How NLP Can Benefit in Education

Education Technology Insights | Friday, January 15, 2021

The education sector uses natural language processing (NLP) as it helps the students improve their language skills.

FREMONT, CA: There is already proof that NLP can evaluate and summarize arguments, help writers develop their writing, and encourage writers to rewrite essays. In educational environments, NLP has been successfully used to classify issues in student grammar and mechanics and provide holistic ratings for five-paragraph essays. Although these fields may be significant, NLP can solve more critical problems in the classroom by learners and teachers.

Natural Language Processing for Reading and Writing

NLP innovations can enable students to write better essays by offering formative feedback (i.e., actionable feedback on essay parts) that can strengthen more than just grammar and mechanics during the revising phase.

For example, NLP may help recognize the absence of significant elements of the debate, such as statements, arguments, and proof. NLP may provide students with suggestions about the organization of an essay. It is possible to integrate these NLP solutions into automated writing assessment (AWE) systems that can offer low-level feedback or higher-level feedback.

Ultimately, this formative feedback, coupled with comprehensive feedback, would encourage students several times before final submission to teachers to review essays. Teachers would then obtain better-developed essays, particularly at lower levels of text characteristics, allowing them to concentrate on writing elements that are more difficult to evaluate, like argumentation, style, and organization through computational algorithms.

Natural Language Processing for Learning Behavior and Motivation

In addition to explicitly enhancing students' language skills, NLP features can also be used to help educators better understand what is going on with their students cognitively. NLP can help define and predict learners' mental states during learning by studying language use in the classroom. Studies are still developing in this field and should be improved upon.

But recent research shows that text characteristics can be predictive of performance in math and science in the written and spoken development of students, both in-person and online. Evaluating mental states immediately will provide a more precise understanding for teachers of how well their students are prepared to learn. The knowledge will help teachers manage the classroom better, recognize struggling students at an early stage, and enhance students' learning.

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