Many experts from the learning sciences and educational technologies communities gathered at the University College London (UCL) Institute of Education in London last week for not one but three conferences during the London Festival of Learning.
While much of education research is focused on student performance, this research turns the focus to the development of the teacher.
Design Research Education Learning Sciences and Technologies Faculty
Does a touchscreen display distract visitors from the cultural museum artifacts it supports?
A team of learning scientists and computer scientists collaborated with museum curators to analyze the role of digital display technology in visitor learning in a collections-based exhibit.
Over 3,000 of the world’s top researchers, scientists, and designers are traveling to Montréal this week for CHI 2018, the ACM CHI Conference on Human Factors in Computing Systems. The premier international conference of Human-Computer Interaction will take place from April 21-26, 2018.
Using mixed-reality to reimagine the classroom from both sides -- an Intelligent Science Station for students and smart glasses for teachers -- earned Gold Awards for an HCII PhD student and Postdoc in the 2017-18 Reimagine Education competition.
A new, five-year, $2.5 million research grant from the James S. McDonnell Foundation has been awarded to a team led by Carnegie Mellon University assistant professor Amy Ogan to study teacher learning in high-need settings.
RoboTutor, educational technology developed at Carnegie Mellon University that teaches children basic math and reading skills, has been named a semifinalist in the $15 million Global Learning XPRIZE competition.
Erroneous examples, step-by-step examples of incorrect problem solving, is a pedagogical approach used in only a few fields, such as medical education. Bruce McLaren, an associate research professor in the Human-Computer Interaction Institute, recently received a grant of just under $1 million from the National Science Foundation (NSF) to research why learning from erroneous examples is successful and how it might be integrated into instruction more generally.
