Multimedia Technology Based Interactive Translation Learning for Students

Abstract

Multimedia technology incorporates into the educational arena to translate traditional educational material into interactive digital mode. This has permitted teachers into the learning environment to design and integrate interactive multimedia learning. Many problems towards giving more attention to students facing teacher's multimedia levels are uneven, and their integration significance, bringing enormous curriculum learning strategies, is not entirely apparent. This research introduces multimedia network interpretation teaching using machine learning (MNIT-ML)in multimedia education design to enhance and strengthen the traditional teaching process and promote various modern approaches to transmit knowledge towards students.Allocation of learning resources (ALR) framework is mainly to enlarge the use and utilization of materials for learning activities from impressed resources into recordings, video content, motion graphics, and other forms of resources. The purpose of the Allocation of Learning Resources (ALR) framework is to aid teachers in making sound decisions about how to distribute available educational materials. Its goal is to guide teachers in making smart choices about how to use limited resources like time, money, and technology in order to improve students' educational achievements. The ALR framework was picked because it offers a methodical strategy for selecting choices that is founded in educational research and best practices. Resource allocation is a key aspect in influencing student outcomes, and efficient allocation can help guarantee that all students have access to the tools they need to succeed. There are a number of alternative frameworks that might direct studies on the distribution of educational resources. The Technological Acceptance Model (TAM) is a common tool for analysing what factors lead to widespread implementation of educational technology. The goal of other frameworks like the Universal Design for Learning (UDL) framework is to help educators create lessons and methods that are inclusive of students of all backgrounds and abilities. The final decision on which framework to use will be determined by the nature of the research issues and the setting in which they are being investigated. In order to make educated decisions, it is crucial to pick a framework that is appropriate for the research issues at hand and that gives a systematic approach based on established educational best practices. The digital promoting resources for teaching (DPRT) method creates a real environment for students to learn, focusing on enhancing training to make students feel the standard language translation skills. The simulation analysis is performed based on security 94.6%, the performance of 95.9%, and privacy, proving the proposed framework's reliability overall ratio of 93.4%.