Learner-centred, self-regulated learning approaches such as flipped classrooms or personalised learning environments are popular. This paper analyses personalised learning in collaborative, self-regulated e-learning approaches applying the theory of cognitive fit to explain the personalisation of learning tasks and learning tools. The personalised learning framework (PLF) is presented defining ...

OBJECTIVE Relation extraction in biomedical text mining systems has largely focused on identifying clause-level relations, but increasing sophistication demands the recognition of relations at discourse level. A first step in identifying discourse relations involves the detection of discourse connectives: words or phrases used in text to express discourse relations. In this study supervised mac...

Learning to predict future events from sequences of past events is an important, real-world, problem that arises in many contexts. This paper describes Timeweaver, a genetic-based machine learning system that solves the event prediction problem by identifying predictive temporal and sequential patterns within data. Timeweaver is applied to the task of learning to predict telecommunication equip...

Introduction: One of the most important problems in student's education is academic failure. Identifying factors that affecting academic achievement and pay attention to these factors is a stride toward success. Students' academic achievement and related factors have priority in education research. This study aimed to determine the relationship between learning study strategies and academic a...

We use machine-learning methods on local structure to identify flow defects-or particles susceptible to rearrangement-in jammed and glassy systems. We apply this method successfully to two very different systems: a two-dimensional experimental realization of a granular pillar under compression and a Lennard-Jones glass in both two and three dimensions above and below its glass transition temper...

In this paper we perform a comparative evaluation of machine learning methods on the task of identifying the correct sense of a word, based on the context in which it appears. This task is known as word sense disambiguation (WSD) and is one of the hardest and most interesting issues in language engineering. Research on the use of machine learning techniques for WSD has so far focused almost exc...