Answer:
B.F Skinner´s studies led him to the idea that children learn language through operant conditioning. Applying positive reinforcement when a child uses a word correctly helps him to learn the association between that word and its meanings.
Explanation:
Celebrating a child for producing sounds that are close to a word reassures him and makes him repeat it. On the other hand, ignoring sounds that aren´t similar to any words makes the child forget about them. Based on his theory, Skinner developed a teaching process for language development based on the reinforcement of correct use of language. Let's imagine a child that says the word "milk" or a sound similar to that word. If he´s given milk after that and praised about it, he will learn the relationship between the word and its meaning and develop a language based on that information.
Answer:
Im pretty sure the first one but i'm not sure
Explanation:
Confucianism is good and peace and stuff like that
A Temporal Investigation of Crash Severity Factors in Worker-Involved Work Zone Crashes: Random Parameters and Machine Learning Approaches:
Reason:
In the context of work zone safety, worker presence and its impact on crash severity has been less explored. Moreover, there is a lack of research on contributing factors by time-of-day. To accomplish this, first a mixed logit model was used to determine statistically significant crash severity contributing factors and their effects. Significant factors in both models included work-zone-specific characteristics and crash-specific characteristics, where environmental characteristics were only significant in the daytime model. In addition, results from parameter transferability test provided evidence that daytime and nighttime crashes need to be modeled separately. Further, to explore the nonlinear relationship between crash severity levels and time-of-day, as well as compare the effects of variables to that of the logit model and assess prediction performance, a Support Vector Machines (SVM)
What is meant by machine learning approach?
Machine Learning is an AI technique that teaches computers to learn from experience. Machine learning algorithms use computational methods to “learn” information directly from data without relying on a predetermined equation as a model.
Learn more about random parameter approach:
brainly.com/question/13739642
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The answer is symbolic interactionism as this theory
revolves with having to shape the personal identity of an individual with the
use of communication towards self or towards other people. The language plays a
huge role in the person’s being.
