Authoring tools have been broadly used to design Intelligent Tutoring Systems (ITS). However, ITS community still lacks a current understanding of how authoring tools are used by non-programmer authors to design ITS. Hence, the objective of this work is to review how authoring tools have been supporting ITS design for non-programmer authors. In order to meet our goal, we conduct a Systematic Literature Review (SLR) to identify the primary studies on the use of ITS authoring tools, following a pre-defined review protocol. Among the 4622 papers retrieved from seven digital libraries published from 2009 to June 2016, 33 papers are finally included after applying our exclusion and inclusion criteria. We then identify the main ITS components authored, the ITS types designed, the features used to facilitate the authoring process, the technologies used to develop authoring tools and the time at which authoring occurs. We also look for evidence of the benefits of ITS authoring tools. In summary, the main findings of this work are: (1) there is empirical evidence of the benefits (i.e., mainly in terms of effectiveness, efficiency, quality of authored artifacts, and usability) of using ITS authoring tools for non-programmer authors, specially to aid authoring of learning content and to support authoring of modeltracing/cognitive and example-tracing tutors; 2) domain and pedagogical models have been much more targeted by authoring tools; (3) several ITS types have been authored, with an emphasis on model-tracing/cognitive and example-tracing tutors;

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Universidade do Rio dos Sinos, PIPCA Av. Unisinos, 950 -Cristo Rei, CEP: 93022-000, São Leopoldo / RS -Brasil !pjaques@unisinos.br ABSTRACTIn this work we present a way to classify students from a gamified online learning environment according to their interactions, and to use the results to create and recommend "missions" -a gamification element that contains challenging tasks to keep students engaged -that focus on: (1) the students' most common interactions, (2) the students' least common interactions (to balance their online behavior), and (3) more than one type of interaction at the same time. The classification approach was systematically applied, following the Pedagogical Recommendation Process. It's main objective was to assist teachers creating personalized missions.We applied a questionnaire to compare the new approach (classification according to patterns in interactions) to the existing one (a report showing some actions students took in the environment). In the results, the classification approach provided a better way to evaluate the students, regarding the three missions' focus.

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Abstract-Ontologies are formal representations of knowledge about a given domain. Based on them, it is possible to create more expressive knowledge bases that can be shared, extended and reused in different scenarios. In software engineering, ontologies can contribute in many different ways to improve the models, methods, techniques and processes of software development. Nevertheless, the use and benefits of ontologies and Semantic Web technologies in Software Engineering is spread across several articles and books available in the literature. In this context, this paper aims at compiling and presenting the research findings and potential benefits when applying ontologies to address three major challenges in software engineering: (1) difficulty in communicating and sharing information; (2) effective management of software development phases; and (3) development techniques and environments to support the production of semantic software through an interdisciplinary approach. We believe that the review of the literature and discussions presented in this work can contribute to disseminate best practices of using ontologies in software development as well as to give directions about this field of research, its challenges and opportunities.

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Resumo.A dissertação trata da conceitualização e criação de uma ferramenta para a recomendação pedagógica cujo objetivo é prover aos professores de cursos baseados na web, recomendações pedagógicas personalizadas geradas por especialistas no domínio com base nos resultados da mineração dos dados educacionais dos alunos. A ferramenta segue o Processo de Recomendação Pedagógica e foi utilizada em um estudo de caso com dados reais de um curso de língua Espanhola com 200 alunos. Os resultados permitiram detectar padrões de interação úteis, usados na criação de recomendações, avaliadas (relevância) por especialistas no domínio educacional/pedagógico, e disponibilizadas para que os professores as oferecessem a seus alunos.