Implementing M-Learning System for Learning Mathematics Through Computer Games and Applying Neural Networks for Content Similarity Analysis of an Integrated Social Network

Abstract

In order to make e-learning systems more readily available for use, the majority of new systems are being developed in a form suitable for mobile learning, i.e. m-learning. The paper puts focus on the parts of the implementation of an e-learning system which is not restricted to desktop platforms, but works equally well on smartphones and tablets in the form of m-learning. The implemented system uses educational computer games for learning Mathematics in primary schools and has an integrated social network, which is used for communication and publishing of the content related to the game. Besides analysing the platforms used for accessing the system (desktop/mobile), since students are given a choice, the paper also questions how to interpret messages when they contain concepts in student jargon or generally unknown to teachers, and shows that these messages can be interpreted by applying neural networks.

Word Embedding for High Performance Cross-Language Plagiarism Detection Techniques

“…Word2Vec: is a word embedding technique proposed by Thomas Mikolov [40], [41] that represents each word in a vector space. The semantic similarity between the words is calculated using the vectors.…”