Children learn better when they are more active in lessons and have more control over their learning, says a new study.
Engaging students through interactive activities, discussions, feedback and AI-enhanced technologies resulted in improved academic performance compared to traditional lectures, lessons or readings, faculty from Carnegie Mellon University's Human-Computer Interaction Institute concluded after collecting research into active learning.
There’s something new rumbling and tumbling at CMA! If you’ve visited the museum lately you’ve seen children building towers and other structures out of blocks. That’s pretty common – we’re big block fans! But the friendly animated gorilla sharing challenges and feedback certainly adds a twist. And things get really fun when the foundation below the blocks begins to shake!
A team of Carnegie Mellon University learning scientists are developing a tool that could change the way high school teachers and students approach their computer science classes. This month Schmidt Futures announced that the team is one of the winners of their Futures Forum on Learning: Tools Competition.
Tomohiro Nagashima, HCI Ph.D. student, received the “Nova Southeastern University Award for Outstanding Practice” at the 2020 Association for Educational Communications and Technology (AECT) International Convention this week.
The award recognizes a graduate student who has designed exemplary instructional materials.
A team of Human-Computer Interaction Institute researchers composed of Systems Scientist Nesra Yannier (PI) and Professors Ken Koedinger (Co-PI) and Scott Hudson (Co-PI), has received a $2.3 million, four-year grant from the National Science Foundation (NSF) to further develop their intelligent science exhibits and mixed-reality system, NoRILLA.
How can students learn to make their civil discourse more productive? One Carnegie Mellon University researcher proposes an AI-powered video game. The educational system targeted toward high schoolers adapts to students' specific values and can be used to measure — and in some cases reduce — the impact of bias.
Intelligent tutoring systems have been shown to be effective in helping to teach certain subjects, such as algebra or grammar, but creating these computerized systems is difficult and laborious. Now, researchers at Carnegie Mellon University have shown they can rapidly build them by, in effect, teaching the computer to teach.
Carnegie Mellon University has shaped artificial intelligence (AI) from the field’s very beginning. Today, researchers from all seven colleges across CMU continue to define AI as the next frontier in human progress and are working to help solve problems in areas from healthcare to education.
Carnegie Mellon University learning engineers are heading to rural Panama to help teachers improve student outcomes in science, technology, engineering and math (STEM) courses. Greg Bunyea, a recent graduate of the Masters of Educational Technology and Applied Learning Science program, will lead the work.
