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The identity and institutional image of universities are presented to the world through their websites. On their websites, universities publish their academic offerings, their mission, their vision, their academic objectives, their achievements, their regulations, their news and all their university work. Hence, the importance of university websites is accessible. The accessibility of university websites has been evaluated several times in the past, but there is no work that has summarized all the evaluations performed to provide a general overview of the situation. Therefore, in this research we have performed a systematic literature review (SLR) to consolidate, analyze, synthesize and interpret the accessibility results of university websites published in 42 papers that have been selected for this study. The methodology used in this SLR was that proposed in Kitchenham's guidelines, which includes three stages: planning the review, conducting the review and reporting the review. The results present the analysis and synthesis of the evaluations of 9,140 universities in 67 countries. Of these, 38,416 web pages, 91,421 YouTube videos and 28,395 PDF documents were evaluated. Manual methods, methods with automatic tools and the combination of both methods were used for the evaluation. Most websites were evaluated using the ISO/IEC 40500:2012 and Section 508 standards. The accessibility guidelines most commonly violated in the evaluations were: adaptable, compatible, distinguishable, input assistance, keyboard accessible, navigable, predictable, readable and text alternatives. In conclusion, the university websites, YouTube videos and PDF documents analyzed in the 42 papers present important accessibility problems. The main contribution of this SLR is the consolidation of the results of the 42 studies selected to determine the findings and trends in the accessibility of university websites around the world.
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Autism spectrum disorder (ASD) covers a range of neurodevelopmental disorders that begin in early childhood and affects developmental activities. This condition can negatively influence the gaining of knowledge, skills, and abilities, such as communication. Over time, different techniques and methods have been put into practice to teach and communicate with children with ASD. With the rapid advancement in the field of technology, specifically in smartphones, researchers have generated creative applications, such as mobile serious games, to help children with ASD. However, usability and accessibility have not been often taken into account in the development of this type of applications. For that reason, in this work we considered that both, usability and especially accessibility are a very important differentiators for the quality and efficiency of mobile serious games. Our approach has two important contributions, the incorporation of accessibility as a fundamental requirement in the development of a mobile serious game and the proposal of a method for the development of this type of applications for children with ASD, a method that can be used by other developers.
Assuntos
Transtorno do Espectro Autista , Criança , Pré-Escolar , Comunicação , Humanos , Projetos de Pesquisa , TecnologiaRESUMO
The eXtensible Markup Language (XML) files are widely used by the industry due to their flexibility in representing numerous kinds of data. Multiple applications such as financial records, social networks, and mobile networks use complex XML schemas with nested types, contents, and/or extension bases on existing complex elements or large real-world files. A great number of these files are generated each day and this has influenced the development of Big Data tools for their parsing and reporting, such as Apache Hive and Apache Spark. For these reasons, multiple studies have proposed new techniques and evaluated the processing of XML files with Big Data systems. However, a more usual approach in such works involves the simplest XML schemas, even though, real data sets are composed of complex schemas. Therefore, to shed light on complex XML schema processing for real-life applications with Big Data tools, we present an approach that combines three techniques. This comprises three main methods for parsing XML files: cataloging, deserialization, and positional explode. For cataloging, the elements of the XML schema are mapped into root, arrays, structures, values, and attributes. Based on these elements, the deserialization and positional explode are straightforwardly implemented. To demonstrate the validity of our proposal, we develop a case study by implementing a test environment to illustrate the methods using real data sets provided from performance management of two mobile network vendors. Our main results state the validity of the proposed method for different versions of Apache Hive and Apache Spark, obtain the query execution times for Apache Hive internal and external tables and Apache Spark data frames, and compare the query performance in Apache Hive with that of Apache Spark. Another contribution made is a case study in which a novel solution is proposed for data analysis in the performance management systems of mobile networks.
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This study determines one of the most relevant quality factors of apps for people with disabilities utilizing the abductive approach to the generation of an explanatory theory. First, the abductive approach was concerned with the results' description, established by the apps' quality assessment, using the Mobile App Rating Scale (MARS) tool. However, because of the restrictions of MARS outputs, the identification of critical quality factors could not be established, requiring the search for an answer for a new rule. Finally, the explanation of the case (the last component of the abductive approach) to test the rule's new hypothesis. This problem was solved by applying a new quantitative model, compounding data mining techniques, which identified MARS' most relevant quality items. Hence, this research defines a much-needed theoretical and practical tool for academics and also practitioners. Academics can experiment utilizing the abduction reasoning procedure as an alternative to achieve positivism in research. This study is a first attempt to improve the MARS tool, aiming to provide specialists relevant data, reducing noise effects, accomplishing better predictive results to enhance their investigations. Furthermore, it offers a concise quality assessment of disability-related apps.
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Language is the primordial element for cultural transfer in indigenous communities; if it is not practiced, there is a risk of losing it and with it, a large part of the history of a community. Ecuador is a multicultural and multiethnic country with 18 indigenous peoples. Currently, in this country, some native languages are at risk of disappearing due to factors such as racial discrimination, underestimation of the language, and, above all, the lack of interest and motivation of the new generations to learn this language. Information technologies have made it possible to create mobile applications such as games, dictionaries, and translators that promote the learning of the Kichwa language. However, the acceptance of technology has not been evaluated, nor the intention to involve mobile devices in the process of teaching this language. Subsequently the objective of this work is to explore the acceptance of technology and the use of mobile devices to motivate the learning of the Kichwa language. For this purpose, the mobile application "Otavalo Rimay" was used with several students of a Kichwa language learning center. The methodology used to verify the hypothesis of this work was Design Sciences Research (DSR) together with the theory of acceptance and use of technology (UTAUT). The instrument used for this evaluation was a survey carried out after the use of the mobile application. The statistical analysis of the results obtained indicates characteristics such as the utility and perceived ease of use, positively influence students to motivate the use of mobile devices in learning a language. The results also show the great technological acceptance by students for learning and confirm that currently, mobile learning is accepted for use in education.
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This article presents the process of building a dataset for evaluation of the accessibility of 368 web pages, beginning with Webometrics rankings, the WAVE tool was used in the evaluation of the web pages. The dataset documents data on repeated errors with higher frequency, in such a way that they alert the web developers, supporting them in creating more inclusive and accessible websites for all types of people, including users with disabilities. The data show that university websites have frequent problems related to the lack of alternative text linked to images. Some of the university websites included in this dataset were found to violate web accessibility requirements based on the Web Content Accessibility Guidelines 2.0 and 2.1. Therefore, this data has been shared to allow replication of the experiment, and serve as an input to future studies related to web accessibility. The dataset is hosted, with public access, in the Mendeley Dataset Repository.