Analyzing the Deep Learning-Based Mobile Environment in Educational Institutions

Abstract

More efficient instructional models that encourage students to engage more actively in their education are essential in today’s world. How information can be found and exchanged, as well as how explanations are delivered, have been shaped by technology. The outcomes demonstrate that mobile learning (m-learning) has enhanced collaboration among instructors and learners, provided immediate feedback, increased student participation and engagement, allowed for authentic learning and evaluation, and supported learning communities in higher education institutions. There was also a change in the teachers’ instructional methods. Students will benefit from simple learning activities, convenient communication, and coaching provided through mobile devices. This study recommends using a learning-based convolutional neural network (CNN) technique to improve students’ English-speaking fluency. In addition, communication between teachers and children in remote areas becomes easier through an interactive system, making both sides more accessible. As a result, it is advisable that educational institutions continually develop innovative teaching techniques that bridge face-to-face and formal-informal learning in the educational setting. The article discusses the background of mobile learning and how it might enhance e-learning as a whole. The m-learning approach is described in this paper as a future version of e-learning. In comparison to the next generation of educational systems, it will be extensively offered and simple to operate for any individual interested in learning. The article also discusses the benefits and potential drawbacks of mobile learning in current educational institutions.