Symbiotic Security, which is announcing a $3 million seed round today, watches over developers as they code and points out potential security issues in real time. Other companies do this, but Symbiotic also emphasizes the next step: teaching developers to avoid these bugs in the first place. Ideally, this means developers will fix security bugs […]

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On Tuesday, Google's CEO revealed that AI systems now generate more than a quarter of new code for its products, with human programmers overseeing the computer-generated contributions. The statement, made during Google's Q3 2024 earnings call, shows how AI tools are already having a sizable impact on software development.

"We're also using AI internally to improve our coding processes, which is boosting productivity and efficiency," Pichai said during the call. "Today, more than a quarter of all new code at Google is generated by AI, then reviewed and accepted by engineers. This helps our engineers do more and move faster."

Google developers aren't the only programmers using AI to assist with coding tasks. It's difficult to get hard numbers, but according to Stack Overflow's 2024 Developer Survey, over 76 percent of all respondents "are using or are planning to use AI tools in their development process this year," with 62 percent actively using them. A 2023 GitHub survey found that 92 percent of US-based software developers are "already using AI coding tools both in and outside of work."

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The large language model-based coding assistant GitHub Copilot will switch from exclusively using OpenAI's GPT models to a multi-model approach over the coming weeks, GitHub CEO Thomas Dohmke announced in a post on GitHub's blog.

First, Anthropic's Claude 3.5 Sonnet will roll out to Copilot Chat's web and VS Code interfaces over the next few weeks. Google's Gemini 1.5 Pro will come a bit later.

Additionally, GitHub will soon add support for a wider range of OpenAI models, including GPT o1-preview and o1-mini, which are intended to be stronger at advanced reasoning than GPT-4, which Copilot has used until now. Developers will be able to switch between the models (even mid-conversation) to tailor the model to fit their needs—and organizations will be able to choose which models will be usable by team members.

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NextWave STEM is a leader in K-12 STEM education. Using the “five essentials” (leadership, self-development, team development, strategic thinking, civic-mindedness and innovation), the company’s vision is to empower students and educators to excel in a continuously changing world. Since its founding in 2017, NextWave STEM has partnered with more than 500 schools and community organizations nationally, served more than 200,000 students, and created award-winning STEM programs in emerging technologies. Schools and community organizations who have partnered with NextWave STEM report improved student attendance, increased student interest in STEM-related courses and careers, and increased teacher confidence in teaching STEM and emerging technologies.

NextWave STEM is a visionary leader that understands the needs of tomorrow and how to best equip and inspire the leaders of tomorrow with the tools and skills to be successful. By combining the project-based learning of STEM with innovative, emerging technologies, the company works to improve academic outcomes, close the achievement gap, and open new opportunities post high school and throughout one’s career.

The company makes STEM education engaging for students, easy for teachers and affordable for partners. Their solutions include award-winning curricula, hands-on exploration kits, and professional development. Courses cover: robotics and artificial intelligence, drones and coding, 3D printing and modeling, cybersecurity, entrepreneurship, and solar and renewable energy, and more. Courses are designed to help students develop the 21st Century skills needed to master problem solving and critical thinking, and be prepared for the influx of STEM-related careers, while professional development helps teachers master the facilitation of STEM education.

NextWaveSTEM® was born in Chicago as the brainchild of our founder, Udit Agarwal (pictured). While working as an IT analyst for Chicago Public Schools, Udit saw the need for excellent and easy-to-implement STEM education. He knew the importance of the education system and the economy at large to empower students with the 21st-century skills of Science, Technology, Engineering, and Math as well as Critical Thinking, Problem Solving, and Innovation. Nonetheless, he didn’t see it being taught in a way that was fun for kids—while also meeting state and national standards.

As Udit learned more and became more interested in robotics, he started researching how to bring robotics classes to schools. He started putting the pieces together to start NextWaveSTEM. In 2017, Udit launched NextWaveSTEM® by offering after-school programming in Chicago. Today, at NextWaveSTEM, Udit’s company offers in-person and virtual courses for schools and turn-key curricula in Robotics, Drone Coding, Artificial Intelligence, 3D Printing, and more at K-12 schools nationwide.

“For our students, we hope to spark a new way of learning using real-world applications and inquiry-based learning,” says Udit. “For our fellow educators, we offer authentic support from our own educators, curriculum developers, and executive team.”

For these reasons and more, Udit Agarwal of NextWaveSTEM earned an EdTech Leadership Award for his visionary work in our field as part of The EdTech Awards from EdTech Digest. Learn more.

The post NextWaveSTEM appeared first on EdTech Digest.

Marina Umaschi Bers has long been at the forefront of technological innovation for kids. In the 2010s, while teaching at Tufts University, in Massachusetts, she codeveloped the ScratchJr programming language and KIBO robotics kits, both intended for young children in STEM programs. Now head of the DevTech research group at Boston College, she continues to design learning technologies that promote computational thinking and cultivate a culture of engineering in kids.

What was the inspiration behind creating ScratchJr and the KIBO robot kits?

Marina Umaschi Bers: We want little kids—as they learn how to read and write, which are traditional literacies—to learn new literacies, such as how to code. To make that happen, we need to create child-friendly interfaces that are developmentally appropriate for their age, so they learn how to express themselves through computer programming.

How has the process of invention changed since you developed these technologies?

Bers: Now, with the maker culture, it’s a lot cheaper and easier to prototype things. And there’s more understanding that kids can be our partners as researchers and user-testers. They are not passive entities but active in expressing their needs and helping develop inventions that fit their goals.

What should people creating new technologies for kids keep in mind?

Bers: Not all kids are the same. You really need to look at the age of the kids. Try to understand developmentally where these children are in terms of their cognitive, social, emotional development. So when you’re designing, you’re designing not just for a user, but you’re designing for a whole human being.

The other thing is that in order to learn, children need to have fun. But they have fun by really being pushed to explore and create and make new things that are personally meaningful. So you need open-ended environments that allow children to explore and express themselves.

The KIBO kits teach kids robotics coding in a playful and screen-free way. KinderLab Robotics

How can coding and learning about robots bring out the inner inventors in kids?

Bers: I use the words “coding playground.” In a playground, children are inventing games all the time. They are inventing situations, they’re doing pretend play, they’re making things. So if we’re thinking of that as a metaphor when children are coding, it’s a platform for them to create, to make characters, to create stories, to make anything they want. In this idea of the coding playground, creativity is welcome—not just “follow what the teacher says” but let children invent their own projects.

What do you hope for in terms of the next generation of technologies for kids?

Bers: I hope we would see a lot more technologies that are outside. Right now, one of our projects is called Smart Playground [a project that will incorporate motors, sensors, and other devices into playgrounds to bolster computational thinking through play]. Children are able to use their bodies and run around and interact with others. It’s kind of getting away from the one-on-one relationship with the screen. Instead, technology is really going to augment the possibilities of people to interact with other people, and use their whole bodies, much of their brains, and their hands. These technologies will allow children to explore a little bit more of what it means to be human and what’s unique about us.

This article appears in the November 2024 print issue as “The Kids’ Inventor.”

CodeGuppy is a free coding platform for schools, coding clubs, and independent learners. Teachers can use codeguppy.com to teach students the JavaScript language by building video games with sprites and sounds. A ton of example projects are included with the platform. With CodeGuppy, students learn coding by building games and fun applications.

With CodeGuppy you’ll learn to code real games and applications directly in your browser. You don’t need to install any software on your local machine. Any Windows, Mac or Chromebook computer is perfect for CodeGuppy.

At CodeGuppy.com they teach JavaScript – the most used and popular programming language nowadays. Their multi-scene code editor is empowering beginners to type their first line of code as well as advanced users to create multi-scene platform games.

To make coding fun and engaging, CodeGuppy provides you with a full library of animated characters, background images, and sounds that you can use in your games and applications.

Learning to code is easy and fun with the right platform. Teachers, parents, and students can use this platform in the classroom, coding club, or at home. The entire curriculum of lessons and projects is tailor-made for students with activities such as interactive graphics and game creation. Using this platform, students love creating programs and sharing them with their friends.

For these reasons and more, CodeGuppy earned a Cool Tool Award (finalist) for “Best Coding, Computer Science, Engineering Solution” as part of The EdTech Awards 2023. Learn more. 

The post CodeGuppy appeared first on EdTech Digest.

In our goal of trying to estimate a programming language’s popularity, we realized that no one can look over the shoulder of every person writing code, whether that be a child writing a Java script for a personal Minecraft server, a mobile app developer hoping to hit it big, or an aerospace engineer writing mission-critical code for a voyage to Mars. Our Top Programming Languages interactive tries to tackle the problem of estimating a language’s popularity by looking for proxy signals.

We do this by constructing measures of popularity from a variety of data sources that we believe are good proxies for active interest for each programming language. In total, we identify 63 programming languages. We then weight each data source to create an overall index of popularity, excluding some of the lowest scorers. Below, we describe the sources of data we use to get the measures, and the weighting scheme we use to produce the overall indices.

By popularity, we mean we are trying to rank languages that are in active use. We look at three different aspects of popularity: languages in active use among typical IEEE members and working software engineers (the “Spectrum” ranking), languages that are in demand by employers (the “Jobs” ranking), and languages that are in the zeitgeist (the “Trending” ranking).

We gauged the popularity of languages using the following sources for a total of eight metrics (see below). We gathered the information for all metrics in July—August 2024. The data were gathered manually to avoid results being biased due to API changes or terminations and because many of the programming language’s names (C++, Scheme) collided with common terms found in research papers and job ads or were difficult for a search engine to parse. When a large number of search results made it impractical to resolve ambiguities by examining all of the results individually, we used a sample of each data source, and determined the relevant sample size based on estimating the true mean with 95 percent confidence. Not all data sources contain information for each programming language and we interpret this information as the programming language having “no hits” (that is, not being popular).

The results from each metric are normalized to produce a relative popularity score between 0 and 1. Then the individual metrics are multiplied by a weight factor, combined, and the result renormalized to produce an aggregate popularity score.

In aggregating metrics, we hope to compensate for statistical quirks that might distort a language’s popularity score in any particular source of data. Varying the weight factors allows us to create the different results for the Spectrum, Jobs, and Trending rankings. We fully acknowledge that, while these weights are subjective, they are based on our understanding of the sources and our prior coverage of software topics. Varying the weight factors allows us to emphasize different types of popularity and produce the different rankings. We then combined each weighted data source for each program and then renormalized the resulting frequency to produce an aggregate popularity score.

The Top Programming Languages was originally created by data journalist Nick Diakopoulos. Our statistical methodology advisor is Hilary Wething. Research assistance was provided by Elizabeth Wood. Rankings are computed using R.

Google

Google is the leading search engine in the world, making it an ideal fit for estimating language popularity. We measured the number of hits for each language by searching on the template, “X programming language” (with quotation marks) and manually recorded the number of results that were returned by the search. We took the measurement in July 2024. We like this measure because it indicates the volume of online information resources about each programming language.

Stack Overflow

Stack Overflow is a popular site where programmers can ask questions about coding. We recorded the number of questions tagged to each program within the last week prior to our search (August 2024). For the Mathematica/Wolfram language, we relied on the sister “Stack” for the Mathematica platform and tallied the number of programming-related questions asked in the past week. These data were gathered manually. This measure indicates what programming languages are currently trending.

IEEE Xplore Digital Library

IEEE maintains a digital library with millions of conference and journal articles covering a wide array of scientific and engineering disciplines. We searched for articles that mention each of the languages in the template “X programming” for the years 2023 and 2024, because this is the smallest timeframe for which we could access articles. For search results that returned thousands of articles, we identified the correct sample size for a 95 percent confidence interval (usually a little over 300) and pulled that number of articles. For each language we sampled, we identified the share of articles that utilize the programming language and then multiplied the total number of articles by this share to tally the likely total number of articles that reference a given programming language. We conducted this search in July 2024. This metric captures the prevalence of the different programming languages as used and referenced in engineering scholarship.

IEEE Job Site

We measured the demand for different programming languages in job postings on the IEEE Job Site. For search results that returned thousands of listings, we identified the correct sample size for a 95 percent confidence interval (usually around 300 results) and pulled that number of job listings to manually examine. For each language we sampled, we identified the share of listings that utilize the programming language and then multiplied the total number of job listings by this share to tally the likely total number of job listings that reference a given programming language. Additionally, because some of the languages we track could be ambiguous in plain text—such as lD, Go, J, Ada, and R—we searched for job postings with those words in the job description and then manually examined the results, again sampling entries if the number of results was large. The search was conducted in July 2024. We like the IEEE Job Site for its large number of non-U.S. listings, making it an ideal to measure global popularity.

CareerBuilder

We measured the demand for different programming languages on the CareerBuilder job site. We searched for “Developer” jobs offered within the United States, as this is the most popular job title for programmers. We sampled 400 job ads and manually examined them to identify which languages employers mentioned in the postings. The search was conducted in July 2024. We like the career builder site to identify the popularity of programmer jobs in the United States.

GitHub

GitHub is a public repository for many volunteer-driven open-source software projects. We used data gathered by GitHut 2.0, which measures the top 50 languages used by the number of repositories tagged with that language and draws from GitHub’s public API. We use two metrics from GitHub: repositories that have been “starred” by users to reflect long-term interests, and the number of pull requests to indicate current activity. The data cover the second quarter of 2024. These measures indicate what languages coders choose to work in when they have a personal choice.

Trinity College Dublin Library

The library of Trinity College Dublin is one of six legal deposit libraries in Ireland and the United Kingdom. A copy must be deposited with the library of any book published or distributed in Ireland, and on request any U.K. publisher or distributor must also deposit a book. We searched for all books published in the year to date that had their subject matter categorized as computer programming and totaled the number of returns. The search was conducted in June 2024. We like this library collection because it represents a large and categorized sample of works, primarily in the English language.

Discord

Discord is popular chat-room platform where many programmers exchange information. We counted the number of tags that correspond to each language. In the case of languages that could also be names of nonprogramming topics, (many nonprogramming-related topics also have dedicated Discord servers; for example, “Julia” could refer to the programming language or the Sesame Street puppet), results were manually examined. Disboard was searched in August 2024. Disboard lists many public discord servers and many young coders use the site, contributing a different demographic of coders.

What works best in early childhood—hands-on experience with physical manipulatives and playful opportunities for self-directed knowledge construction—also works best for teaching AI. KIBO provides a research-proven method to explore computer science, engineering, and now AI concepts in early childhood STEM education. With KIBO, advanced and abstract concept like AI become accessible to young kids.

This new (and free!) AI curriculum, Thinking with KIBO: Introducing Artificial Intelligence (AI) in Early Grades, is designed to help students in grades 1–3 understand how artificial intelligence works, what its limitations are and how to think critically about how these tools can improve lives in their communities.

Featuring five lessons, students explore fundamental ideas about AI through activities with the hands-on and screen-free KIBO robot. Thinking with KIBO engages with computer science concepts in K–5, alongside evolving content standards in artificial intelligence. The curriculum is ideal for a 5–6 week unit in computer science or technology/media classes, as well as afterschool programs, enrichment centers, libraries, makerspaces, and more.

The curriculum’s core learning objectives include:

• AI is a tool made by people.
• AI systems (and robots!) make decisions based on input and rules.
• AI doesn’t think like people do, and it’s not alive.
• AI can help people solve difficult problems.

Based on 20+ years of early child development research by co-founder, Dr. Marina Bers, KIBO engages young students to learn STEAM concepts through play and creative self-expression. KIBO provides developmentally appropriate robotics and coding to young learners: teaching computer science, engineering, and computational thinking.

For these reasons and more, KIBO Robots is a Cool Tool Award Winner for “Best Robotics (for Learning, Education) Solution” as part of The EdTech Awards 2024 from EdTech Digest. Learn more. 

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