Representation learning is one of the foundations of Deep Learning and allowed important improvements on several Machine Learning tasks, such as Neural Machine Translation, Question Answering and Speech Recognition. Recent ...

The present article sheds light on new representations of learning. The proposition deals with a representation of learning in four dimensions, in which the highlight is on the navigation across space as a new perspective ...

Based on some constructs of the Activity Theory (Leontiev, 1978), we point to the need to develop activities that reveal the meaning of representations. We examine use of representations in teaching and propose some ...

Despite of the substantial success of Convolutional Neural Networks (CNNs) on many recognition and representation tasks, such models are very reliant on huge amount of data to allow effective training. In order to improve ...

The main objective of this work is aimed to analyze the representations that emerged from the teletandem interactions among foreign language learners, regarding the historical-political aspects of their countries, discussing ...

In Cultural Heritage inquiries, a common requirement is to establish time-based trends between archaeological artifacts belonging to different periods of a given culture, enabling among other things to determine chronological ...

Developing chemistry students' capability to use representations to explain phenomena is a challenging task for educators. To overcome chemistry students' learning difficulties, strategies that favor the development of ...

Affections experienced by students in the school environment influence learning. This study sought to investigate how students perceive the learning environment and what feelings are involved in the relationship with ...