With health metrics improving and mitigation measures in place across Massachusetts schools, Elementary and Secondary Commissioner Jeff Riley said Tuesday it's time to begin the process of getting more students back into classrooms. Riley, who is set to join Gov. Charlie Baker and Education Secretary James Peyser for a 2 p.m. press conference on education and COVID-19, told Board of Elementary and Secondary Education members that he plans to ask them in March to give him the authority to determine when hybrid and remote school models no longer count for learning hours, as part of a broader plan to return more students to physical school buildings. Riley said he would take a "phased approach to returning students into the classrooms, working closely with state health officials and medical experts." He said his plan would focus on elementary school students first, with the initial goal of having them learning in-person five days a week this April. "At some point, as health metrics continue to improve, we will need to take the remote and hybrid learning models off the table and return to a traditional school format," Riley said.
As technology and automation rapidly remake a very different future of work, some economists predict that women will benefit the most from the coming disruptions. Although women have no doubt been hardest hit by the COVID-19 economy, in the coming years, women-dominated caring jobs--like nursing, teaching, and providing child and elder care--that aren't easily replaced by machines will be among the fastest-growing occupations and thus more likely to be "future-proof." It's not that many women's jobs won't be automated away. Just as men-dominated mechanical and machine operating jobs are predicted to disappear, so too are women-dominated administrative and clerical jobs. But most of these future-of-work predictions assume women will continue to dominate the care economy. And all because men aren't expected to care.
Here's a Women in Robotics Spotlight, where we share stories from women who are working on all sorts of interesting projects who haven't yet been featured in our Annual Showcase. We hope these stories provide inspiration to everyone to join us working in the field of robotics. And if you're a woman working in robotics, why not contribute your story too! "I love robots however I do find it frustrating when the code that was working the day before doesn't work. I also find it hard supplying my robots with power. I learn online although I do have a few mentors that help me but it's really not easy learning on my own. My favourite thing about robotics is making them, and when they work like they should. My robots make people really happy so I love that. I also love succeeding – the feeling when my robots come to life is unbelievable."
Saving the Los Angeles school year has become a race against the clock -- as campuses are unlikely to reopen until teachers are vaccinated against COVID-19 and infection rates decline at least three-fold, officials said Monday. The urgency to salvage the semester in L.A. and throughout the state was underscored by new research showing the depth of student learning loss and by frustrated parents who organized statewide to pressure officials to bring back in-person instruction. A rapid series of developments Monday -- involving the governor, L.A. Unified School District, the teachers union and the county health department -- foreshadowed the uncertainties that will play out in the high-stakes weeks ahead for millions of California students. "We're never going to get back if teachers can't get vaccinated," said Assemblyman Patrick O'Donnell (D-Long Beach), who chairs the state's Assembly Education Committee and has two high schoolers learning from home. He expressed frustration that educators are not being prioritized by the L.A. County Health Department even as teachers in Long Beach are scheduled for vaccines this week. Although Long Beach is part of L.A. County, it operates its own independent health agency.
Contributions: The Chinese University of Hong Kong (CUHK)-Jockey Club AI for the Future Project (AI4Future) co-created an AI curriculum for pre-tertiary education and evaluated its efficacy. While AI is conventionally taught in tertiary level education, our co-creation process successfully developed the curriculum that has been used in secondary school teaching in Hong Kong and received positive feedback. Background: AI4Future is a cross-sector project that engages five major partners - CUHK Faculty of Engineering and Faculty of Education, Hong Kong secondary schools, the government and the AI industry. A team of 14 professors with expertise in engineering and education collaborated with 17 principals and teachers from 6 secondary schools to co-create the curriculum. This team formation bridges the gap between researchers in engineering and education, together with practitioners in education context. Research Questions: What are the main features of the curriculum content developed through the co-creation process? Would the curriculum significantly improve the students perceived competence in, as well as attitude and motivation towards AI? What are the teachers perceptions of the co-creation process that aims to accommodate and foster teacher autonomy? Methodology: This study adopted a mix of quantitative and qualitative methods and involved 335 student participants. Findings: 1) two main features of learning resources, 2) the students perceived greater competence, and developed more positive attitude to learn AI, and 3) the co-creation process generated a variety of resources which enhanced the teachers knowledge in AI, as well as fostered teachers autonomy in bringing the subject matter into their classrooms.
In December, the University of Texas at Austin's computer science department announced that it would stop using a machine-learning system to evaluate applicants for its Ph.D. program due to concerns that encoded bias may exacerbate existing inequities in the program and in the field in general. This move toward more inclusive admissions practices is a rare (and welcome) exception to a worrying trend in education: Colleges, standardized test providers, consulting companies, and other educational service providers are increasingly adopting predatory, discriminatory, and outright exclusionary student data practices. Student data has long been used as a college recruiting and admissions tool. In 1972, College Board, the company that owns the PSAT, the SAT, and the AP Exams, created its Student Search Service and began licensing student names and data profiles to colleges (hence the college catalogs that fill the mail boxes of high school students who have taken the exams). Today, College Board licenses millions of student data profiles every year for 47 cents per examinee.
Network homophily, the tendency of similar nodes to be connected, and transitivity, the tendency of two nodes being connected if they share a common neighbor, are conflated properties in network analysis, since one mechanism can drive the other. Here we present a generative model and corresponding inference procedure that is capable of distinguishing between both mechanisms. Our approach is based on a variation of the stochastic block model (SBM) with the addition of triadic closure edges, and its inference can identify the most plausible mechanism responsible for the existence of every edge in the network, in addition to the underlying community structure itself. We show how the method can evade the detection of spurious communities caused solely by the formation of triangles in the network, and how it can improve the performance of link prediction when compared to the pure version of the SBM without triadic closure.
Last month, the British television network Channel 4 broadcast an "alternative Christmas address" by Queen Elizabeth II, in which the 94-year-old monarch was shown cracking jokes and performing a dance popular on TikTok. Of course, it wasn't real: The video was produced as a warning about deepfakes--apparently real images or videos that show people doing or saying things they never did or said. If an image of a person can be found, new technologies using artificial intelligence and machine learning now make it possible to show that person doing almost anything at all. The dangers of the technology are clear: A high-school teacher could be shown in a compromising situation with a student, a neighbor could be depicted as a terrorist. Can deepfakes, as such, be prohibited under American law?
For this first time in his life, Pete Peeks was able to use both hands to hang Christmas lights outside his house this year -- thanks to the help of a high school robotics team. Peeks, 38, was born without the full use of his right hand, and though many may take gripping a nail, hammering it in and stringing holiday lights for granted, Peeks said it was beyond his wildest dreams. Early this month, he became one of the latest clients of the Sequoyah High School Robotics Team in Canton, Georgia. The team has designs and 3D- printed custom prosthesis to send for free to people around the world who need them. And as Americans gather for the winter holidays, the students will be at home continuing their work.
Picture this: a small group of middle school students are learning about ancient Egypt, so they strap on a virtual reality headset and, with the assistance of an artificial intelligence tour guide, begin to explore the Pyramids of Giza. The teacher, also journeying to one of the oldest known civilizations via a VR headset, has assigned students to gather information to write short essays. During the tour, the AI guide fields questions from students and points them to specific artifacts and discuss what they see. In preparing the AI-powered lesson on Egypt, the teacher beforehand would have worked with the AI program to craft a lesson plan that not only dives deep into the subject, but figures out how to keep the group moving through the virtual field trip and how to create more equal participation during the discussion. In that scenario, the AI listens, observes and interacts naturally to enhance a group learning experience, and to make a teacher's job easier.