New Thoughts On Language Acquisition: Toddlers As Data Miners

Their theory, which they have explored with 12- and 14-month-olds, takes a radically different approach to the accepted view that young children learn words one at a time -- something they do remarkably well by the age of 2 but not so well before that.

Data mining, usually computer-assisted, involves analyzing and sorting through massive amounts of raw data to find relationships, correlations and ultimately useful information. It often is used and thought of in a business context or used by financial analysts, and more recently, a wide range of research fields, such as biology and chemistry. IU cognitive science experts Linda Smith and Chen Yu are investigating whether the human brain accumulates large amounts of data minute by minute, day by day, and handles this data processing automatically. They are studying whether this phenomenon contributes to a "system" approach to language learning that helps explain the ease by which 2- and 3-year-olds can learn one word at a time.

"This new discovery changes completely how we understand children's word learning," Smith said. "It's very exciting."

Smith, chair of the Department of Psychological and Brain Sciences at IU Bloomington, and Yu, assistant professor in the department, recently received a $1 million grant from the National Institutes of Health to fund this research for five years. Here are some recent findings:

*In one of their studies, published in the journal Cognition, Yu and Smith attempted to teach 28 12- to 14-month-olds six words by showing them two objects at a time on a computer monitor while two pre-recorded words were read to them. No information was given regarding which word went with which image. After viewing various combinations of words and images, however, the children were surprisingly successful at figuring out which word went with which picture.

*In the adult version of the study, which used the same eye-tracking technology used in the Cognition study, adults were taught 18 words in just six minutes. Instead of viewing two images at a time, they simultaneously were shown anywhere from three to four, while hearing the same number of words. The adults, like the children, learned significantly more than would be expected by chance. Many of the adult subjects indicated they were certain they had learned nothing and were "amazed" by their success. 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."

Yu and Smith say it's possible that the more words tots hear, and the more information available for any individual word, the better their brains can begin simultaneously ruling out and putting together word-object pairings, thus learning what's what.

Yu, who has a doctorate in computer science and writes much of the software programming for their studies, said that if they can identify key factors involved in this form of learning and how it can be manipulated, they might be able to make learning languages easier, through training DVDs and other means, for children and adults. The learning mechanisms used by the children to learn words also could be used to further machine learning.