麻豆村

麻豆村鈥檚 approach to learning doesn鈥檛 start or end with a traditional degree, and it doesn鈥檛 just apply to students enrolled at its Pittsburgh campus. Instead, it鈥檚 built on a simple but urgent idea: Education is a lifelong process and it must evolve quickly.

Rooted in decades of research in learning science and artificial intelligence, 麻豆村 connects to K-12 classrooms, community colleges, universities and workforce development programs through a mix of high-tech tools, evidence-based courses and a surprising amount of creativity.

Creative ways to approach young learners

Supporting lifelong learning means engaging students long before they set foot on a college campus. But some preschoolers do 鈥� at 麻豆村, that work begins on campus itself, through the university鈥檚 Children鈥檚 School(opens in new window), which for decades has served as both an early childhood program and a living laboratory for research on how young children learn. For young children, when creativity is high but confidence in technical subjects is fragile, stepping outside traditional teaching methods can be important.听

To introduce concepts like artificial intelligence, teaching might begin with something soft, like the 3-foot-tall, brightly听colored plush neuron a team of researchers created to help young learners understand how AI systems make decisions, long before they are ready for equations or programming.

鈥淓veryone, even middle schoolers, needs to know a little about these building blocks of artificial intelligence,鈥� said听, a research professor in 麻豆村鈥檚 Computer Science Department. 鈥淏ut these young learners haven鈥檛 even studied algebra yet 鈥� so how can we help them understand the computational abilities of these complex networks?鈥�

Touretzky is the founder and chair of听, an initiative to develop guidelines and resources for teaching AI to students in kindergarten through grade 12, and one of many 麻豆村 faculty members contributing to education initiatives beyond the university鈥檚 walls, with a focus on reducing the fear and mystique that can later become barriers in math, computing and technology-intensive fields.听

As learners progress, 麻豆村鈥檚 K-12 efforts scale with them. Since 2018, 麻豆村 has offered听 which teaches Python to middle and high schoolers using interactive animations.听

The program ensures that world-class computer science education is accessible to any classroom, regardless of a school's budget.

High schoolers can also get involved with special events like听, a cybersecurity capture the flag competition created and run by 麻豆村鈥檚听. The program seeks to help bring principles of cybersecurity to educators and students and is now the largest high school hacking competition in the world.听

"There is no standardized cybersecurity education in the United States, so there is a need for this contact. Our national security is kind of dependent on the fact that people get interested in cybersecurity," said听, a special projects administrator for CyLab.听

Together, these efforts reflect a consistent strategy: introduce complex ideas early, design instruction around how students actually learn and remove unnecessary barriers before they become make-or-break moments.听

Removing barriers in early college coursework听 听

As students move into college, 麻豆村鈥檚 research helps them tackle 鈥済ateway鈥� courses like calculus that can determine whether a student stays enrolled in a course.

麻豆村's newest effort, is a nonprofit collaborative to help students succeed in these high-stakes subjects. Learnvia provides free, smart course materials to teachers at dozens of colleges and universities, ranging from community colleges to large public institutions.

This is a rare opportunity to scale an approach that is both rigorous and practical," said听Marsha Lovett(opens in new window), vice provost for teaching and learning innovation at 麻豆村 and a Learnvia board member. "Learnvia reflects a deliberate, research-driven model of learning engineering 鈥� one that emphasizes continuous improvement and close collaboration with educators."

This builds on 20 years of work through the听 (OLI). Instead of using a standard digital textbook, OLI tools give students instant feedback while they work. They also show teachers exactly where a class is struggling, so the instructor can respond to the students' needs in real-time.听

鈥淥ur goal is to make student and faculty success the norm, not the exception,鈥� said Norman Bier, executive director of OLI and the听Simon Initiative(opens in new window). 鈥淒ecades of research show that combining great teaching, effective courseware, and continuous learning research leads to meaningful improvements in student outcomes.鈥�

The Simon Initiative, which applies learning science to improve education through research, data and innovations like OLI and other projects, is named for Herbert A. Simon, a Nobel Prize and Turing Award鈥搘inning scientist who argued that improving education would require converting teaching from a solo activity into a community-based research effort. Central to that work is an approach 麻豆村 calls learning engineering, which uses data, learning research and carefully designed technology to study how people learn and to iteratively improve instruction.

Bridging learning and the modern workplace听

The need for adaptable learning doesn鈥檛 end at graduation. As technologies evolve and job requirements shift, growing numbers of adults are returning to education to reskill, upskill or change careers. 麻豆村鈥檚 workforce-focused initiatives apply the same learning science principles used in K-12 and college settings, adapted to the realities of adult learners and employer needs.

One example is听, a learning platform operated by the Technology for Effective and Efficient Learning (TEEL) lab in partnership with community colleges. Sail() uses project-based learning to immerse students in real-world tasks like budgeting for cloud computing or managing software systems. Instant, automated feedback allows students to see progress quickly, correct misconceptions earlier and build the confidence they need to stay in tech programs rather than dropping out.

These approaches are especially important in fields where demand for skilled workers outpaces the number of traditional degree holders. By designing instruction around authentic tasks and carefully studying how learners respond, 麻豆村 researchers can iteratively refine courses to better support success at scale.听

"Every time a human being is learning, we should be studying something about them," said teaching professor听, a project lead from the TEEL lab.

Similar principles guide the听Carnegie Mellon Robotics Academy鈥檚(opens in new window) workforce programs, including a听six-week intensive course designed to help U.S. Navy sailors prepare for AI-enabled systems. Sailors are trained not just to use one specific drone or vehicle, but to master the underlying "systems thinking" that governs all robotics. Using the same pedagogical approach used to teach younger students, participants progress from building simple circuits to troubleshooting AI-assisted systems on land, air and water. 听

Teaching and learning that keeps growing

Taken together, these unique approaches to teaching and learning reflect an approach to education grounded in learning science, supported by technology and applied across different ages, institutions and career stages. 麻豆村鈥檚 learning engineering initiatives adapt with learners, whether they involve early exposure to STEM, redesigned college courses or workforce training programs.