better understanding and measuring trainee work experience. MethodsInternal Medicine and Medicine-Pediatrics residents at an academic medical center were invited to participate in focus groups discussing contributors to inpatient workload and work experience between March and April 2024. A qualitative content analysis identified key metrics of trainee workload and work experience, which were then consolidated into overarching domains. A structured, multi-round rating process ranked the perceived relevance of each metric. Resul
We do not allow requests for this scam competition. Going forward if you post something asking for votes your post will be removed (which we’ve been doing) and you will be banned. Please continue to report future posts made by people who can’t read directions. submitted by /u/pile_o_puppies [link] [comments]
IntroductionEvaluate large language models (LLMs) for scoring medical student essays, and compare various prompting techniques and models. MethodsOpenAI GPT scored 51 medical student reflection essays (15 real, 36 fabricated) using a previously-reported 6-point rubric (April-May 2025). We compared 29 prompt-model conditions by systematically varying the LLM prompts (including the persona, scoring rubric, few-shot learning [exemplars], chain-of-thought reasoning, and temperature), fine-tuning, and model (including GPT-4.1, GPT-4.1-mini, GPT-o4-mini, and GPT-4-Turbo). Outcomes were accuracy (compared with human raters, measured using single-score intraclass correlation coefficient [ICC] and mean absolute difference [MAD; zero indicates perfect agreement]), within-condition reproducibility, and cost. ResultsAcross all conditions, it took mean (SD) 3.73 (3.12) seconds to score 1 essay. The cost to score 100 essays was USD $0.04 for GPT-4.1-mini, $0.21 for GPT-4.1, $0.57 for GPT-4.1 with 3
In recent years, progress in medical informatics and machine learning has been accelerated by the availability of openly accessible benchmark datasets. However, patient-level electronic medical record (EMR) data are rarely available for teaching or methodological development due to privacy, governance, and re-identification risks. This has limited reproducibility, transparency, and hands-on training in cardiovascular risk modelling. Here we introduce PRIME-CVD, a parametrically rendered informatics medical environment designed explicitly for medical education. PRIME-CVD comprises two openly accessible synthetic data assets representing a cohort of 50,000 adults undergoing primary prevention for cardiovascular disease. The datasets are generated entirely from a user-specified causal directed acyclic graph parameterised using publicly available Australian population statistics and published epidemiologic effect estimates, rather than from patient-level EMR data or trained generative mode
Good evening, r/nursing . We know this is a challenging time for all due to the outrageous events that occurred on a Minnesota street yesterday. As your modteam, we would like to take a moment to address some questions we've gotten regarding our moderator actions in the last 48 hours and to make our position on the death of Alex Pretti, and our future moderation actions regarding this topic, completely clear. Six years ago at the beginning of the pandemic, we witnessed an incredible swell of activity from users not typically seen as participants within our community. Misinformation was plentiful and rife. As many of you recall, accusations of nurses harming or outright killing patients to create a 'plandemic' were unfortunately a dime a dozen. We were inundated with vaccine deniers, mask haters, and social distancing detractors. For every voice of reason from a flaired and long-standing contributor in our forum, there was at least one outside interloper here simply to argue. At that ju
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Me encanta aprender con Duolingo
BEAUTIFUL!
It’s fun and easy to follow, but it doesn’t feel encouraging enough. I could leave it for a day, and forget it exist for a year. It may just be me. But also every time you complete something it makes an annoying ding sound. And there’s no way to turn it off. But otherwise it’s nice for learning different languages.
Lol
Duolingo is not great anymore. I originally downloaded it because you could hear native speakers in whatever language you were studying, which was incredibly helpful. Now it’s all AI garbage that you can get anywhere for free. It’s glitchy, and annoying, and gets things wrong a lot- because AI doesn’t actually know anything. I did a bunch of lessons yesterday that disappeared today & it used a streak freeze for no reason. The Flashcard Frenzy only accepts one answer (so if you use the feminine “belle” when it asks for “beautiful” but they wanted the masculine “beau”, you’re wrong, except you’d have no way of knowing that). I could go on, but honestly, the point is: Duolingo won’t help you navigate in a foreign language. My speaking/listening skills are not any better than when I started. Get Pimsleur instead if you want to have functional language skills.
Duolingo is cool and I use it all the time but why did you guys make Oscar so weird bro is rizzing me up😭
It’s helps me ANYTHING that I want to learn and that’s the BEST THING EVER!!! And thank all of the staff that created and helped Duolingo. Thank you!
I only have the free version, but all the ads for the max version feel really AI and it’s turning me off. The podcast episode I had also felt like AI. If that’s the vibe of the paid version I don’t want it
I think Duolingo would be better You could change the language to be the opposite like if you’re learning English and speak Spanish. You can switch it so it would be like you speak English, and you’re learning Spanish, so in case you didn’t know some words, you can figure out and then continuing learning English. And there are some mistakes en Duolingo, like sometimes it has yo which means I, but when you translate it in English, there’s not supposed to be an l aka yo
I am getting at Spanish it is great try it
Energy is a predatory way to punish your learners to buy your subscription. Used to be rewarded for accuracy, and now, you are punished for not spending money. Lame