Personalised trails and learner profiling within e-learning environments

This deliverable focuses on personalisation and personalised trails. We begin by introducing and defining the concepts of personalisation and personalised trails. Personalisation requires that a user profile be stored, and so we assess currently available standard profile schemas and discuss the requirements for a profile to support personalised learning. We then review techniques for providing personalisation and some systems that implement these techniques, and discuss some of the issues around evaluating personalisation systems. We look especially at the use of learning and cognitive styles to support personalised learning, and also consider personalisation in the field of mobile learning, which has a slightly different take on the subject, and in commercially available systems, where personalisation support is found to currently be only at quite a low level. We conclude with a summary of the lessons to be learned from our review of personalisation and personalised trails

Personalised trails and learner profiling in an e-learning environment

This deliverable focuses on personalisation and personalised trails. We begin by introducing and defining the concepts of personalisation and personalised trails. Personalisation requires that a user profile be stored, and so we assess currently available standard profile schemas and discuss the requirements for a profile to support personalised learning. We then review techniques for providing personalisation and some systems that implement these techniques, and discuss some of the issues around evaluating personalisation systems. We look especially at the use of learning and cognitive styles to support personalised learning, and also consider personalisation in the field of mobile learning, which has a slightly different take on the subject, and in commercially available systems, where personalisation support is found to currently be only at quite a low level. We conclude with a summary of the lessons to be learned from our review of personalisation and personalised trails

Revisión sistemática de los métodos de evaluación de experiencia de usuario de sitios web informativos

El presente trabajo de tesis consiste en una revisión sistemática, presentada como artículo científico, sobre los métodos de evaluación que son empleados actualmente para la evaluación de la experiencia de usuario en sitios Web informativos. El trabajo de investigación consiste en una revisión de la literatura para identificar los métodos, criterios y herramientas empleadas para evaluar la experiencia de usuario en sitios web de acuerdo a la definición planteada para ambos términos en la ISO 9241. Las investigaciones consideradas para la revisión fueron encuestas, estudios de casos, estudios comparativos y experimentos que incluyan la descripción de la metodología aplicada. El artículo fue publicado en Springer como parte de la participación en el evento "HCI International 2017", realizado en Vancouver (Canadá) en el 2017.Trabajo de Investigació

Contents

We discuss the current minimisation strategies adopted by research projects involving the determination of parton distribution functions (PDFs) and fragmentation functions (FFs) through the training of neural networks. We present a short overview of a proton PDF determination obtained using the covariance matrix adaptation evolution strategy (CMA-ES) optimisation algorithm. We perform comparisons between the CMA-ES and the standard nodal genetic algorithm (NGA) adopted by the NNPDF collaboration

Architecture handbook

2002 handbook for the Faculty of Architectur

Architecture handbook

2002 handbook for the Faculty of Architectur