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      Computer Model Helps Explain How Children Integrate Information for Language Development

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      By the time they turn 2 years old, most kids know approximately 200 to 300 words. By age 12, they know about 50,000. Over that 10-year span, the number of words they learn factors out to nearly 14 per day. That’s an awful lot to process. The question is, how do they do it?

      Kids Use A 'Bag of Tricks' To Build A Massive Vocabulary

      Building a vocabulary from scratch requires children to use multiple sources in their social environment, including the context in which they hear words in addition to their current state of knowledge.

      How they process and integrate that information was a matter addressed by researchers at the Max Planck Institute for Evolutionary Anthropology (MPI), the Massachusetts Institute of Technology (MIT), and Stanford University.

      "We know that children use a lot of different information sources in their social environment, including their own knowledge, to learn new words,” says Manuel Bohn, a researcher at the Max Planck Insitute. “But the picture that emerges from the existing research is that children have a bag of tricks that they can use."

      This “bag of tricks” includes the use of the following mechanisms:

      • Expectations that speakers communicate in a cooperative and informative manner
      • A shared common ground about what is being discussed in conversation
      • Semantic knowledge about previously learned word-object mappings

      To understand how these mechanisms work, consider this scenario:

      ehr emr selection guide by insync healthcare solutionsIf you show a child an object they already know – say a cup – as well as an object they have never seen before – say a frog – the child will usually think that the word they never heard before (frog) belongs with this new object. Why? Because children use information in the form of their existing knowledge of words (the thing you drink out of is called a "cup") to deduce that the object that doesn't have a name goes with the name (frog) that doesn't have an object.

      Think of it as a kind of process of elimination or deductive reasoning.

      Bohn tells us exclusively, "Children generate expectations about what someone will talk about based on the preceding interaction. In our study, children keep track of what the speaker already talked about and what’s 'new' to them, and they assume that the speaker is more likely to talk about something new."

      Model: Intention of The Speaker Is Key to Children's Understanding of Words 

      "In the real world, children learn words in complex social settings in which more than just one type of information is available,” Bohn says. “They have to use their knowledge of words while interacting with a speaker. Word-learning always requires integrating multiple, different information sources."

      This brings us back to the question: How do children integrate information from multiple sources to increase their vocabulary in such a spectacular fashion?

      To find the answer, the researchers followed a three-step process, beginning with:

      • Conducting a series of experiments that measures children's sensitivity to different information sources
      • Formulating a computational cognitive model to detail the manner in which this information is integrated

      How does the model work? The algorithm that processes and integrates the different information sources looks at language-learning as a social inference problem, in which the child tries to find out what the speaker means – what their intention is. The different information sources are all systematically related to this underlying intention, which provides a natural process for integrating them.

      The model also specifies what aspects of the process change as children get older. This is relevant because, throughout their development, children become increasingly sensitive to individual information sources, and yet the social reasoning process that integrates the information sources remains the same.

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      Michael Henry Tessler of MIT’s Department of Brain and Cognitive Services and one of the study’s lead authors, describes the model as “a little computer program.”

      “We input children's sensitivity to different information, which we measure in separate experiments, and then the program simulates what should happen if those information sources are combined in a rational way. The model spits out predictions for what should happen in hypothetical new situations in which these information sources are all available."

      In a final step, the researchers turned these hypothetical situations into real experiments. They collected data with 2- to 5-year-old children to test how well the predictions from the model line up with real-world data. The results were considered a success.

      A Computational Model That Serves as A Base for Future Language Development Research

      "The virtue of computational modeling is that you can articulate a range of alternative hypotheses – alternative models – with different internal wiring to test if other theories would make equally good or better predictions," says Tessler. "In some of these alternatives, we assumed that children ignore some of the information sources. In others, we assumed that the way in which children integrate the different information sources changes with age. None of these alternative models provided a better explanation of children's behavior than the rational integration model." 

      The study offers several results that increase our understanding of how language development works in young children. Beyond that, it opens up a new, interdisciplinary way of doing research.

      "Our goal was to put formal models in a direct dialogue with experimental data. These two approaches have been largely separated in child development research," says Manuel Bohn.

      The next steps in this research program will be to test the robustness of this theoretical model. To do so, the team is currently working on experiments that involve a new set of information sources to be integrated.

      "It is remarkable how well the rational model of information integration predicted children's actual behavior in these new situations,” says Bohn. “It tells us we are on the right track in understanding from a mathematical perspective how children learn language."

      In a Word, InSync Knows About Speech-Language EHR Systems

      At InSync Healthcare Solutions, our experienced staff knows the demands of speech-language pathology when it comes to a fully integrated specialized EHR software. Click below to watch a brief video demonstration of the software designed for rehabilitative professionals.

      click to watch a brief video overview of the InSync Healthcare Solutions EHR system for physical therapists

      For a closer look at how our interoperable, mobile-friendly and configurable software system can grow as your speech-language pathology practice and its workforce grows, schedule a demo now with one of our experts. We're happy to answer questions and explain how we can tailor our system to meet your needs while saving you time and money. 

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