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:2608.25063v1 Announce Type: new Abstract: The purpose of this study was to analyze patterns of artificial intelligence (AI) use and attitudes toward AI among students, faculty, and administrative staff at a large university specializing in teacher education. The analytical sample comprised 1809 students, 250 faculty members, and 62 administrative staff members (N = 2121). Three role-adapted 75-item questionnaires covered the frequency and contexts of AI use, perceived usefulness, trust and control, academic integrity concerns, responsible-use norms, institutional policy clarity, and perceived improvement in output quality. Data analysis included descriptive statistics, Welch group comparisons, pooled ordinary least squares (OLS) models, reliability and dimensionality checks for observed indices, and exploratory student-only K-means clustering. The results revealed a pronounced AI adaptation gap across university groups. Students reported higher current AI-use intensity and percei
Article URL: https://www.scientificamerican.com/article/medical-education-needs-rethinking/ Comments URL: https://news.ycombinator.com/item?id=24293391 Points: 2 # Comments: 0
When I shipped Gramms AI to the App Store, I ran straight into a question that every developer building for kids will eventually face: What does “age-appropriate” actually mean in practice? And how do you build systems that enforce it reliably?
Student support and tech professions are projected to make gains while teaching positions shrink.
Across the country, districts are confronting a growing PK-12 leadership pipeline crisis. Veteran principals, assistant principals, and district administrators are retiring at increasing rates, yet there is not a sufficiently prepared pool of aspiring leaders ready to step into these roles.
The commission approved a request for public comment on whether it should reconsider the 30-year program that helps schools connect to the internet.
Dive Snapshot: Rep. Suzanne Bonamici filed three articles of impeachment Thursday against U.S. Education Secretary Linda McMahon, accusing her of illegally dismantling the U.S. Department of Education and lying to Congress. Bonamici pointed to McMahon’s moves to transfer...
Rep. Suzanne Bonamici filed impeachment articles accusing the secretary of illegally transferring the department's duties to other federal agencies.
Class Disrupted is an education podcast featuring author Michael Horn and Futre’s Diane Tavenner in conversation with educators, school leaders, students and other members of school communities as they investigate the challenges facing the education system in the aftermath of the pandemic — and where we should go from here. Find every episode by bookmarking […]
Judge Tosses ED’s ‘Professional’ Degree Definition, Likely Aiding Student Borrowers Ryan Quinn Thu, 06/25/2026 - 01:29 PM The ruling says the Education Department violated Congress’s instructions by adding criteria strictly limiting which degrees qualify for higher federal student loan borrowing caps. Byline(s) Ryan Quinn
The agency released widely contested regulations this spring to block access to higher borrowing limits for many graduate students.
The agency released widely contested regulations this spring that blocked access to higher borrowing limits for many graduate students.
The agency released widely contested regulations this spring that blocked access to higher borrowing limits for many graduate students.
In May, a cybercriminal group executed the largest educational data breach on record, targeting Instructure, the company behind the Canvas learning management system. The breach impacted 275 million students, teachers and staff across approximately 9,000 education institutions. Many took quick action. The University of Wisconsin-Madison, for example, issued real-time alerts warning faculty and students: “If Canvas prompts you to perform any action — such as clicking a link, logging in, resetting your password or completing any tasks — do not proceed.” For universities, the incident…
Kansas City Public Schools teachers will receive a 5% base salary raise after the school board approved a new collective bargaining agreement with the Kansas City Federation of Teachers, the district’s teachers union. Superintendent Jennifer Collier called the raise “historic.” “This is the highest pay increase for KCPS teachers in recent memory and brings our […]
Linda McMahon became the first U.S. education secretary to be the target of impeachment proceedings Thursday. Rep. Suzanne Bonamici, a member of the House education committee, filed three articles of impeachment against McMahon, noting the secretary’s “willful intent to unilaterally dismantle and eliminate the Department of Education.” Bonamici announced her plans a week ago, prompting […]
In June 2020, amid the COVID-19 pandemic, Nestling House, a childcare center in Milwaukee, Wisconsin, was preparing to reopen after closing down in mid-March, like so many other childcare programs around the country. It would be a process, with some rooms ready before others, and the leadership team knew things would be different once the […]
Higher education has been inching away from entrance exams. Less than 10% of U.S. institutions that grant bachelor’s degrees require a score from the SAT, or its fellow ACT test, for the fall 2026 admissions cycle. The post 100 years ago, students across took the first SAT. Where is it headed now? appeared first on District Administration .
The state’s public university system board on Thursday advanced the proposal, which has garnered support from Republican Gov. Ron DeSantis.
As a special education advocate in Oklahoma, Lucia Frohling handles about 40 cases per year in which schools reduce class time for students with disabilities, often for behavior issues or serious medical conditions. When she negotiates with school officials, she often leans on a 2022 warning from the federal government that such “informal removals” — […]
To have a sustainable workforce in 2026, CNOs must partner closely with CHROs and other TA leaders to streamline recruiting and do more than make roles appealing to applicants. From a talent acquisition (TA) standpoint, recruiting isn't just about filling roles with just anyone anymore. According to Jennifer Spinelli , director of system talent acquisition at Beebe Healthcare , the goal now is to reach sustainability by building the right mix of permanent staff pipelines and having the flexibility to be proactive instead of reactive. Here are three ways that CNOs can partner with TA leaders to build a more sustainable nursing workforce, according to Spinelli. Click here to read the accompanying story . Pillar: CNO Image: Tags: HR nurses nursing recruitment retention Secondary Pillars: CNO Article Type: Analysis Published Date: Wednesday, June 24, 2026 Hide sidebars: Render small main image:
A student’s school experience can shift dramatically--not just from year to year but from classroom to classroom each day. They may feel seen and encouraged by one teacher, but overlooked and underestimated by another.
The conversation around AI in schools is changing almost as rapidly as the technology. Here are some recent trends.
Community colleges serve as a bridge between education and employment, helping students gain the skills needed for local and regional jobs. But with workforce needs evolving more rapidly, these institutions are under pressure to ensure programs remain aligned with labor market demand. Data analytics and artificial intelligence (AI) are helping community colleges leverage labor market intelligence (LMI) to make more informed decisions about program creation, student success initiatives and workforce development strategies. However, overcoming organizational challenges, fragmented systems, data…
Kansas Sides With DOJ Against State Tuition Equity Law Sara Weissman Thu, 06/25/2026 - 03:00 AM Byline(s) Sara Weissman
When the Record Doesn’t Follow the Learner quintina.barne… Thu, 06/25/2026 - 03:00 AM What practitioners running prison education programs reveal about a failure that affects all learners. Byline(s) Quintina Barnett Gallion
U of Michigan Sticks With Early Decision Admission, Bucking Faculty Ryan Quinn Thu, 06/25/2026 - 03:00 AM Byline(s) Ryan Quinn
New ‘SOURCE’ Tracks Private Money to Higher Ed kathryn.palmer… Thu, 06/25/2026 - 03:00 AM Byline(s) Kathryn Palmer
Persistence, Retention Among Black and Hispanic Freshmen Reach Decade Highs gianna.jakubowski Thu, 06/25/2026 - 03:00 AM While persistence and retention rates for the entering class of 2024 remained the same as the previous year, Black and Hispanic students saw slight increases in both, a new report finds. Byline(s) Gianna Jakubowski
New Compilation: Designing a More Connected Campus colleen.flaherty Thu, 06/25/2026 - 03:00 AM Byline(s) IHE Staff
Meet the Externs: How Faculty Use Workplace Experience to Help Students Emma Whitford Thu, 06/25/2026 - 03:00 AM Faculty-to-industry bridge programs have been popular for years, but this summer the professor-externs are focused on bringing AI skills and understanding back to their students. Byline(s) Emma Whitford
Can Price-First Admissions Improve College Access? Joshua.Bay Thu, 06/25/2026 - 03:00 AM Cornell College’s program gives students financial aid estimates before they apply, reducing affordability uncertainty and influencing enrollment decisions. Byline(s) Joshua Bay
New data from the National Student Clearinghouse Research Center also showed that Black and Hispanic persistence rates reached decade highs.
The contracts offer a way for school districts to lock in costs as electricity prices rise, says Louis Maltezos, co-president of the energy infrastructure company.
About 60% of Americans support some form of teacher-led school prayer, but most say student participation should be optional, Pew Research found.
Even a federal law enforcement vehicle parked a block and a half away were enough to impact attendance, an Annenberg researcher said.
The Los Angeles Unified Board voted unanimously to appoint Andres Chait, a longtime district administrator, as superintendent days after his predecessor resigned. “This board’s decision reflects the confidence in Mr. Chait’s leadership, his decades of service to Los Angeles Unified, and his demonstrated ability to guide the district during this period of transition,” said board […]
arXiv:2606.23870v2 Announce Type: replace-cross Abstract: PLCverif is the most mature open-source platform for PLC formal verification, developed at CERN and in production use since 2019. Yet it has two fundamental limitations: no support for Ladder Diagram (LD) programs, the dominant PLC notation, and reliance on CBMC as its primary backend, which restricts verification to bounded proofs. The PLCverif authors themselves identified ESBMC as the appropriate backend improvement. Prior work established ESBMC-PLC (a textual LD frontend with k-induction) and ESBMC-GraphPLC (graphical PLCopen XML support); together, they cover LD with unbounded proofs but not Structured Text (ST), and graphical LD with timer/counter function blocks remains unverifiable. This paper presents ESBMC-PLC+, a unified framework that closes both gaps: (1) an ST/SCL frontend via the MATIEC IEC 61131-3 compiler, routing C-compiled ST to ESBMC with nondeterministic input modeling and YAML property injection; (2) functi
arXiv:2606.23195v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) agents increasingly rely on memory systems to maintain long-term coherence. Recent work shows that agent memories degrade during continuous consolidation. However, existing research assumes memories are derived from unbiased experiences. In this work, we identify and formalize a novel phenomenon: Memory Contagion -- the cross-temporal propagation of evaluator bias through agent memory. We show that when agents are trained or guided by biased evaluators, their experiences become biased; when these trajectories are stored and consolidated into memory, the bias propagates to future agents retrieving from the same memory store, even when consolidation is perfect (oracle). Across two bias types (length preference, authority bias) and four experimental phases, we demonstrate: (1) Memory Contagion occurs for length bias even with perfect consolidation on older models (Gamma_A = 13.18, DeepSeek V4-Chat), while
arXiv:2606.22873v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) are increasingly deployed in consumer, medical, financial, and enterprise applications. This broad deployment expands the safety surface: risks can arise from multimodal question answering, assistant responses, and cross-modal composition, while moderation policies may vary across products, regions, and deployment stages. Most existing guardrails either rely on fixed taxonomies or target only a narrow set of interaction settings, which limits their adaptability when safety rules change at deployment time. We present \textbf{SingGuard}, a policy-adaptive multimodal guardrail model family for safety assessment in multimodal conversations. SingGuard treats the active policy as a runtime input: given natural-language rules, it checks the target content against the active policy rule by rule and predicts both the safety label and the triggered rule. To balance efficiency and interpretability, SingGuard s
arXiv:2606.22485v2 Announce Type: replace-cross Abstract: Decision-making in real-world settings rarely follows a fixed script. Instead, it unfolds as a dynamic reasoning process in which the appropriate course of action evolves as new context and data become available. Traditional Business Process Management systems provide rigor, determinism, and auditability, yet they generally struggle to adapt their execution at runtime. Conversely, agentic systems based on Large Language Models (LLMs) bring flexibility to decision-making, but they are inherently opaque, often unreliable, and suffer from significant scalability constraints when operating over large datasets. To combine these complementary paradigms, we introduce VADAOrchestra, a neurosymbolic framework that models complex workflows as evolving reasoning processes. The framework adopts a hybrid approach: given a user query and a collection of data sources, an LLM-based orchestrator incrementally plans and adapts the workflow. This
arXiv:2606.19626v2 Announce Type: replace-cross Abstract: AI pipelines that reason quantitatively over technical text depend on input where physical quantities, numbers, units, and symbolic expressions arrive intact; when these entities fragment at tokenization, errors propagate downstream. Byte-Pair Encoding, optimized for vocabulary compression, is blind to such entities and fragments them into arbitrary subwords -- a problem aggravated in technical Brazilian Portuguese. We present TOTEN, a knowledge-based system whose input representation preserves each technical entity as a whole, typed unit: vocabulary is not derived statistically but classified declaratively under a formal ontology of engineering entities (OEE). The core is the triple : types, principles, and invariants; a classifier mapping raw text into typed regions; and instantiators yielding a self-descriptive representation. Integrity rests on deterministic coupling to three external authorities: Pint (dimensional), Unicode
arXiv:2606.19157v2 Announce Type: replace-cross Abstract: AudioLLMs enable speech recognition conditioned on textual prompts such as domain descriptions or entity lists. However, it remains unclear whether these models genuinely utilise such context or rely on parametric knowledge learned during pretraining. Existing benchmarks cannot answer this question because they evaluate transcription under fixed prompting conditions and rarely include explicit contextual inputs. We introduce IndicContextEval, a 56-hour multilingual benchmark of natural speech from 555 speakers across 8 Indian languages and 23 professional domains. We design a 7-level prompting framework that progressively introduces contextual signals, including metadata, natural-language descriptions, entity lists in English and native script, and adversarial prompts with incorrect entities. Evaluating five models reveals substantial differences in context utilisation behaviour, highlighting the need for explicit evaluation of
arXiv:2606.16497v2 Announce Type: replace-cross Abstract: GPU kernel optimization represents a paradigm where functional correctness is assumed and execution efficiency is the objective. We present daVinci-kernel, a reinforcement learning framework that couples skill discovery with skill exploitation through a dynamically evolving skill library. daVinci-kernel jointly trains three agents sharing one LLM backbone: a Skill Selection Agent that retrieves relevant techniques via BM25 and LLM reranking, a Policy Agent that generates multi-turn CUDA/Triton kernels conditioned on selected skills, and a Skill Summary Agent that distills successful rollouts into reusable skills. Candidate skills are added only after execution-based verification confirms reproducible speedups. All three agents share a single LLM backbone, are initialized via a structured SFT cold start on diversity-filtered data, and are then jointly optimized end-to-end with multi-turn REINFORCE and per-agent advantage estimati
arXiv:2606.07512v2 Announce Type: replace-cross Abstract: Current Vision-Language Models struggle with hours-long videos because processing full-length visual sequences induces prohibitive token explosion and attention dilution. To overcome this, we introduce MemDreamer to decouple perception and reasoning, shifting long-video understanding into an agentic exploration process. As a plug-and-play framework, it incrementally streams videos to construct a Hierarchical Graph Memory, a top-down three-tier architecture for semantic abstraction, anchored by a foundational graph capturing spatiotemporal and causal relations. During inference, the reasoning model employs agentic tool-augmented retrieval, navigating hierarchies, searching nodes, and traversing logical edges via an Observation-Reason-Action loop. Experiments show MemDreamer achieves SOTA results across four mainstream benchmarks, narrowing the gap with human experts to only 3.7 points. It constrains the reasoning context window t
arXiv:2605.05097v3 Announce Type: replace-cross Abstract: LLMs are trained once, then deployed into a world that never stops changing. External memory compensates for this, but most systems manage it explicitly rather than letting it adapt on its own. Biological memory works differently: coupled multi-timescale dynamics make new associations immediately usable, strengthen what repetition confirms, and let the rest fade. We argue that external memory should follow a similar principle. In Memini, this view takes the form of an associative memory that organizes knowledge as a directed graph. Each edge carries two coupled internal variables, one fast and one slow, following the Benna-Fusi model of synaptic consolidation. From this coupling, episodic sensitivity, gradual consolidation, and selective forgetting are expected to emerge as facets of a single mechanism, reframing external memory as a learning substrate that reorganizes through its own dynamics. This workshop article describes an
arXiv:2604.03314v2 Announce Type: replace-cross Abstract: Foundation models have revolutionized AI, but adapting them efficiently for multimodal tasks, particularly in dual-stream architectures composed of unimodal encoders, such as DINO and BERT, remains a significant challenge. ParameterEfficient Fine-Tuning (PEFT) methods like LowRank Adaptation (LoRA) enable lightweight adaptation, yet they operate in isolation within each modality, limiting their ability in capturing cross-modal interactions. In this paper, we take a step in bridging this gap with Cross-Modal LowRank Adaptation (CoLA), a novel PEFT framework that extends LoRA by introducing a dedicated inter-modal adaptation pathway alongside the standard intra-modal one. This dual-path design enables CoLA to adapt unimodal foundation models to multimodal tasks effectively, without interference between modality-specific and crossmodal learning. We evaluate CoLA across a range of vision-language (RefCOCO, RefCOCO+, RefCOCOg) and au
arXiv:2603.10371v2 Announce Type: replace-cross Abstract: Speech tokenizers are essential for connecting speech to large language models (LLMs) in multimodal systems. Speech tokenizers are expected to preserve both semantic and acoustic information for downstream understanding and generation tasks. However, emerging evidence suggests that the term "semantic" in speech processing does not align with linguistic lexical-semantic, leading to a mismatch between speech and text modality. In this paper, we systematically analyze the information encoded by several widely used speech tokenizers, evaluating their lexical-semantic and phonetic content through three tasks. Our results show that current tokenizers primarily capture phonetic rather than lexical-semantic structure, deriving practical implications for the design of next-generation speech tokenization methods. Code is released to public at https://github.com/Alexuan/codec_probing_release.
arXiv:2602.17663v2 Announce Type: replace-cross Abstract: HIPE-2026 is a CLEF evaluation lab dedicated to person-place relation extraction from noisy, multilingual historical texts. Building on the HIPE-2020 and HIPE-2022 campaigns, it extends the series toward semantic relation extraction by targeting the task of identifying person-place associations in multiple languages and time periods. Systems are asked to classify relations of two types -- $at$ ("Has the person ever been at this place?") and $isAt$ ("Is the person located at this place around publication time?") -- requiring reasoning over temporal and geographical cues. The lab introduces a three-fold evaluation profile that jointly assesses accuracy, computational efficiency, and domain generalization. By linking relation extraction to large-scale historical data processing, HIPE-2026 aims to support downstream applications in knowledge-graph construction, historical biography reconstruction, and spatial analysis in digital hum
arXiv:2602.06566v3 Announce Type: replace-cross Abstract: Despite recent successes, test-time scaling -- i.e., dynamically expanding the token budget during inference as needed -- remains brittle for vision-language models (VLMs). Unstructured visual reasoning chains entangle perception and reasoning, leading to long, disorganized contexts where small perceptual mistakes may cascade into completely wrong answers. Reasoning also requires expensive reinforcement learning with hand-crafted rewards. Here, we introduce SPARC (Separating Perception And Reasoning Circuits), a modular framework that explicitly decouples visual perception from reasoning. Inspired by sequential sensory-to-cognitive processing in the brain, SPARC implements a two-stage pipeline where the model first performs explicit visual search to localize question-relevant regions, then conditions its reasoning on those regions to produce the final answer. This separation enables independent test-time scaling with asymmetric