Considering the feedback given by students, they do engage in this kind of activity, are aware of the learning gains and do feel it was a fruitful learning experience. Our goal was to understand: a) if students are motivated to this kind of learning experience b) if students are aware of the possible learning gains when participating in these activities c) if students do, effectively, feel that they have learned something d) which are the achievements of this kind of activities (perceived by the teachers). Also, tips for teachers willing to build similar Educational Escape Games are suggested. The procedure followed to create the games is presented and both activities are described and evaluated. This paper describes the implementation of two Escape Games aimed at Computer Science undergraduate students, at Instituto Superior Técnico, University of Lisbon. more Educational Escape Games are active learning strategies, as students solve problems related with the curriculum content to “escape” from the physical place where they are “locked”.

Moreover, since we not know in advance.Įducational Escape Games are active learning strategies, as students solve problems related with. To tackle the challenge of deciding whether each incoming pair source-translations is worthy to query for human feedback, we resort to a number of stream-based active learning query strategies. In this paper, we assume a real world human-in-the-loop scenario in which: (i) the source sentences may not be readily available, but instead arrive in a stream (ii) the automatic translations receive feedback in the form of a rating, instead of a correct/edited translation, since the human-in-the-loop might be a user looking for a translation, but not be able to provide one. Most active learning approaches for Machine Translation assume the existence of a pool of sentences in a source language, and rely on human annotators to provide translations or postedits, which can still be costly. more Active learning can play an important role in low-resource settings (i.e., where annotated data is scarce), by selecting which instances may be more worthy to annotate. N.Īctive learning can play an important role in low-resource settings (i.e., where annotated data i. To the best of our knowledge, no recent work that considers the recent available tools, was carried out for the Portuguese language.Têm sido desenvolvidas várias ferramentas para o processamento da língua portuguesa. We also present a qualitative analysis of two dependency parsers. All the resources used in this evaluation (mapping tables between labels, testing corpora, etc.) will be made available, allowing to replicate/fine-tune the results here presented. We evaluate twelve different models for the first task and eight for the second. In this work, we propose an evaluation of tools, publicly available and free, that perform the tasks of Part-of-Speech Tagging and Named Entity Recognition, for the Portuguese language. However, and due to different choices at the basis of these tools' behaviour (different preprocessing, different labels, etc.), it becomes difficult to have an idea of each one's comparative performance. more There are several tools for the Portuguese language. However, and due to different choices at the. There are several tools for the Portuguese language.

Pagico review 2015