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The International Workshop on Rethinking Children’s Automatic Speech Recognition for Education—held on September 10 at the University at Buffalo—brought together more than 50 researchers, practitioners, funders, developers, and educators to foster real conversations about moving the field forward, says Jing Liu, an associate professor of education policy at the University of Maryland.
“The data problem is real and urgent,” says Liu, who directs the Center for Educational Data Science and Innovation at UMD. “We're facing a massive shortage of children's speech datasets, which creates barriers for developing accurate, fair ASR systems.
Meanwhile, Liu adds, the potential applications in EdTech and educational assessment are mind-blowing—including uses like real-time reading support, authentic language assessment, and truly adaptive learning platforms.
INSIDE THE MIDDLE SCHOOL classroom, a video camera swivels on its tripod while five microphones capture clues to the age-old question: How do you teach math to kids?
Recordings from this lesson and thousands like it across the country will be fed into an artificial intelligence (AI) program trained to spot instances of student engagement and the teaching practices that elicit it: Maybe a pupil explains her reasoning—“it can’t be divided because it’s a prime number!”—or raises her hand several times.
It’s the first half of a project, funded by a $4.5 million grant from the Gates Foundation/Walton Family Foundation and led by UMD’s Center for Educational Data Science and Innovation (EDSI) to create a massive database arming scholars and ed-tech companies with real-world classroom data to mine for best practices.
Elementary and middle-school math scores have tumbled from pre-COVID levels, widening the gap between high and low achievers as other countries leapfrog the United States in international rankings.
Accelerate today announced awardees for two complementary grant programs, the Call for Effective Technology (CET) and Evidence for Impact (EFI). Together, these investments build stronger evidence on tutoring and classroom technology while helping states and districts put proven strategies into practice.
High-dosage tutoring and effective ed tech are among the most promising strategies for accelerating student learning, but they only deliver results when implemented well. Too often, schools struggle with time, staffing, and integration into the school day. Accelerate helps states and districts overcome those barriers by pairing grantees with independent researchers, clear standards, and a national lens to understand what works. These grants reflect that mission: giving leaders the tools and evidence they need to scale proven solutions, particularly in historically underserved communities.
| Fortune
Want to up your chances of securing a higher salary straight out of college? The secret might be hidden in your high school schedule.
A new study found that among high school students who take a computer science class, their earnings will be 8% greater on average by the time they’ve secured their first job.
For low-income, Black, and female students, their salaries could see a 14% raise.
Moreover, these benefits are in reach no matter one’s career path, according to the researchers from the University of Maryland.
| Axios
Students who attend high schools that offer a computer science course end up earning 8% higher salaries than those who don't, regardless of career path or whether they attend college, according to a report by the Brookings Institution. (The study examined the impact of giving students access to computer science classes, not of requiring them.)A University of Maryland-led team has received a $4.5 million grant from the Gates Foundation/Walton Family Foundation to improve artificial intelligence (AI) as a tool to strengthen math instruction and boost learning.
The researchers will develop a large-scale, open-source dataset for AI model training tools focused on K–12 math education, sourced over the next three years from classroom recordings of 300 instructors around the country who teach fourth to eighth graders.
Jing Liu, an assistant professor of education policy in UMD’s College of Education who is the lead principal investigator on the project, said the team aims to cover school districts from many different localities and that serve students from different socioeconomic backgrounds.
Discover how advancements in automated feedback can improve the scalability, efficiency, and impact of instructional coaching—and how your district can get involved.
In this webinar, we discuss:
- Preview the M-Powering Teachers platform, an app that uses machine learning to provide automated feedback on HQIM-aligned instructional practices
- Explore a coaching model that leverages the M-Powering Teachers automated feedback
- Learn the keys to successful roll-out from district leaders who have piloted the program
- Discuss the potential impact of incorporating automated feedback into instructional coaching and teacher self-reflection
As the U.S. economy becomes more digitalized, employment in computer and information technology occupations is projected to grow by 10% in the next decade. In response to this increasing demand for technology skills, many states are working to expand computer science (CS) learning opportunities across K-12 classrooms. Thirty states have adopted a key part of Code.org Advocacy Coalition’s policy recommendations, which require all high schools to offer CS coursework, while eight states (and counting) have gone a step further in requiring all students to take CS as a high school graduation requirement. Despite heightened policy interest in CS access, however, research is surprisingly sparse on how the expansion of CS coursework affects postsecondary and labor market outcomes.
In a recent working paper, we aim to fill this research gap by investigating the impact of the expansion of high school CS course offerings. The State of Maryland, which is the context of our study, has rapidly expanded CS course offerings over the last decade. A 2018 law further requires all Maryland high schools to offer at least one “high-quality” CS course aligned with rigorous K-12 CS standards. These “high-quality” courses include foundational courses such as Computer Science Essentials, AP courses such as AP Computer Science Principles, and more specialized programming courses. They are also closely aligned with Code.org’s definition of “foundational” CS courses.
The sound of his teacher smacking his desk jolted Marquan into consciousness, and his head jerked up. “Wake up,” his teacher said.
Marquan hadn’t slept much the night before, and the words came out before he was fully coherent. “Watch out before you make me mad,” he said.
His teacher turned and asked if that was a threat. The 16-year-old said no, he was just startled, but it was too late – he was sent out of the classroom and given a two-day suspension.
| EdSurge
In recent years high schools across the country have been adding computer science courses, and there is a movement to make them ubiquitous. A new study of an unusually rich dataset in Maryland found that such efforts can have a significant impact when it comes to getting more students to go on to careers in coding, and in bringing more diversity to the field.
The study, published as a working paper this month, found that taking a high-quality computer science course in high school increased the chance that the student goes on to major in computer science in college by 10 percentage points, and increased the chance that the student would finish a CS degree program by 5 percentage points.
“It’s not surprising in some ways,” says the lead researcher on the study, Jing Liu. “But we need the numbers so we can show it concretely.”