Abstract
This paper presents Enki, a web-based IDE that integrates several pedagogical tools designed to engage students in learning programming languages. Enki achieves this goal (1) by sequencing educational resources, either expository or evaluative, (2) by using gamification services to entice students to solve activities, (3) by promoting social interaction and (4) by helping students with activities, providing feedback on submitted solutions. The paper describes Enki, its concept and architecture, details its design and implementation, and covers also its validation.

Abstract
The corner stone of a language development environment is an editor. For programming languages, several code editors are readily available to be integrated in Web applications. However, only few editors exist for diagrammatic languages. Eshu is an extensible diagram editor, embeddable in Web applications that require diagram interaction, such as modeling tools or e-learning environments. Eshu is a JavaScript library with an API that supports its integration with other components, including importing/exporting diagrams in JSON. Eshu was already integrated in a pedagogical environment with automated diagram assessment, configured for extended entityrelationship diagrams, that served as basis for an usability evaluation. © José Paulo Leal, Helder Correia, and José Carlos Paiva;licensed under Creative Commons License CC-BY.

Abstract
Existing gamification services have features that preclude their use by e-learning tools. Odin is a gamification service that mimics the API of state-of-theart services without these limitations. This paper presents Odin as a gamification service for learning activities, describes its role in an e-learning system architecture requiring gamification, and details its implementation. The validation of Odin involved the creation of a small e-learning game, integrated in a Learning Management System (LMS) using the Learning Tools Interoperability (LTI) specification. Odin was also integrated in an e-learning tool that provides formative assessment in online and hybrid courses in an adaptive and engaging way.

Abstract
Currently, a learning management system (LMS) plays a central role in any e-learning environment. These environments include systems to handle the pedagogic aspects of the teaching-learning process (e.g. specialized tutors, simulation games) and the academic aspects (e.g. academic management systems). Thus, the potential for interoperability is an important, although over looked, aspect of an LMS. In this paper, we make a comparative study of the interoperability level of the most relevant LMS. We start by defining an application and a specification model. For the application model, we create a basic application that acts as a tool provider for LMS integration. The specification model acts as the API that the LMS should implement to communicate with the tool provider. Based on researches, we select the Learning Tools Interoperability (LTI) from IMS. Finally, we compare the LMS interoperability level defined as the effort made to integrate the application on the study LMS.

Abstract
This paper presents an overview and main features of Enki, a web-based learning environment for computer science languages. Enki was designed to be a sort of entry level IDE, aggregating tools for navigating and viewing course materials, for solving exercises and receiving automated feedback, as well as promoting the learning process. Enki uses services from several other systems, namely for content sequencing and recommendation, exercise assessment, and gamification.

Abstract
There are two main types of semantic measures (SM): similarity and relatedness. There are also two main types of datasets, those intended for similarity evaluations and those intended for relatedness. Although they are clearly distinct, they are similar enough to generate some misconceptions. Is there a confusion between similarity and relatedness among the semantic measure community, both the designers of SMs and the creators of benchmarks? This is the question that the research presented in this paper tries to answer. Authors performed a survey of both the SMs and datasets and executed a cross evaluation of those measures and datasets. The results show different consistency of measures with datasets of the same type. This research enabled us to conclude not only that there is indeed some confusion but also to pinpoint the SMs and benchmarks less consistent with their intended type.