An Online Big-Data Driven Design of Reading and Writing Test

An Online Big-Data Driven Design of Reading and Writing Test

연구 분야: Software Development

학회: International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness

This paper presents an online big-data driven design of reading and writing tests, incorporating empirical data analysis. The study aims to investigate the nature of reading and writing abilities, their corresponding relationship, and the impact of background variables on learning-oriented test performance. The counterpart was administered through an online platform, where data are collected for assessing the performance of students. The objectives of our work are to provide insights into the test design, delivery, and feedback mechanisms, and to conduct a statistical evaluation of the test’s reliability, validity, and correlations. The findings contribute to our understanding of reading and writing assessment in an online context, while also highlighting the implications of background variables on test performance.