Contrastive terminology: semitic, anglo-germanic and latin concept building through complex terms. (avoiding one-way method procedures in translation

This paper aims to present a contrastive approach between three different ways of building concepts after proving the similar syntactic possibilities that coexist in terms. However, from the semantic point of view we can see that each language family has a different distribution in meaning. But the most important point we try to show is that the differences found in the psychological process when communicating concepts should guide the translator and the terminologist in the target text production and the terminology planning process. Differences between languages in the information transmission process are due to the different roles the different types of knowledge play. We distinguish here the analytic-descriptive knowledge and the analogical knowledge among others. We also state that none of them is the best when determining the correctness of a term, but there has to be adequacy criteria in the selection process. This concept building or term building success is important when looking at the linguistic map of the information society.

Modelling an e-learning environment for learning programming languages

It is widely accepted that solving programming exercises is fundamental to learn how to program. Nevertheless, solving exercises is only effective if students receive an assessment on their work. An exercise solved wrong will consolidate a false belief, and without feedback many students will not be able to overcome their difficulties. However, creating, managing and accessing a large number of exercises, covering all the points in the curricula of a programming course, in classes with large number of students, can be a daunting task without the appropriated tools working in unison. This involves a diversity of tools, from the environments where programs are coded, to automatic program evaluators providing feedback on the attempts of students, passing through the authoring, management and sequencing of programming exercises as learning objects. We believe that the integration of these tools will have a great impact in acquiring programming skills. Our research objective is to manage and coordinate a network of eLearning systems where students can solve computer programming exercises. Networks of this kind include systems such as learning management systems (LMS), evaluation engines (EE), learning objects repositories (LOR) and exercise resolution environments (ERE). Our strategy to achieve the interoperability among these tools is based on a shared definition of programming exercise as a Learning Object (LO).