In the pandemic-era of online learning, professors have had to double as video producers. Hollywood-style lighting, new microphones, and cameras set (or stacked) to just the right height are just a few of the investments many have had to make. That’s in addition to time spent converting in-person teaching plans to video recordings. Professors are increasingly using videos to disseminate lectures and other instructional content to their students, and students are now watching hours of recorded videos each week for their courses.
Although this is the new normal, it provokes an important question: Are videos as effective for student learning as in-person instruction? Or has the nearly universal shift to remote, video-based learning resulted in a net learning loss for students?
A new meta-analysis provides insight into the effectiveness of instructional videos in higher education. The primary findings show that when instructional videos fully replace other methods like in-person instruction, videos are marginally more effective for student learning. But when videos are added to in-person instruction, students experience even greater learning gains.
PLOS Global Public Health is a global forum for public health research that reaches across disciplines and regional boundaries to address some of the biggest health challenges and inequities facing our society today. We will work alongside researchers to drive diversity at all levels—editors, editorial boards, peer reviewers and authors—to broaden the range of perspectives we learn from to advance the health of all humankind. We empower researchers to make work of the highest methodological and ethical rigor openly available to the researchers, policy experts, clinicians and patients who depend on it.
The University of Wisconsin-Eau Claire unveiled a new supercomputer on its campus Monday, funded in part by a new public-private partnership between the college and Hewlett Packard Enterprise.
The company, which has a site in neighboring Chippewa Falls, will put $362,426 toward the supercomputer. Faculty secured a $350,000 grant from the National Science Foundation and the university contributed another $20,000 through its College of Arts and Sciences and Office of Research and Sponsored Programs.
The $733,426 high-performance computer will allow the university to significantly expand research and teaching opportunities to students and faculty involved in computer and data science. But researchers on topics from health care to geography can use the technology in their studies.
Red Hat, Inc., the world’s leading provider of open source solutions, and Boston University (BU), an internationally recognized institution of higher education and research, today announced an expanded collaboration to help fund education and research for open source projects, communities and hybrid cloud operations. To drive these efforts, Red Hat is donating software subscriptions, valued at $551.9 million, to BU while also announcing a renewed and expanded commitment of $20 million to support research and deepen collaboration under the Red Hat Collaboratory at BU.
As hybrid cloud operations at scale become a key focus for organizations across industries, Red Hat is committed to providing resources to help deliver the next generation of innovation.
Oregon State University’s College of Engineering is launching a unique program for graduate study in artificial intelligence, with an initial cohort of about 40 students to be enrolled in fall 2021.
Oregon State’s program will be the first in the United States to offer both master’s and doctoral degrees in artificial intelligence as an interdisciplinary field of study, said Scott Ashford, Kearney Dean of Engineering. A small number of institutions throughout the country have launched undergraduate or master’s programs in AI, and a few offer doctoral programs specializing in machine learning.
“AI is what I like to call the outward-looking face of computer science,” said OSU’s Prasad Tadepalli, the new program’s director and a professor of computer science. “Much of computer science is associated with how to make computers faster, better, cheaper and so on. AI is more focused on how to apply computer science to other fields.”
Government Technology, San Diego Union-Tribune, Gary Robbins
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Apple plans to add nearly 4,000 jobs in greater San Diego through 2026, which could mean more interest in nearby universities that focus on wireless technology, A.I., silicon engineering and cybersecurity.
U.S. Secretary of Transportation Pete Buttigieg on April 21 named Robert Hampshire, PhD, as the chief science officer for the United States Department of Transportation (USDOT). The appointment marks the first time since 1980 that the spot has been filled.
The department has taken several steps to act on President Joe Biden’s and Vice President Kamala Harris’ commitment to address the climate emergency. The department also announced it has begun work to reestablish its Climate Change Center and to restore public access to climate-related reports, program information and other scientific and technical information.
In his role as chief science officer, Hampshire will serve as an advisor to Buttigieg on science and technology issues. He is charged with ensuring that the USDOT’s research, development and technology programs are scientifically and technologically well-founded and conducted with integrity.
In continuation of this conversation, Garrett Morrow, Ph.D. candidate at Northeastern University and MetroLab’s Experiential Research Fellow during Fall 2020, met with members of our Summit panel and others to further dive into how data and algorithm use shapes trust in institutions, the availability of data and connecting with communities to use it, and different government models of public data use.
As the data science field continues to generate more jobs and create new research and economic development opportunities, educators have decided to teach it in high schools. Many of the materials and tools they use, however, are inaccessible and fail to meet the needs of students with disabilities, impeding their access to data science careers.
To help address barriers to entry in data science and similar sectors, Nicholas Giudice of the University of Maine Virtual Environments and Multimodal Interaction Laboratory (VEMI Lab) will help spearhead the creation of educational materials and tools that are more accessible to high school students with visual impairments, learning or other disabilities.
New research from the departments of chemistry and physics at Cambridge University has just helped demonstrate the potential of natural language processing (NLP) for understanding biomolecular condensates. Whether proteins undergo phase separation into membrane-less compartments, and under what conditions, is governed by “surprisingly rigorous grammar,” according to Tuomas Knowles, professor of physical chemistry and biophysics at the university and co-founder of Transition Bio, Inc, a company formed last fall to build better technologies for studying biomolecular condensates.
As described in an article newly published in PNAS, (DOI: 10.1073/pnas.2019053118), the grammar lessons included an “astonishing amount” of physics and chemistry that did not have to be ingested by the NLP algorithm, named DeePhase, he says. Researchers just asked the algorithm to learn the language of proteins and it outperformed several existing machine learning methods for predicting protein liquid–liquid phase separation (LLPS) using publicly available datasets.
MIT researchers have developed a technique to quickly determine certain properties of a material, like stress and strain, based on an image of the material showing its internal structure. The approach could one day eliminate the need for arduous physics-based calculations, instead relying on computer vision and machine learning to generate estimates in real time.
The researchers say the advance could enable faster design prototyping and material inspections. “It’s a brand new approach,” says Zhenze Yang, adding that the algorithm “completes the whole process without any domain knowledge of physics.”
The researchers used x-ray microtomography—a method used in dental research to examine cross-sections of teeth—to analyze the folded layers of paper; the technology also picks up ink on the paper. The team used these x-ray images to create 3D digital reconstructions of the letters, which a computational algorithm then unfolded.
Anytime you start a conversation about diversity in tech, the “pipeline problem” comes up: The pool of qualified workers that tech companies recruit from isn’t diverse enough. Amazon — a company where only 7% of corporate employees are Black — is trying to change that, with a new nine-month Lambda School training program that offers income share agreements for students instead of up-front tuition.
Traditionally, Amazon hasn’t hired software engineers without a computer science degree or a certain amount of work experience. But with the new program, that’s changing. Amazon will essentially treat graduates from the Lambda School course the same as those with a four-year computer science degree, according to Lambda. “This is, in my mind, pretty monumental,” Lambda founder Austen Allred told Protocol. “This is the first time Amazon is saying, explicitly, ‘We are hiring software engineers without a degree.'”
And degrees, Allred thinks, are overrated. “As a society, we’ve over-rotated on the importance of a degree to hiring,” he said. “That has a lot of unforeseen consequences.” One such consequence is tech’s lack of diversity. “If you charge a high-cost tuition,” Allred explained, “you’ve eliminated folks who have demographically come from lower incomes, and folks who are less able to take on more personal risk.” In other words, “you just cut out a whole lot of diversity.”
Disney’s 2019 remake of its 1994 classic “The Lion King” was a box-office success, grossing more than one and a half billion dollars. But it was also, in some ways, a failed experiment. The film’s photo-realistic, computer-generated animals spoke with the rich, complex voices of actors such as Donald Glover and Chiwetel Ejiofor—and many viewers found it hard to reconcile the complex intonations of those voices with the feline gazes on the screen. In giving such persuasively nonhuman animals human personalities and thoughts, the film created a kind of cognitive dissonance. It had been easier to imagine the interiority of the stylized beasts in the original film.
Disney’s filmmakers had stumbled onto an issue that has long fascinated philosophers and zoologists: the gap between animal minds and our own. The dream of bridging that divide, perhaps by speaking with and understanding animals, goes back to antiquity. Solomon was said to have possessed a ring that gave him the power to converse with beasts—a legend that furnished the title of the ethologist Konrad Lorenz’s pioneering book on animal psychology, “King Solomon’s Ring,” from 1949. Many animal lovers look upon the prospect of such communication with hope: they think that, if only we could converse with other creatures, we might be inspired to protect and conserve them properly. But others warn that, whenever we attempt to communicate with animals, we risk projecting our ideas and preconceptions onto them. We might do this simply through the act of translation: any human language constrains the repertoire of things that can be said, or perhaps even thought, for those using it.
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wrote “Cooking up statistics: The science and the art” https://rss.onlinelibrary.wiley.com/doi/10.1111/j.1740-9713.2018.01191.x What will you write about?” Deadline for submissions is May 31.