Going to classroom to learn student response for curriculum implementation can soon become things of the past as a US researcher has figured out an easier way - and it could include playing video games.
With an artificial neural network which is basically artificial intelligence that simulates the human brain, the researchers developed what they call the Student Task and Cognition Model to know student response.
"Traditionally, we'd be confined to a classroom to study student learning for virtually every potential theory we have about science education and curriculum implementation,” said Richard Lamb, a professor at Washington State University.
“But now, instead of taking a shotgun approach, we can test the initial interventions on a computer and see which ones make the most sense to then study in the classroom,” Lamb added.
For the study, students were given tasks to complete in an electronic game. The tasks were scientific in nature and required students to make a choice.
The researchers used statistical techniques to track everything and assign each task as a success or failure.
“The computer is able to see what constitutes success, but it is also able to see how students approach science,” Lamb said.
Because the computer is learning an approach to science, rather than just how to do a specific task, it will later try to solve a different problem the same way a student might.
“The computer is learning to solve novel or new problems, which means we can test different educational interventions before ever getting to a classroom,” Lamb noted.
The study appeared in the journal Computers and Education.