Impact of Read Theory in Mobile-Assisted Language Learning on Engineering Freshmen's Reading Comprehension Using BI-LSTM

The effect of Read Theory in Mobile-Assisted Language Learning (MALL) on reading comprehension is critical, especially for engineering freshmen who require excellent language abilities to navigate their complicated academic courses. Read Theory is a customized reading platform that offers adaptive reading activities based on the user's ability level, which is especially useful in MALL settings where accessibility and flexibility are essential. However, traditional methods of MALL have frequently faced with constraints, such as the inability to completely adapt to students' different and dynamic learning demands. This deficiency usually results in poor improvement in reading skills because the conventional paradigms do not capture the intricate and diverse learning processes that are necessary for the effective learning of languages. To fix these issues, a Deep Learning approach that involves the implementation of BI-LSTM networks for enhancing the completion’s reading outcomes is offered. BI-LSTM is more suitable for this task because it has forward and backward reading capabilities to better understand and predict the dynamics of language acquisition. The research established improvement and an astonishing accuracy of 99.3%. The implementation was done using Python. This high value of accuracy disproves the common weakness of the strategy and provides convincing evidence that the proposed approach can significantly enhance MALL projects’ outcomes. The specified technique, which improves on the flaws of previous approaches, does not only improve the process of reading but has the potential to revolutionize language acquisition for engineering students, making it more effective and conforming to ability.

@article{Pearlin2024,
  title     = {Impact of Read Theory in Mobile-Assisted Language Learning on Engineering Freshmen's Reading Comprehension Using BI-LSTM},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {9},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {E. Pearlin and S. Mercy Gnana Gandhi},
  doi       = {10.14569/IJACSA.2024.0150969},
  url       = {https://doi.org/10.14569/IJACSA.2024.0150969}
}