AI Research

AI grading issue affects hundreds of MCAS essays in Mass. – NBC Boston

Published

7 hours ago

September 12, 2025

The use of artificial intelligence to score statewide standardized tests resulted in errors that affected hundreds of exams, the NBC10 Investigators have learned.

The issue with the Massachusetts Comprehensive Assessment System (MCAS) surfaced over the summer, when preliminary results for the exams were distributed to districts.

The state’s testing contractor, Cognia, found roughly 1,400 essays did not receive the correct scores, according to a spokesperson with the Department of Elementary and Secondary Education.

DESE told NBC10 Boston all the essays were rescored, affected districts received notification, and all their data was corrected in August.

So how did humans detect the problem?

We found one example in Lowell. Turns out an alert teacher at Reilly Elementary School was reading through her third-grade students’ essays over the summer. When the instructor looked up the scores some of the students received, something did not add up.

The teacher notified the school principal, who then flagged the issue with district leaders.

“We were on alert that there could be a learning curve with AI,” said Wendy Crocker-Roberge, an assistant superintendent in the Lowell school district.

AI essay scoring works by using human-scored exemplars of what essays at each score point look like, according to DESE.

DESE pointed out the affected exams represent a small percentage of the roughly 750,000 MCAS essays statewide.

The AI tool uses that information to score the essays. In addition, humans give 10% of the AI-scored essays a second read and compare their scores with the AI score to make sure there aren’t discrepancies. AI scoring was used for the same amount of essays in 2025 as in 2024, DESE said.

Crocker-Roberge said she decided to read about 1,000 essays in Lowell, but it was tough to pinpoint the exact reason some students did not receive proper credit.

However, it was clear the AI technology was deducting points without justification. For instance, Crocker-Roberge said she noticed that some essays lost a point when they did not use quotation marks when referencing a passage from the reading excerpt.

“We could not understand why an individual score was scored a zero when it should have gotten six out of seven points,” Crocker-Roberge said. “There just wasn’t any rhyme or reason to that.”

District leaders notified DESE about the problem, which resulted in approximately 1,400 essays being rescored. The state agency says the scoring problem was the result of a “temporary technical issue in the process.”

According to DESE, 145 districts were notified that had at least one student essay that was not scored correctly.

“As one way of checking that MCAS scores are accurate, DESE releases preliminary MCAS results to districts and gives them time to report any issues during a discrepancy period each year,” a DESE spokesperson wrote in a statement.

Mary Tamer, the executive director of MassPotential, an organization that advocates for educational improvement, said there are a lot of positives to using AI and returning scores back to school districts faster so appropriate action can be taken. For instance, test results can help identify a child in need of intervention or highlight a lesson plan for a teacher that did not seem to resonate with students.

“I think there’s a lot of benefits that outweigh the risks,” said Tamer. “But again, no system is perfect and that’s true for AI. The work always has to be doublechecked.”

DESE pointed out the affected exams represent a small percentage of the roughly 750,000 MCAS essays statewide.

However, in districts like Lowell, there are certain schools tracked by DESE to ensure progress is being made and performance standards are met.

That’s why Crocker-Roberge said every score counts.

With MCAS results expected to be released to parents in the coming weeks, the assistant superintendent is encouraging other districts to do a deep dive on their student essays to make sure they don’t notice any scoring discrepancies.

“I think we have to always proceed with caution when we’re introducing new tools and techniques,” Crocker-Roberge said. “Artificial intelligence is just a really new learning curve for everyone, so proceed with caution.”

There’s a new major push for AI training in the Bay State, where educators are getting savvier by the second. NBC10 Boston education reporter Lauren Melendez has the full story.

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AI Research

Artificial Intelligence Cheating | Nation

Published

57 minutes ago

September 12, 2025

Jae C. Hong - AP

Artificial Intelligence Cheating | Nation | hjnews.com

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AI Research

Artificial Intelligence in Healthcare Market : A Study of

Published

1 hour ago

September 12, 2025

The Editors

Global Artificial Intelligence in Healthcare Market size was valued at USD 27.07 Bn in 2024 and is expected to reach USD 347.28 Bn by 2032, at a CAGR of 37.57%

Artificial Intelligence (AI) in healthcare is reshaping the industry by enabling faster diagnosis, personalized treatment, and enhanced operational efficiency. AI-driven tools such as predictive analytics, natural language processing, and medical imaging analysis are empowering physicians with deeper insights and decision support, reducing human error and improving patient outcomes. Moreover, AI is revolutionizing drug discovery, clinical trial optimization, and remote patient monitoring, making healthcare more proactive and accessible in both developed and emerging markets.

The adoption of AI in healthcare is also being accelerated by the rising demand for telemedicine, wearable health devices, and real-time data-driven solutions. From virtual health assistants to robotic surgery, AI is driving innovation across patient care and hospital management. However, challenges such as data privacy, ethical considerations, and regulatory frameworks remain crucial in ensuring responsible deployment. As AI continues to integrate with IoT, cloud, and big data platforms, it is set to create a connected healthcare ecosystem that prioritizes precision medicine and patient-centric solutions.

Get a sample of the report https://www.maximizemarketresearch.com/request-sample/21261/

Major companies profiled in the market report include

BP Target Neutral . JPMorgan Chase & Co. . Gold Standard Carbon Clear . South Pole Group . 3Degrees . Shell. EcoAct.

Research objectives:

The latest research report has been formulated using industry-verified data. It provides a detailed understanding of the leading manufacturers and suppliers engaged in this market, their pricing analysis, product offerings, gross revenue, sales network & distribution channels, profit margins, and financial standing. The report’s insightful data is intended to enlighten the readers interested in this business sector about the lucrative growth opportunities in the Artificial Intelligence in Healthcare market.

Get access to the full description of the report @ https://www.maximizemarketresearch.com/market-report/global-artificial-intelligence-ai-healthcare-market/21261/

It has segmented the global Artificial Intelligence in Healthcare market

by Offering

Hardware

Software

Services

by Technology

Machine Learning

Natural Language Processing

Context-Aware Computing

Computer Vision

Key Objectives of the Global Artificial Intelligence in Healthcare Market Report:

The report conducts a comparative assessment of the leading market players participating in the globalArtificial Intelligence in Healthcare

The report marks the notable developments that have recently taken place in the Artificial Intelligence in Healthcare industry

It details on the strategic initiatives undertaken by the market competitors for business expansion.

It closely examines the micro- and macro-economic growth indicators, as well as the essential elements of theArtificial Intelligence in Healthcaremarket value chain.

The repot further jots down the major growth prospects for the emerging market players in the leading regions of the market

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A Unified Model for Robot Interaction, Reasoning and Planning

Published

3 hours ago

September 12, 2025

Huang Fang, Mengxi Zhang, Heng Dong, Wei Li, Zixuan Wang, Qifeng Zhang, Xueyun Tian, Yucheng Hu, Hang Li

[Submitted on 1 Sep 2025 (v1), last revised 11 Sep 2025 (this version, v2)]

View a PDF of the paper titled Robix: A Unified Model for Robot Interaction, Reasoning and Planning, by Huang Fang and 8 other authors

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Abstract:We introduce Robix, a unified model that integrates robot reasoning, task planning, and natural language interaction within a single vision-language architecture. Acting as the high-level cognitive layer in a hierarchical robot system, Robix dynamically generates atomic commands for the low-level controller and verbal responses for human interaction, enabling robots to follow complex instructions, plan long-horizon tasks, and interact naturally with human within an end-to-end framework. Robix further introduces novel capabilities such as proactive dialogue, real-time interruption handling, and context-aware commonsense reasoning during task execution. At its core, Robix leverages chain-of-thought reasoning and adopts a three-stage training strategy: (1) continued pretraining to enhance foundational embodied reasoning abilities including 3D spatial understanding, visual grounding, and task-centric reasoning; (2) supervised finetuning to model human-robot interaction and task planning as a unified reasoning-action sequence; and (3) reinforcement learning to improve reasoning-action consistency and long-horizon task coherence. Extensive experiments demonstrate that Robix outperforms both open-source and commercial baselines (e.g., GPT-4o and Gemini 2.5 Pro) in interactive task execution, demonstrating strong generalization across diverse instruction types (e.g., open-ended, multi-stage, constrained, invalid, and interrupted) and various user-involved tasks such as table bussing, grocery shopping, and dietary filtering.