New Jersey schools will remain closed for the remainder of the academic year because of the coronavirus outbreak, Gov. Phil Murphy said Monday. Teachers have been required to conduct remote instruction since schools shuttered in mid-March. New Jersey is among the hardest-hit states in the country with 7,871 COVID-19 fatalities and more than 120,000 positive cases. New Jersey has some 600 school districts and about 1.4 million students enrolled, according to the state Education Department.
"Subjecting 5-year-olds to this technology will not make anyone safer, and we can't allow invasive surveillance to become the norm in our public spaces," said Stefanie Coyle, deputy director of the Education Policy Center for the New York Civil Liberties Union. "Reminding people of their greatest fears is a disappointing tactic, meant to distract from the fact that this product is discriminatory, unethical and not secure." The debate in Lockport has unfolded over nearly two years. The school district initially announced its plans to install a facial recognition security system, called Aegis, in March 2018. The district spent $1.4 million, with money it had been awarded by the state, to install the technology across 300 cameras.
Interactive Educational Systems (IESs) have developed rapidly in recent years to address the issue of quality and affordability of education. Analogous to other domains in AI, there are specific tasks of AIEd for which labels are scarce. For instance, labels like exam score and grade are considered important in educational and social context. However, obtaining the labels is costly as they require student actions taken outside the system. Likewise, while student events like course dropout and review correctness are automatically recorded by IESs, they are few in number as the events occur sporadically in practice. A common way of circumventing the label-scarcity problem is the pre-train/fine-tine method. Accordingly, existing works pre-train a model to learn representations of contents in learning items. However, such methods fail to utilize the student interaction data available and model student learning behavior. To this end, we propose assessment modeling, fundamental pre-training tasks for IESs. An assessment is a feature of student-system interactions which can act as pedagogical evaluation, such as student response correctness or timeliness. Assessment modeling is the prediction of assessments conditioned on the surrounding context of interactions. Although it is natural to pre-train interactive features available in large amount, narrowing down the prediction targets to assessments holds relevance to the label-scarce educational problems while reducing irrelevant noises. To the best of our knowledge, this is the first work investigating appropriate pre-training method of predicting educational features from student-system interactions. While the effectiveness of different combinations of assessments is open for exploration, we suggest assessment modeling as a guiding principle for selecting proper pre-training tasks for the label-scarce educational problems.
For years, the Denver public school system worked with Video Insight, a Houston-based video management software company that centralized the storage of video footage used across its campuses. So when Panasonic acquired Video Insight, school officials simply transferred the job of updating and expanding their security system to the Japanese electronics giant. That meant new digital HD cameras and access to more powerful analytics software, including Panasonic's facial recognition, a tool the public school system's safety department is now exploring. Denver, where some activists are pushing for a ban on government use of facial recognition, is not alone. Mass shootings have put school administrators across the country on edge, and they're understandably looking at anything that might prevent another tragedy.
LONDON--(BUSINESS WIRE)--The artificial intelligence market in the US education sector is expected to post a CAGR of nearly 48% during the period 2018-2022, according to the latest market research report by Technavio. The increasing emphasis on customized learning paths using AI will be one of the major drivers in the global artificial intelligence market in the US education sector. The education system of the US is well developed and teachers and students in the country are aware about AI technology. This increases the adoption of artificial intelligence in the education sectors of the US. Moreover, the growing reliance on machine learning technologies for the collection of data about student performance will contribute to expanding the artificial intelligence market in the US education sector.
How do OfSTED determine which schools to inspect? On Wednesday 11th April, I attended an NAHT meeting, a new commission on accountability, spanning every phase and sector of education. Over the next few months it will canvass the views of some of the foremost thinkers in this area of education policy with the aim to have interim findings before the summer term and to publish our full report in September 2018. This post captures a presentation delivered by an OfSTED representative and not the meeting itself. When will [XYZ school] be inspected?
Education systems face a multitude of challenges in today's fast-moving world. Teacher workload is ever-increasing, while delivering personalised lessons to students and fostering their critical thinking skills are crucial but elusive goals. Many people lack access to high-quality learning materials and qualified professors. Fortunately, technologies such as artificial intelligence (AI) can provide schools with much needed assistance, and companies have developed smart algorithms that refine educational experiences in many different ways. Whether through personalised learning and smart content or through transcribing words and improving cognitive performance, AI-driven tools are transforming the way children learn and develop new skills.
About a month ago in Pittsburgh, we brought together a group of educators, students, and technology users to ponder some big unwieldy questions about the intersection of education, artificial intelligence, and youth media. But instead of having attendees passively ingest ideas from a speaker on stage, the event started by giving every guest a chance to pause, think, and respond to a series of questions. How often do we draw the line between what we can do with tech to what we should do with it? I see a lot of focus on the "risk" of online spaces. When profit is the motivation of AI systems, there is always an overlooking of what people actually need and/or want.
Artificial intelligence has existed as a field for more than 50 years, but in pace with technological developments in recent years, the area has found increasing numbers of applications and has been the subject of increasing attention. New methods and technologies mean that the mobile phone not only understands what we say, but also translates between languages as quickly as we speak, recognizes faces. There are methods and technologies of artificial intelligence that lie at the core of self-driving cars and robots that perform precise surgical procedures. Facial recognition in stores, robotic sellers who submit offers based on past behaviors, facial recognition in stores, language assistants (like Alexa or Google Home) who are always listening and making recommendations based on recorded conversations. Al is a subject area that is changing how we live and work and how the future will be.