Abstract
Evaluating scientists based on their scientific production is often a controversial topic. Nevertheless, bibliometrics and algorithmic approaches can assist traditional peer review in numerous tasks, such as attributing research grants, deciding scientific committees, or choosing faculty promotions. Traditional bibliometrics focus on individual measures, disregarding the whole data (i.e., the whole network). Here we put forward OTARIOS, a graph-ranking method which combines multiple publication/citation criteria to rank authors. OTARIOS divides the original network in two subnetworks, insiders and outsiders, which is an adequate representation of citation networks with missing information. We evaluate OTARIOS on a set of five real networks, each with publications in distinct areas of Computer Science. When matching a metric’s produced ranking with best papers awards received, we observe that OTARIOS is >20 more accurate than traditional bibliometrics. We obtain the best results when OTARIOS considers (i) the author’s publication volume and publication recency, (ii) how recently his work is being cited by outsiders, and (iii) how recently his work is being cited by insiders and how individual he his. © 2019, Springer Nature Switzerland AG.

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Abstract

Abstract
The analysis of sentiments, emotions, and opinions in texts is increasingly important in the current digital world. The existing lexicons with emotional annotations for the Portuguese language are oriented to polarities, classifying words as positive, negative, or neutral. To identify the emotional load intended by the author, it is necessary to also categorize the emotions expressed by individual words. EmoSpell is an extension of a morphological analyzer with semantic annotations of the emotional value of words. It uses Jspell as the morphological analyzer and a new dictionary with emotional annotations. This dictionary incorporates the lexical base EMOTAIX. PT, which classifies words based on three different levels of emotions-global, specific, and intermediate. This paper describes the generation of the EmoSpell dictionary using three sources: the Jspell Portuguese dictionary and the lexical bases EMOTAIX. PT and SentiLex-PT. Additionally, this paper details the Web application and Web service that exploit this dictionary. It also presents a validation of the proposed approach using a corpus of student texts with different emotional loads. The validation compares the analyses provided by EmoSpell with the mentioned emotional lexical bases on the ability to recognize emotional words and extract the dominant emotion from a text.

Abstract
Learning to program is hard. Students need to remain motivated to keep practicing and to overcome their difficulties. Several approaches have been proposed to foster students’ motivation. As most people enjoy playing games of some kind and play on a regular basis, the use of games is one of the most widely spread approaches. However, taking full advantage of games to teach specific concepts of programming requires much effort. This paper presents Asura, a game-based assessment environment built on top of Mooshak that challenges students to code Software Agents (SAs) to play a game, allowing them to test the SAs against each others’ SAs and watch a movie of the test. Once the challenge development stage ends, teachers are able to organize game-like tournaments among SAs. One of the key features of Asura is that it provides a means to reduce the required effort of building game-based challenges up to that of creating traditional programming exercises. © José Carlos Paiva and José Paulo Leal.

Abstract
Learning through practice is crucial to acquire a complex skill. Nevertheless, learning is only effective if students have at their disposal a wide range of exercises that cover all the course syllabus and if their solutions are promptly evaluated and given the appropriate feedback. Currently the teaching-learning process in complex domains, such as computer programming, is characterized by an extensive curricula and a high enrolment of students. This poses a great workload for faculty and teaching assistants responsible for the creation, delivering and assessment of student exercises. In order to address these issues, we created an e-learning framework - called Ensemble - as a conceptual tool to organize and facilitate technical interoperability among systems and services in domains that use complex evaluation. These domains need a diversity of tools, from the environments where exercises are solved, to automatic evaluators providing feedback on the attempts of students, not forgetting the authoring, management and sequencing of exercises. This paper presents and analyzes the use of Ensemble for managing the teaching-learning process in an introductory programming course at ESEIG - a school of the Polytechnic of Porto. An experiment was conducted to validate a set of hypotheses regarding the expected gains: increase in number of solved exercises, increase class attendance, improve final grades. They support the conclusion that the use of this e-learning framework for the practice-based learning has a positive impact on the acquisition of complex skills, such as computer programming. © Springer International Publishing AG, part of Springer Nature 2018.