National Taiwan Normal University researchers have developed a text readability assessment system that rates the reading difficulty of a book and locates books that suit students’ reading levels and interests, and some schools in Taiwan, Hong Kong and Indonesia have already adopted the system.
Educational psychology professor Sung Yao-ting (宋曜廷) said his team combined theories of psychology and linguistics with cognition technology, such as natural language processing and machine learning algorithms, to develop a Chinese-language readability system, which can decode the semantic content of various texts and rate the difficulty of a book.
“If a book is too difficult for children, they might lose interest in reading. On the other hand, if children can read a book without their parents’ help, it might boost their confidence and motivation,” Sung said.
The system has analyzed 5,611 textbook articles on various subjects and incorporates corpus data to establish a knowledge base of each grade for elementary and secondary school. Parents and teachers can use the system to predict if a book is suitable for students of a certain level, Sung said, adding that the system has an 82.07 percent accuracy rate.
An analysis of popular science magazines and children’s books suggests that most publications are too difficult for children, and there is a tendency among publishers to overate children’s reading ability, he said.
“Traditionally, publishers rely on experience to set the age rating for a book, but they do not have a consistent method to analyze the textual structure of a book to predict whether a book might overwhelm the reader. Our system offers a solution,” he said.
The system could also assess the Chinese competence of students in terms of vocabulary, semantic and lexical comprehension, summarizing, inference ability and critical analysis by subjecting them to a computerized test, while results could be compared with their peers to understand each student’s strengths and weaknesses to design a personalized reading list.
The system could also predict what books a student might like and arrange a reading schedule to encourage further reading, Sung said.
More than 10,000 elementary and secondary-school students from Taiwan, Hong Kong, China and Indonesia began using the system in November last year, and teachers were given data to reorient their teaching and textbook selection, he said.
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