Distributed Readability Analysis Of Turkish Elementary School Textbooks

TL;DR

This paper presents a distributed system using Hadoop to efficiently analyze the readability levels of Turkish elementary school textbooks, demonstrating the system's performance and readability scoring capabilities.

Contribution

It introduces a novel distributed Big Data framework for large-scale readability analysis of textbooks, leveraging MapReduce and Hadoop for efficiency.

Findings

Readability scores for Turkish textbooks are provided.

System demonstrates efficient processing performance.

Framework enables large-scale educational content analysis.

Abstract

The readability assessment deals with estimating the level of difficulty in reading texts.Many readability tests, which do not indicate execution efficiency, have been applied on specific texts to measure the reading grade level in science textbooks. In this paper, we analyze the content covered in elementary school Turkish textbooks by employing a distributed parallel processing framework based on popular MapReduce paradigm. We outline the architecture of a distributed Big Data processing system which uses Hadoop for full-text readability analysis. The readability scores of the textbooks and system performance measurements are also given in the paper.