Innovation in Deep Learning and Its Application in Education: An Analysis of Literature Research

Abstract

This study analyzes innovation in deep learning and its application in education through a literature review. The main objective of this study is to identify the latest trends in the application of deep learning technology, its impact on learning outcomes and student engagement, and the challenges in its application. The method used was a literature analysis of various previous studies exploring deep learning integration in education. The results showed that deep learning has been used to improve personalized learning through adaptive systems, intelligent tutors based on natural language processing (NLP), and analytical models capable of predicting student performance. These findings also show that this innovation can increase student engagement and learning effectiveness. However, the main challenges in its implementation include limited access to technological devices, lack of educator skills in using this technology, and the need for adequate computing infrastructure. The conclusion of this study emphasizes that although deep learning has great potential to improve education, further efforts are needed in educator training, the development of supportive policies, and the provision of adequate infrastructure. Further research involving primary data is recommended to provide deeper insights into implementing this technology in education.