Artificial intelligence could one day be used to teach students how to improve their language skills, according to a new study.
The National Science Foundation’s Artificial Intelligence Research Center at Stanford University found that it could be used as a learning aid for those struggling with their vocabulary and comprehension.
The researchers, from the Center for Information and Learning and the University of Washington, found that when students use a computer-generated language, it can sometimes improve comprehension and comprehension in the classroom, but not in real life.
That’s because the computer model that the computer uses to train the model, called a reinforcement learning algorithm, is able to recognize and mimic language, even when it doesn’t fully understand what is being spoken.
“We’ve all had the experience of the classroom having a computer program try to understand the words and phrases that students are using and respond appropriately,” said researcher Andrew Kaczynski.
“It’s often a frustrating experience because it’s not clear what the program is learning and why it is trying to understand something.
We want to build a model that can do that.
That’s what we’ve been doing.”
The Stanford study was based on data from over 500 students across five countries, including the United States, China, India, Russia and the United Kingdom.
The students were asked to read a list of vocabulary words from a dictionary.
They were then asked to write an answer to each of the words.
The computer was given the word “go” and asked to find the word in the dictionary that had the most number of correct answers.
It then looked up the most common word in each answer and looked for the most correct word in a separate section of the dictionary.
The program then repeated the process, asking students to try to remember the correct answer.
It turned out that the model that was trained on the students’ answers did better at recognizing and mimicking words than the real word.
In the words of Kacowski:The models were able to learn to associate the words that students were saying with different meanings.
The students who had been trained in the real world also tended to get better scores in some areas of vocabulary and grammar compared to the students who were not.
The researchers believe that the way the program learns to identify and mimic words is very similar to what students in real classrooms are doing in real-life.
“Our research suggests that using a machine learning model that has the ability to learn from real-world input could be helpful in improving students’ language comprehension and language learning skills,” Kacovsky said.
Kaczynski’s team has been working on developing a machine-learning model to help students in other areas of learning.
The Stanford team’s model, known as an open-source learning model, can be used by students from across the globe.
“The idea of using AI to improve language skills is pretty much a new frontier,” said Kacynski.
“We’re really excited to be part of this revolution and it’s an exciting time to be working on this.”