Named after the hundred-eyed watchman of Greek myth, Argus 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.
arXiv:2607.15533v1 Announce Type: new Abstract: Haptic interfaces for the wrist and forearm offer an attractive alternative to hand-worn devices as they are simple to wear, leave the hands free for interaction with the real world, and interfere minimally with natural arm motions. To be useful in real-world settings, however, such devices must balance functionality, wearability and comfort, all while being fully untethered with minimal mass and volume. In this work, we present CASAband, a haptic wristband that integrates compliant amplified shape memory alloy actuators (CASA) into a multi-layered textile wristband to deliver spatial and temporal haptic feedback. CASAband operates completely untethered, generates no noise, and has a total mass of 63 g. The device incorporates four actuators that can generate up to 1.7 N of blocked force and 3.2 mm of free displacement with an operating bandwidth ranging from 1.34-6.59 Hz depending on the applied voltage. We conducted a perceptual study a
arXiv:2607.15523v1 Announce Type: new Abstract: Scene-centric visualization systems expose semantic components, such as marks, encodings, layouts, and axes, as first-class objects that can be directly manipulated. Existing interaction abstractions, however, are largely based on event streams, signals, and data selections rather than semantic scene components. This mismatch makes interactions involving scene components less natural to specify and limits the expressive power of scene-centric visualization systems. We present Interactive Mascot, a scene-centric interaction grammar for data visualizations. Interactive Mascot extends scene-centric representations for static visualizations by modeling interactive behavior as information flow among four interaction components (trigger, responder, evaluator, and updater) and two forms of context (event context and state context). To realize these semantics, we introduce a dependency-graph execution model that systematically transforms interact
arXiv:2607.15403v1 Announce Type: new Abstract: Assessing learning in virtual reality (VR) environments typically relied on traditional pre-post content retention tests, revealing little about the process of learnng within such immersive environments. Multimodal data from player activity in VR is promising to better measure learning processes and higher-order skills, but little research in the learning sciences has explored how such data can be combined to provide meaningful measures. To address this, we explored multimodal sources of data from a VR escape room containing hands-on logic puzzles that require problem-solving strategies and engagement in verbal metacognitive reflections. We leverage VR's affordances to immerse users in sustained dialog and promote multimodal interactions in a digital environment to understand how logfile and verbal data reveal participants' reasoning skills versus guesswork.
arXiv:2607.15325v1 Announce Type: new Abstract: Multisensory integration, particularly through visual and tactile feedback, plays a crucial role in enhancing audience engagement with artworks. Although recent research has increasingly explored tactile experiences in art, existing systems often lack real-time variable stiffness modulation and depend on bulky mechanical infrastructures. In this work, we propose a novel tangible display based on a magnetic jamming mechanism, enabling real-time, low-noise, and low-voltage stiffness modulation integrated into traditional sculptural artworks. Our system combines visual motion and dynamic tactile feedback within a compact standalone module, allowing audiences to interactively experience variations in the rigidity and form of features such as those found in the traditional Korean mask Hahoetal. This approach offers a new paradigm for interactive art, enabling more immersive, multisensory engagement through the fusion of cultural artifacts and
arXiv:2607.15282v1 Announce Type: new Abstract: Empathy is most often theorized as resonance: a mirroring of another's present emotional or cognitive state. This synchronic framing has shaped artificial systems, where empathic behavior is defined as affect recognition and response alignment. We argue this is the wrong target for extended dialogue, where understanding unfolds over time through prediction, divergence, and repair. We reframe empathy as predictive misalignment tolerance: the capacity to anticipate and regulate divergence across time rather than collapse it. We formalize this as Interpretive Error Tolerance (IET), a dynamic-threshold heuristic that models empathy as maintaining a viable band of divergence between agents. We evaluate this framework with two computational probes under controlled noise. The IET update rule does not outperform fixed baselines. Instead, we find a robust regime-dependent structure: repair trades discriminative fidelity for gist preservation. At l
arXiv:2604.06419v2 Announce Type: replace-cross Abstract: Drawing on 20 qualitative interviews with users of AI companion platforms and general-purpose chatbots, this study examines what users seek from AI companionship and how gratifications develop through sustained interaction. Through abductive qualitative content analysis, we find that familiar Uses and Gratifications categories, including emotional release, self-expression, social presence, and identity affirmation, are generated through interpersonalized affordances: availability, memory, personalization, and responsiveness interpreted as relational qualities. The study extends the Uses and Gratifications framework by showing that AI companionship gratifications are relationally produced and recursively reorganized as users' needs and expectations change over time.
arXiv:2604.06381v2 Announce Type: replace-cross Abstract: This paper examines artificial intelligence (AI) companionship as a site where intimate relations are simultaneously produced, extracted from, and governed through datafied systems. Drawing on critical data studies and platform studies, we challenge prevailing narratives that locate harm in user psychology rather than platform architecture. Through in-depth interviews with 20 individuals who have AI companions, we address three questions: what harms do users identify, how do they make sense of those harms, and what do their accounts reveal about the perceived distribution of responsibility among users, platforms, and regulators? Participants identified design-based harms, including unsolicited content generation and safety mechanisms that stigmatized the users they intended to protect, alongside use-based harms centered on emotional dependency they could recognize but not resolve. Users deployed individualized sensemaking strate
arXiv:2603.13545v2 Announce Type: replace-cross Abstract: AI development has a fiction dependency problem. Developers have treated large corpora of modern books, including fiction, as valuable enough to accept substantial cost and legal risk, yet current models still struggle to generate compelling long-form fiction. I term this the "AI-Fiction Paradox," and it is particularly startling because training data strongly shapes model output. This paper offers a theoretically precise account of why fiction resists AI generation by identifying three distinct challenges for current systems. First, fiction depends on what I call narrative causation, a form of plot logic where events must feel both surprising in the moment and retrospectively inevitable. Standard autoregressive generation commits to prose sequentially, creating a practical obstacle to coordinating local surprise with retrospective inevitability across a long narrative. Second, I identify an informational revaluation challenge:
arXiv:1503.00694v5 Announce Type: replace-cross Abstract: Two fundamental axioms in social choice theory are consistency with respect to a variable electorate and consistency with respect to components of similar alternatives. In the context of traditional non-probabilistic social choice, these axioms are incompatible with each other. We show that in the context of probabilistic social choice, these axioms uniquely characterize a function proposed by Fishburn (Rev. Econ. Stud., 51(4), 683--692, 1984). Fishburn's function returns so-called maximal lotteries, i.e., lotteries that correspond to optimal mixed strategies of the underlying plurality game. Maximal lotteries are guaranteed to exist due to von Neumann's Minimax Theorem, are almost always unique, and can be efficiently computed using linear programming.
arXiv:2512.10113v3 Announce Type: replace Abstract: Dark personality traits have long been associated with antisocial and toxic online behaviors, yet their relationship with observable online activity remains unclear. We investigate the association between validated dark personality measures, self-reported experiences of online incivility, and linguistic and behavioral features extracted from real-world user activity. To this end, we developed a Web application that securely links responses to validated psychological questionnaires collected via Amazon Mechanical Turk with participants' Reddit activity. This yielded a dataset of nearly 57K comments (2.2M tokens) from 114 users, represented through a broad set of linguistic and behavioral features. Our analyses reveal a clear distinction between self-reported and observed behavior. Dark personality traits show consistent associations with self-reported engagement in uncivil interactions. However, no validated dark personality dimension
arXiv:2505.00100v2 Announce Type: replace Abstract: Background and Context. Generative AI (GenAI) tools are increasingly used in programming courses, but we have limited evidence about how brief instruction can foster responsible, learning-oriented use. Objectives. We evaluate "AI-Lab", a scaffolded GenAI literacy intervention, asking how students' self-reported GenAI usage and their openness and comfort using GenAI for conceptual, debugging, and homework tasks change after participation. Methods. Across two semesters in three CS courses and one first-year engineering course at a U.S. university, we deployed the "AI-Lab" (pre-lab orientation, in-class critique of GenAI outputs, and a required homework reflection), collecting paired pre/post surveys (Perception N=831; Usage N=826) and six post-intervention focus groups; primary inferential analyses used the three CS courses (N=778 and 773, respectively). We analyzed survey shifts with paired non-parametric tests and focus groups via the
arXiv:2607.16010v1 Announce Type: cross Abstract: Governments are increasingly mandating that LLM-generated content carry watermarks. The EU AI Act calls for markings that are "sufficiently reliable and robust." California's SB 942 requires disclosure that is "permanent or extraordinarily difficult to remove." Both mandates rest on an untested assumption: that watermark detection yields evidence reliable enough for courts. This paper tests that assumption directly. We evaluate three representative LLM watermarking methods -- KGW, Unigram, and the MarkLLM implementation of SynthID-Text -- against the Daubert admissibility criteria and the NIST SP 800-86 digital forensic process. To structure this evaluation, we propose a Forensic Readiness Score (FRS) framework with 12 criteria, three mandatory gates, and a 60-point scoring system. We focus on meaning-preserving paraphrase as the attack vector, since it is both legally realistic and difficult to dismiss as evidence tampering. The result
arXiv:2607.15944v1 Announce Type: cross Abstract: Standard automation ROI misses four categories of systemic risk -- tacit knowledge erosion, resilience reduction, regulatory exposure, and socio-institutional capital degradation -- that affect long-term organizational performance. PHP-AIO (Protocol for Human Preservation in AI-Optimized Organizations) is a five-gate sequential decision protocol with a final composite check that quantifies these unpriced systemic risks at the role level and produces auditable automation decisions. A closed-form automation-debt measure ($\rho(P)$) formalises how role-level decisions accumulate across multi-step processes; its warning is neutralised only by a regulator-mandated human-in-the-loop anchor. Applied to stylised profiles of representative internal roles, PHP-AIO produces distinct outcomes -- automate, augment, hybrid, and preserve -- for candidates that standard cost-benefit analysis would uniformly automate. Threshold sensitivity analysis conf
arXiv:2607.15879v1 Announce Type: cross Abstract: Much empirical legal research depends on translating unstructured text into structured variables. In corporate governance research as elsewhere, this translation has traditionally relied on human coding of documents such as charters and bylaws, a process that is costly, difficult to scale, and often opaque. This paper introduces DECODEM, a set of benchmark datasets for evaluating the automated extraction of corporate governance variables from organizational documents. The benchmarks pair randomly sampled corporate charters and bylaws with high-quality human annotations covering a range of governance provisions commonly studied in empirical work. Using these datasets, the paper evaluates several large-language-model extraction pipelines that vary in prompt design, task decomposition, and document handling. The underlying task consists of a set of document-level binary classification problems, one for each governance variable. The results
arXiv:2607.15769v1 Announce Type: cross Abstract: Generative AI and coding agents are intensifying a central governance tension in open-source software (OSS): they scale contribution generation faster than maintainers can assess risk, evidence, and accountability. Existing responses improve agent-readability and traceability, but project rules must also organize contribution-specific risk, evidence, accountability, and review-gate states. We theorize this organizational arrangement as project-side governability infrastructure. A diagnostic audit of 50 GitHub repositories finds widespread general governance artifacts, observable agent-readability, and fragmented AI-governance cues, but no project-wide arrangement that coordinates shared rules, preparation obligations, verification rights, and maintainer decision authority across AI-mediated contribution workflows. We develop the Agent Governance Manifest (AGM) as a repository-hosted boundary resource and bidirectional governance contrac
arXiv:2607.16130v1 Announce Type: new Abstract: AI governance increasingly requires judgments about whether an AI system remains adequately trustworthy over time, whether observed changes are tolerable, and how such judgments should be documented in a transparent and contestable way. Yet existing work on AI trustworthiness remains either too high-level to support lifecycle monitoring and reassessment or too narrowly metric-driven to connect with governance needs. We therefore propose a lightweight methodology for auditable trustworthiness levels in AI governance. The methodology has two components: a formal framework for representing and learning trustworthiness levels, and a lightweight AI lifecycle governance procedure for documenting, monitoring, and reassessing them over time. The formal framework models governance-relative trustworthiness through a context-sensitive protocol of measurable dimensions and learns trustworthiness levels as interpretable rules over trustworthiness prof
arXiv:2607.16115v1 Announce Type: new Abstract: Generative AI is increasingly used for feedback in higher education, but evidence from repeated classroom use remains limited. This short paper analyses 2988 reflective essay-feedback-appraisal instances from 283 Estonian bachelor students across one semester. Students obtained and assessed feedback from a self-selected AI tool using a uniform prompt. The present analysis of the anonymized text corpus covers essay content, AI feedback, and its perceived helpfulness. Students found feedback helpful and actionable more often than not; about a tenth thought AI unhelpful, more so towards the end of the semester. We also analyzed essay reflection depth, and used a validated AI text classifier to estimate the share of essays that could be treated as likely unaided student writing. The study contributes descriptive classroom evidence on integration of AI feedback - a fast and scalable way to provide immediate writing advice, but not a self-conta
arXiv:2607.15888v1 Announce Type: new Abstract: Autonomous driving ethics is not only an expert concern, but also a public issue involving risk, responsibility, and governance. However, non-experts often struggle to interpret these issues in concrete incidents, especially when responsibility is distributed across multiple stakeholders. This paper investigates interactive narrative as a public-facing method for eliciting situated ethical reflection on autonomous driving. We present Red Light, Grey Zone, a web-based, multi-perspective interactive narrative prototype inspired by a real-world autonomous-driving incident. The prototype invites participants to compare stakeholder perspectives, examine scene materials, and make responsibility judgments in the face of ethical ambiguity. We report an exploratory user study (N=12) examining how differently non-experts responded to the prototype. Our analysis focuses on three dimensions of reflection: ethical cognition, responsibility-focused cri
arXiv:2607.15738v1 Announce Type: new Abstract: Generative AI (GenAI) is increasingly used by students for programming explanation, debugging, and assignment support. Yet unrestricted large language model (LLM) tutors can hallucinate, contradict course policy, reveal complete solutions, and foster passive dependence. This paper presents EduGuard, a safe retrieval-augmented generation (RAG) tutoring framework for introductory programming. EduGuard integrates query understanding, instructor-approved course retrieval, pedagogical strategy selection, rubric-aware generation, claim-level verification, and overreliance control. To make evaluation provenance explicit, we construct BILearn-CS, a 600-query instructor-authored, TA-validated benchmark spanning concept questions, debugging cases, misconceptions, assignment-support requests, code-mixed Bangla-English queries, and adversarial direct-answer prompts. Moving beyond a synthetic-only benchmark, we further evaluate on a 150-query public C
arXiv:2607.15704v1 Announce Type: new Abstract: Policymakers around the world face the question of how to use artificial intelligence in general, and large language models in particular, to improve the policymaking process. Used well, large language models can strengthen the collection, interpretation and synthesis of policy-relevant information and the drafting of policy-relevant output. Yet the use of large language models in policymaking is associated with risks. Output that is plausible but not necessarily correct, bias resulting from unrepresentative training data, the exposure of sensitive information and, over time, deskilling and dependency can erode trust if large language models are not used thoughtfully. The CRAFT principles - control, rigour, accountability, fairness and transparency - offer a way to make the most of large language models in policymaking while managing the risks.
arXiv:2607.15436v1 Announce Type: new Abstract: Human mobility data have become fundamental to research across transportation, public health, urban science, and disaster resilience. However, existing mobility datasets typically capture only isolated aspects of travel behavior and rarely provide linked multimodal journeys together with network-level route representations and population-level inference. Here we present Complete Trip, a mobility dataset that reconstructs linked multimodal travel behavior from passively collected smartphone location-based services (LBS) data. The first released implementation covers six counties in Utah throughout 2020 and represents journeys across car, bus, rail, and active transportation through a four-stage workflow consisting of trip identification, mode imputation, route reconstruction, and trip linking. Complete Trip preserves journey-level relationships by linking sequential travel segments where multiple segments belong to the same travel episode,
arXiv:2607.15397v1 Announce Type: new Abstract: Electronic health record audit logs record timestamped actions through which clinical work is carried out. Generated as operational metadata, they now support research on clinician effort, patient outcomes, care-team coordination, and workflow structure. This Perspective explains that breadth by articulating audit logs as multi-axial event streams and drawing implications for representation learning, evaluation, and governance. Each logged action belongs simultaneously to multiple clinically meaningful relations: a clinician's work, a patient's trajectory, a team's activity, and a recurring workflow. This structure motivates foundation-model pretraining to learn reusable representations over the raw stream. Reading audit logs as multi-axial traces specifies what such representations must preserve, how their value should be tested, and how their use should be governed.
arXiv:2607.15364v1 Announce Type: new Abstract: Social media companies have shifted away from human fact-checkers and instead have embedded conversational Large Language Models (LLM) on their platforms. LLM chatbots differ from human fact-checkers in many ways that may shape user responses to corrections. Of particular interest in this study is that LLM chatbots can be ideologically configured via the content emphasized in their responses, the sources cited, and the configured persona. Using data from two within-subjects experiments (n=705), this paper investigates the effectiveness of fact checking information from ideologically configured LLM chatbots. We find that LLM fact-checkers significantly shift trust in true and false political news headlines, even when the chatbot is politically incongruent with the user. The perceived political congruency between the participant and the bot matters only when headlines are politically distant. That is, trust in correctly labeled true headlin
Seventh-grade math teacher Dylan Kane decided to conduct an experiment in his classes by going cold turkey on ed-tech.
Many years ago, around 2010, I attended a professional development program in Houston called Literacy Through Photography, at a time when I was searching for practical ways to strengthen comprehension, discussion, and reading fluency, particularly for students who found traditional print-based tasks challenging.
Washington, DC’s education paradox: rapid gains, low proficiency.
Last year, one of my strongest students could solve complex equations flawlessly--but paused when I asked a simple question: “Why does this method work?”
Practical advice for district leaders implementing AI in their district.
Edcafe AI is an eduction specific tool designed to help along the entire teaching cycle.
Far too many students enter math class expecting to fail. For them, math isn’t just a subject--it’s a source of anxiety that chips away at their confidence and makes them question their abilities.
Article URL: https://greyenlightenment.com/2025/11/15/aristocratic-tutoring-cannot-explain-von-neumanns-success/ Comments URL: https://news.ycombinator.com/item?id=45949852 Points: 1 # Comments: 4
KFF found that insurers denied 12%-18% of standard prior authorization requests in 2025, with significant variation among insurers and gaps in transparency. The post KFF: Insurers Denied 12%-18% of Prior Authorization Requests in 2025 appeared first on MedCity News .
Migraine drugs developer Slate Medicines is going public in a reverse merger with Fulcrum Therapeutics. The biotech’s lead antibody drug blocks two novel migraine targets, offering the potential for better efficacy compared to other next-generation migraine drugs in R&D. The post Slate Medicines’ Merger and $245M Private Placement Fuel Mission in Migraine appeared first on MedCity News .
FLAGSTAFF, Ariz. — Parent-teacher conferences can conjure a familiar scene: adults crammed into child-size chairs, listening to teachers run through a list of students’ achievements and struggles. For many families, they can also mean frustration. Today’s school conferences are sometimes 15 to 20 minutes, with little time for parents to ask their own questions. Adults may arrive […]
Few details are known without the rule’s text, which has yet to be published in the Federal Register, but the change may pose difficulties for employers.
The move comes after the board shared concerns with President Torey Alston, including over students’ low passage rates on nursing licensure exams.
Consumer diagnostics will be one of several discussions at the INVEST Digital Health conference focused on power shifting to the consumer in healthcare. The conference is scheduled for October 29 in Dallas at Pegasus Park, in partnership with Health Wildcatters. The post The Rise of Consumer Diagnostics and Emerging Trends appeared first on MedCity News .
Justices are set to consider two cases out of Texas that aim to block such laws, which have regained momentum in recent years.
This year’s startling collapse of New York City’s reading scores, followed by last year’s big gains, has some experts asking: Did something go wrong with the test itself? There is no clear evidence there is a problem, experts emphasize, but the unusually wide swing in scores warrants careful investigation, multiple testing experts told Chalkbeat this […]
In 2025, the Workforce Pell Grant was announced as part of the Working Families Tax Cuts Act. On August 4, the first program was approved for the new Workforce Pell Grant, a milestone in higher education. To be eligible, institutions must prove a 70% completion rate and 70% job placement rate — in the industry or field of the program — within 180 days. Programs must also run between eight to 15 weeks in length. “If an institution is starting now, they’re six months too late — minimum,” says Wesley Bange, a chief information and technology officer at Bossier Parish Community College. Meeting…
Conversations about Education Savings Account programs seem to start in the same place: the money. Where is it going? How is it being used? Who is benefiting? Understandably so. When taxpayer money moves, people talk. But being on the frontlines for several years as a certified literacy specialist — working with families, taking the calls, […]
Quantifying cyber risk in terms of financial exposure helps K–12 IT teams justify their spending and make the case that security is an enterprise-critical endeavor. This approach pushes districts to audit existing security tools, prioritize threats based on potential financial impact and measure success in dollar-based risk exposure rather than technical metrics. Here’s how a quantified risk analysis can help K–12 security leaders identify which investments meaningfully reduce exposure and which add cost and complexity without real value. Click the banner below to learn how a risk…
Despite Seattle Public Schools’ district policy to issue devices to each of its nearly 50,000 students, some highly vocal parents are successfully opting their students out of technology altogether. The post These kids are learning without technology in Seattle Public Schools appeared first on District Administration .
State Rep. Jared Patterson is preparing legislation that would move the start of the school year to after Labor Day. The post Texas lawmakers push for later school start dates amid summer heat appeared first on District Administration .
Most healthcare organizations are experimenting with AI. Few are preparing to manage AI agents as participants in everyday healthcare workflows. The post Healthcare Is Deploying AI Tools — It’s Not Ready for AI Colleagues appeared first on MedCity News .
Prospective home buyers are often experiencing transition in their personal lives. Perhaps a wedding — or divorce — is on the horizon. Maybe their kids have grown up and moved out, or their financial circumstances have changed. In many cases, though, people are looking to move because they want to start or grow their families, said Daryl […]
[Sponsored] A recent webinar, sponsored by Verato, offered insights from executives at SCAN Health Plan and the Alliance of Community Health Plans on a wide range of tech challenges in healthcare from fragmented data to technology architecture to patient identity. The post How Payers and Health Plans Think of Identity and the Risks of Fragmented Data appeared first on MedCity News .
Updated August 18, 2026 Every few years, testing experts at the U.S. Department of Education weigh state assessments against their “gold standard,” the National Assessment of Educational Progress, also known as “the nation’s report card.” In a review released in 2021, two states stood out, but not in a good way. Both Iowa and Virginia […]