Data mining, according to Wikipedia, ‘is the principle of sorting through large amounts of data and picking out relevant information.’ Until now though data mining has been the playground of business intelligence and financial analysts, and even science is beginning to make use of the ability in extracting information from enormous data sets.
But according to researchers from the Indiana University, young children are using the same technique to develop their language skills.
Data mining is usually computer assisted, and involves analyzing and sorting through large amounts of data to find correlations within. IU cognitive science experts Linda Smith and Chen Yu have recently begun investigating whether this sort of data mining helps toddlers at age 2 and 3, learn one word at a time.
Once a child reaches the age of 2 or 3, they begin to learn words one at a time. This is shown through the importance of a child’s first words. From that point, the child will learn a succession of new words; but normally not more than one at a time.
The research however suggests that children aged around 12 or 14 months accumulate large amounts of data day by day, which then later helps them to so quickly learn one word after the next.
"This new discovery changes completely how we understand children's word learning," Smith said. "It's very exciting."
Together the two published a study in the journal Cognition that saw them attempt to teach 28 12-to 14-month-olds six words. By showing them two objects at a time on a computer monitor, while simultaneously playing two re-recorded words, the children were later surprisingly successful in figuring out which word went with which picture.
A similar version was tested on adults, though the adults were taught 18 words in just six minutes, and instead of viewing just two images at a time, they would be shown anywhere from three to four; they were also played three or four words.
Similarly to the children, the adults learnt more words than is expected simply by chance. Yu and Smith wrote in the journal Psychological Science, "This suggests that cross-situational learning may go forward non-strategically and automatically, steadily building a reliable lexicon."
Thus, the pair believes that the more words toddlers hear growing up, and the more information available to them, the better chances their brains will have of correctly matching word with object. Yu, who thanks to a doctorate in computer science writes much of the software programming necessary for their studies, believes that these breakthrough’s may provide help in learning new languages for children and adults in the future.
Joshua Hill, a Geek’s-Geek from Melbourne, Australia, Josh is an aspiring author with dreams of publishing his epic fantasy, currently in the works, sometime in the next 5 years. A techie, nerd, sci-fi nut and bookworm.
