Desarrollo de un prototipo que emplee la plataforma lenguaje natural de google cloud

El lenguaje natural en la actualidad se ha convertido una herramienta importante, donde nacen diversas aplicaciones las cuales cuyo objetivo es automatizar de cierta manera un proceso, convirtiéndose una herramienta esencial para el desarrollo de este prototipo. Debido a que Google Cloud una plataforma robusta la cual permite el desarrollo de dos prototipos por medio de lenguaje natural como herramienta para el desarrollo de análisis de opiniones y clasificación de textos ya sean por medio de librerías clientes, así como un modelo personalizado, el cual se puede uno crear acorde a la necesidad que se requiere clasificar. Un análisis de opiniones dentro de la red social Twitter toma un rol importante para medir el nivel de impacto que está teniendo cierto hashtag y además la clasificación de textos para “Grounded Theory in Software Development” lo cual permitimos una clasificación automática basada en el modelo que sea necesario. Finalmente, como resultados se quiere ver que tan eficaz es el proceso de análisis para los dos casos anteriormente descritos.Natural language today has become an important tool, since several applications are born there, whose objective is to automate a process in a certain way, becoming an essential tool for the development of this prototype. Because Google Cloud is a robust platform which allows the development of two prototypes through natural language as a tool for the development of opinion analysis and text classification either through client libraries, as well as a personalized model, which one can create according to the need to classify. An analysis of opinions within the social network Twitter takes an important role to measure the level of impact that a certain hashtag is having and also the classification of texts for “Grounded Theory in Software Development” which allows an automatic classification based on the model that be necessary. Finally, as results we want to see how effective the analysis process is for the two cases described above

Challenges Encountered in Creating Personalised Learning Activities to Suit Students Learning Preferences

This book chapter reviews some of the challenges encountered by educators in creating personalised e-learning activities to suit students learning preferences. Technology-enhanced learning (TEL) alternatively known as e-learning has not yet reached its full potential in higher education. There are still many potential uses as yet undiscovered and other discovered uses which are not yet realisable by many educators. TEL is still predominantly used for e-dissemination and e-administration. This chapter reviews the potential use of TEL to provide personalised learning activities to suit individual students learning preferences. In particular the challenges encountered by educators when trying to implement personalised learning activities based on individual students learning preferences

A Review of Personalised E-Learning: Towards Supporting Learner Diversity

The realisation of personalised e-learning to suit an individual learner’s diverse learning needs is a concept which has been explored for decades, at great expense, but is still not achievable by non-technical authors. This research reviews the area of personalised e-learning and notes some of the technological challenges which developers may encounter in creating authoring tools for personalised e-learning and some of the pedagogical challenges which authors may encounter when creating personalised e-learning activities to enhance the learning experience of their students. At present educators who wish to create personalised e-learning activities require the assistance of technical experts who are knowledgeable in the area. Even with the help of an expert the creation of personalised e-learning activities still remains a complex process to authors who are new to the concept of tailoring e-learning to suit learner diversity. Before the successful utilisation of adaptive authoring tools can be realised, academic authors need to learn how to effectively use these tools. All learners come to education with a diverse set of characteristics; educators need to decide which learner characteristic(s) they wish to focus on addressing through the use of personalised e-learning activities. Further investigation, evaluation and analyses of authoring tools is required before personalised e-learning to support learner diversity can be achieved by many academics. Research members of the AMAS (2013) project team are currently involved in developing an authoring tool for adaptive activities for e-learning