Daniel Lichtnow

Quality Ontology for Recommendation in an Adaptive Educational System

In this paper, we present an ontology-based and student´ model to recommend the most suited material of study for each student in e-learning environments. Our aim is to increment the current systems personalization capabilities for student´s in different scenarios making use of learning objects ontology. This approach is being developed in an e-learning environment: the AdaptWeb system. The main features of the recommendations aspects for student´s profile are described and we use some examples to discuss and illustrate how to provide this personalization.

Recommendation of Learning Material through Students´ Collaboration and User Modeling in an Adaptive E-Learning Environment

In this chapter, we present an approach for recommendation of learning materials to students in an e-learning environment. Our aim is to increase the current system’s personalization capabilities for students in different scenarios making use of recommendation techniques. The recommendation is produced considering learning materials’ properties, student’s profile and the context of use. In addition, the process of recommendation is improved through students´ collaboration. In the context of this work, a learning material is a link to a Web page or a paper available on the Web and previously stored in a private repository. The process of collaboration occurs during student’s evaluations of the recommendations. These student´s evaluations are used by the system to produce new recommendations for other students. The main features of the recommendations aspects are described and some examples are also used to discuss and illustrate how to provide this personalization.

Using Papers Citations for Selecting the Best Genomic Databases

Selecting the right data is an essential activity in Genomic-related Information Systems. This work aims to analyze if it is possible to select the best genomic databases from a catalog using information about papers citations related to these genomic databases. The motivation for using information about citations has to do with the fact that it is not easy to obtain proper metadata with respect to these databases. Thus, in this work, information related to papers citations is used for measuring three distinct data quality dimensions: believability, timeliness, and relevancy. Believability is evaluated through the inspection of the number of citations. The variation of the number of citations over time is useful for determining the recency of a database and it is related to the timeliness dimension. Regarding to relevancy, the keywords of papers are useful to indicate the main context of application of these databases.

Using Scientific Publications to Identify People with Similar Interests

In many situations, related to some types of systems or organizations’ tasks, it is necessary to identify people with similar profiles. In the case of a collaborative recommender system, items to be recommended are those associated to similar users. Another example, in the academic environment, is to identify new members to be part of a research group (people with similar profiles). This task of identifying people with similar profiles can be time-consuming. In this sense, this work considers that scientific papers written by people can be used to identify users with similar profiles. Considering this assumption, we have done some experiments to identify which parts of papers, which type of indexes (terms or concepts) and which type of similarity functions (Jaccard or a Fuzzy function) are more suitable to identify similar people. The paper presents the results of some experiments and some application scenarios considering academic environments.

Time-Aware Recommender Systems: A Systematic Mapping

A Recommender System (RS) provides personalized suggestions of objects of users’ interest or that they may like. Traditional RS techniques consider only aspects related to users and items to recommend and ignore contextual information. Context-Aware RS (CARS) consider information about the user’s context to improve the recommendation process. Time is adimension of context that has the advantage of being easy to collect, since almost any system can record the interaction timestamp. Moreover, time can serve as valuable input for improving recommendation quality. Therefore, this work aims to investigate how time is being applied in CARS and, for this purpose, we used a Systematic Mapping methodology. In total, 88 papers were considered to answer the research questions defined. Initially we observed that the papers’ distribution by year have been increased in the last years. As a result, we also defined seven categories of how CARS uses the time in recommendation process.

The Use of Time Dimension in Recommender Systems for Learning.

When the amount of learning objects is huge, especially in the e-learning context, users could suffer cognitive overload. That way, users cannot find useful items and might feel lost in the environment. Recommender systems are tools that suggest items to users that best match their interests and needs. However, traditional recommender systems are not enough for learning, because this domain needs more personalization for each user profile and context. For this purpose, this work investigates Time-Aware Recommender Systems (Context-aware Recommender Systems that uses time dimension) for learning. Based on a set of categories (defined in previous works) of how time is used in Recommender Systems regardless of their domain, scenarios were defined that help illustrate and explain how each category could be applied in learning domain. As a result, a Recommender System for learning is proposed. It combines Content-Based and Collaborative Filtering approaches in a Hybrid algorithm that considers time in PreFiltering and Post-Filtering phases.

Sistema de Recomendações em Discussões Eletrônicas - Apoio à Construção do Conhecimento em Comunidades Virtuais de Aprendizagem

Webgrade is an on-line system for managing and publishing student grades on web. Webgrade provides: (1) to the teachers, features for managing grade plans, publishing student grades, and sending messages to the students by email; (2) to the students, access to their grades and number of absences to the classes, in a private and restrict page on the internet. All interactions between Webgrade and users are done by a web browser. Webgrade was developed with open-source technology and can be freely distributed under GPL.Resumo: Este artigo relata uma experiencia de inclusao digital (ID) do Programa de Extensao Onda Digital com 40 jovens carentes. O curso de Informatica Basica de 36 horas fez parte do programa educacional da ONG Eletrocooperativa. Este programa visa a formacao musical, melhoria das condicoes de trabalho e de cidadania de jovens afro-descendentes brasileiros. A experiencia de ID contou com a participacao de alunos do curso de graduacao em Ciencia da Computacao da UFBA, que atuaram como instrutores. O gerenciamento do curso, a elaboracao das aulas e do material didatico foram feitos com a utilizacao de ferramentas colaborativas livres. O proprio conteudo do curso de informatica foi baseado em solucoes livres, dentro do sistema operacional GNU/Linux. O resultado foi encorajador: dos 22 alunos que concluiram o curso com sucesso, 13 ja estao empregados em menos de 6 meses e 2 decidiram matricular-se em curso pre-vestibular. Acreditamos que iniciativas como esta despertam nos jovens a motivacao de engajar-se na universidade ou no mercado de trabalho. Abstract: This paper describes a digital inclusion (DI) experience of the OndaDigital Extension Program with 40 deprived teenagers. The IntroductoryInformatics Course had a total of 36 hours and was part of the EducationalProgram from the NGO Eletrocooperativa. Their program focuses on musicalformation, improvement of work condition and citizenship of afro-descendantsBrazilian youngsters. This DI experience counted with the participation ofstudents from the Computer Science undergraduate course of UFBA asmonitors and instructors. The management of the course, preparation oflessons and pedagogical material was done using a collaborative tool basedon free software. The course content was also based on free softwareapplications using GNU/Linux operating system. The results were veryencouraging: from the 22 students that successfully finished the course, 13found a job in less than six months and 2 decided to take preparatory coursesfor entering university. We believe that initiatives like this one motivateteenagers to aim for the university or enter the job market.

Describing Scenarios and Architectures for Time-Aware Recommender Systems for Learning

This work investigates the use of Time-Aware Recommender Systems in e-learning systems. In this sense, in the work are defined recommender systems architectures taking into account how the time can be used in recommender systems in the learning domain. For each architecture the main requirements to use the time in a specific way is identified, and some algorithm ideas area presented. Scenarios are presented to illustrate how the proposal architectures can be useful. The results of this work can guide other researches on the field to apply recommender systems techniques in the learning domain.

Evaluation of usability and user experience regarding the gamification of educational systems

Gamification, which is the use of game techniques in contexts not related to games, has been increasingly used in the educational area to motivate and engage students. The aim of this paper is to evaluate the usability and the user experience of gamified educational systems. For this, a heuristic evaluation using the ergonomic criteria as guideline was conducted in 10 different gamified educational systems. From them, 4 systems with more problems were selected to perform usability testing in the laboratory and to fill out a questionnaire by participants. In the end, the usability and user experience problems found are discussed and a comparison between the evaluations of experts and users is performed.

A Framework Reactive and Proactive for Pervasive Homecare Environments

Smart environments are spaces that interact with users taking into account their needs and preferences. Systems that manage these environments need to manipulate the context for interacting in a suitable way with users. One big challenge for creating a smart environment is to deal with context dynamicity. Ideally, these computer-supported environments must detect relevant events to forecast future situations and to act proactively to mitigate or eliminate situations related to specific user’s needs. This paper proposes a framework for providing extensible, reactive and proactive behavior in Smart Environment systems. The focus of the present work is related to a specific class of Smart Environments: an Ambient Assisted Living. In this sense we define a framework and illustrate practical aspects of the use of framework by describing a home-care scenario in which the system observes the behavior of the user, as the time goes by, and detects relevant situations and acts reactively and proactively for preserving user health condition.