n this chapter, I was fascinated by the principles of automated writing evaluations. In the past, where we only use paper, and the computer penetration on the educational system was very tiny, the idea about automatic writing evaluations was impossible.

Nowadays still tricky to see this kind of education solution is not being used because of the AI penetration in the educational system is very low, and I believe it is due to conservative ideas from the one that formulated the education policies.

https://en.wikipedia.org/wiki/Natural_language_processing

I did some research on this topic and discovered some interesting ideas. Alan Turing published an article titled "Computing Machinery and Intelligence," which proposed what is now called the Turing test as a criterion of intelligence back in the 1950's. He built the first stone of the automated writing evaluations (AWE) by starting this research of machine learning principles.

Reading more about theses ideas on Wikipedia article, I discovered some most commonly researched tasks in natural language processing. The field of applications is unprecedented and can be used to solve a large number of problems.

The most common tasks are:

Syntax
Semantics
Discourse
Speech
Dialogue

For our discussion here about automated writing evaluations, I believe the capacity of process syntax, and semantics are essential features. Bryan Fendley published an article on this Medium blog account about "how natural language processing for educational technology developers." He said, "Educational technology will undoubtedly see out-of-the-box thinking as more applications begin including artificial intelligence."

I sincerely agree with him, and our society needs to embrace AI as part of the educational system. This massive adoption will help our teacher and students get the better educational performance and increase the qualitative education results instead of quantitative results.

And to conclude my point of view, we can have an integrated approach to impact education by using one of its ideas. He said, "Natural language processing can take all kinds of things like social media, emails, and documents as input crunching it down, pulling out the meaning while categorizing and scoring with confidence."

Image source: https://content-static.upwork.com/blog/uploads/sites/3/2017/06/27091727/image-72.png

Source: https://medium.com/@BryanFendley/natural-language-processing-for-educational-technology-developers-6beeb7f9c765 Source: https://en.wikipedia.org/wiki/Natural_language_processing