Informatics, Volume 6, Issue 3 (September 2019) – 17 articles

Incorporating gamification into training–learning at universities is hampered by a shortage of quality, adapted educational video games. Large companies are leading in the creation of educational video games for their internal training or to enhance their public image and universities can benefit from collaborating. The aim of this research is to evaluate, both objectively and subjectively, the potential of the simulation game BugaMAP (developed by the MAPFRE Foundation) for university teaching about insurance. To this end, we have assessed both the game itself and the experience of using the game as perceived by 142 economics students from various degree plans and courses at the University of Seville during the 2017–2018 academic year. As a methodology, a checklist of gamification components is used for the objective evaluation, and an opinion questionnaire on the game experience is used for the subjective evaluation. Among the results several findings stand out. One is the high satisfaction of the students with the knowledge acquired using fun and social interaction. Another is that the role of the university professors and the company monitors turns out to be very active and necessary during the game-learning sessions. Finally, in addition to the benefits to the university of occasionally available quality games to accelerate student skills training, the company–university collaboration serves as a trial and refinement of innovative tools for game-based learning. Full article

This study aims to analyse how translation experts from the German department of the European Commission’s Directorate-General for Translation (DGT) identify and correct different error categories in neural machine translated texts (NMT) and their post-edited versions (NMTPE). The term translation expert encompasses translator, post-editor as well as revisor. Even though we focus on neural machine-translated segments, translator and post-editor are used synonymously because of the combined workflow using CAT-Tools as well as machine translation. Only the distinction between post-editor, which refers to a DGT translation expert correcting the neural machine translation output, and revisor, which refers to a DGT translation expert correcting the post-edited version of the neural machine translation output, is important and made clear whenever relevant. Using an automatic error annotation tool and the more fine-grained manual error annotation framework to identify characteristic error categories in the DGT texts, a corpus analysis revealed that quality assurance measures by post-editors and revisors of the DGT are most often necessary for lexical errors. More specifically, the corpus analysis showed that, if post-editors correct mistranslations, terminology or stylistic errors in an NMT sentence, revisors are likely to correct the same error type in the same post-edited sentence, suggesting that the DGT experts were being primed by the NMT output. Subsequently, we designed a controlled eye-tracking and key-logging experiment to compare participants’ eye movements for test sentences containing the three identified error categories (mistranslations, terminology or stylistic errors) and for control sentences without errors. We examined the three error types’ effect on early (first fixation durations, first pass durations) and late eye movement measures (e.g., total reading time and regression path durations). Linear mixed-effects regression models predict what kind of behaviour of the DGT experts is associated with the correction of different error types during the post-editing process. Full article

Smart technology in the area of the Internet of Things (IoT) that extensively gathers user data in order to provide full functioning has become ubiquitous in our everyday life. At the workplace, individual’s privacy is especially threatened by the deployment of smart monitoring technology due to unbalanced power relations. In this work we argue that employees’ acceptance of smart monitoring systems can be predicted based on privacy calculus considerations and trust. Therefore, in an online experiment (N = 661) we examined employees’ acceptance of a smart emergency detection system, depending on the rescue value of the system and whether the system’s tracking is privacy-invading or privacy-preserving. We hypothesized that trust in the employer, perceived benefits and risks serve as predictors of system acceptance. Moreover, the moderating effect of privacy concerns is analyzed. Full article

The accessibility and quality of public open spaces (e.g., parks, gardens, squares and plazas) are critical for cultural identity development as they provide important gathering points in the urban fabric and offer a place for social activities, enabling interaction among people of different generations and ethnicities. Public open spaces enhance the urban environment by providing important ecological processes and ecosystem services. The current research generates knowledge about co-creation approach to be used to merge the application of information and communication technologies (ICT) with these essential functions of the public spaces. It explores new dynamics of open spaces as a trusted service for the community and expands our understanding of how meditated public open spaces function, paying attention to stakeholders, local context and different social groups. The paper presents the design of Digital Co-Creation Index and methodological guidelines for applying Digital Co-creation monitoring technique for evaluation of co-creation processes in designing attractive, inclusive and responsive public open spaces. Full article

Many systems rely on the expertise from human operators, who have acquired their knowledge through practical experience over the course of many years. For the detection of anomalies in industrial settings, sensor units have been introduced to predict and classify such anomalous events, but these critically rely on annotated data for training. Lengthy data collection campaigns are needed, which tend to be combined with domain expert annotations of the data afterwards, resulting in costly and slow process. This work presents an alternative by studying live annotation of rare anomalous events in sensor streams in a real-world manufacturing setting by experienced human operators that can also observe the machinery itself. A prototype for visualization and in situ annotation of sensor signals is developed with embedded unsupervised anomaly detection algorithms to propose signals for annotation and which allows the operators to give feedback on the detection and classify anomalous events. This prototype allowed assembling a corpus of several weeks of sensor data measured in a real manufacturing surrounding and was annotated by domain experts as an evaluation basis for this study. The evaluation of live annotations reveals high user motivation after getting accustomed to the labeling prototype. After this initial period, clear anomalies with characteristic signal patterns are detected reliably in visualized envelope signals. More subtle signal deviations were less likely to be confirmed an anomaly due to either an insufficient visibility in envelope signals or the absence of characteristic signal patterns. Full article

This paper provides a summary of progress on implementation research conducted to deliver evidence-based informatics infrastructure and guidance resources to advance integrated care in Ireland. (1) Background: The International Classification for Nursing Practice (ICNP^©) R&D centre has progressed with its agenda to advance informatics theory and optimise the nursing contribution within eHealth Ireland. The centre has evolved as a formal multi-disciplinary research centre in Dublin City University expanding its research activity to become the Centre for eIntegrated Care (CeIC). The mission of the CeIC is to advance eIntegrated care in order to improve health and wellbeing of citizens; (2) Methods: In this paper, CeIC offers insights into the specific approaches adopted to realise this vision using Innovation 2.0 and Open Science as an emerging paradigm and rigorous methodology to drive transformational change; (3) Conclusions; we provide here a summary of our activity and discuss our experiences to date. We present detail on our progress through three core viewpoints namely (1) the individual and stakeholder engagement; (2) the development of technology infrastructure and (3) the political process considering the academic role in advancing informatics research. Our conclusions suggest that one needs to intrinsically link all three perspectives and provide focused interactions in order to bring about sustainable change for progression of eHealth. Full article

This paper takes a high-level view of both the sources and status of uncertainty in historical research and the manners in which possible negative effects of this omnipresent characteristic might be managed and mitigated. It draws upon both the experience of a number of digital projects and research into the many-faceted concept of uncertainty in data, and in particular, it explores the conflicting strategies for the management of uncertainty in historical research processes that are reflected in the historiographical and digital humanities literature. Its intention is to support a dialogue between the humanities and computer science, able to realise the promise of digital humanities without a reversion to a new positivism in disciplines such as history and literary studies and it therefore concludes with recommendations for the developers of research tools and environments for digital history. Full article

To build state-of-the-art Neural Machine Translation (NMT) systems, high-quality parallel sentences are needed. Typically, large amounts of data are scraped from multilingual web sites and aligned into datasets for training. Many tools exist for automatic alignment of such datasets. However, the quality of the resulting aligned corpus can be disappointing. In this paper, we present a tool for automatic misalignment detection (MAD). We treated the task of determining whether a pair of aligned sentences constitutes a genuine translation as a supervised regression problem. We trained our algorithm on a manually labeled dataset in the FR–NL language pair. Our algorithm used shallow features and features obtained after an initial translation step. We showed that both the Levenshtein distance between the target and the translated source, as well as the cosine distance between sentence embeddings of the source and the target were the two most important features for the task of misalignment detection. Using gold standards for alignment, we demonstrated that our model can increase the quality of alignments in a corpus substantially, reaching a precision close to 100%. Finally, we used our tool to investigate the effect of misalignments on NMT performance. Full article

Different types of uncertainties occur in almost all datasets and are an inherent property of data across different academic disciplines, including digital humanities (DH). In this paper, we address, demonstrate and analyse spatio-temporal uncertainties in a non-standard German legacy dataset in a DH context. Although the data collection is primarily a linguistic resource, it contains a wealth of additional, comprehensive information, such as location and temporal detail. The addressed uncertainties have manifested because of a variety of reasons, and partly also because of decades of data transformation processes. We here propose our own taxonomy for capturing and classifying the various uncertainties, and show with numerous examples how the remedying but also re-introduction of uncertainties affects DH practices. Full article

This short communication proposes an exploratory investigation regarding the impact of social media information on interpersonal trust in new virtual work partners. The suggested approach assesses this potential impact via a combination of theories from informational economic studies and virtual team research. An initial theoretical model is also proposed. Full article

Gamification has recently been presented as a successful strategy to engage users, with potential for online education. However, while the number of publications on gamification has been increasing in recent years, a classification of its empirical effects is still missing. We present a systematic literature review conducted with the purpose of closing this gap by clarifying what effects gamification generates on users’ behaviour in online learning. Based on the studies analysed, the game elements most used in the literature are identified and mapped with the effects they produced on learners. Furthermore, we cluster these empirical effects of gamification into six areas: performance, motivation, engagement, attitude towards gamification, collaboration, and social awareness. The findings of our systematic literature review point out that gamification and its application in online learning and in particular in Massive Online Open Courses (MOOCs) are still a young field, lacking in empirical experiments and evidence with a tendency of using gamification mainly as external rewards. Based on these results, important considerations for the gamification design of MOOCs are drawn. Full article

As visualization becomes widespread in a broad range of cross-disciplinary academic domains, such as the digital humanities (DH), critical voices have been raised on the perils of neglecting the uncertain character of data in the visualization design process. Visualizations that, purposely or not, obscure or remove uncertainty in its different forms from the scholars’ vision may negatively affect the manner in which humanities scholars regard computational methods as useful tools in their daily work. In this paper, we address the issue of uncertainty representation in the context of the humanities from a theoretical perspective, in an attempt to provide the foundations of a framework that allows for the construction of ecological interface designs which are able to expose the computational power of the algorithms at play while, at the same time, respecting the particularities and needs of humanistic research. To this end, we review past uncertainty taxonomies in other domains typically related to the humanities and visualization, such as cartography and GIScience. From this review, we select an uncertainty taxonomy related to the humanities that we link to recent research in visualization for the DH. Finally, we bring a novel analytics method developed by other authors (Progressive Visual Analytics) into question, which we argue can be a good candidate to resolve the aforementioned difficulties in DH practice. Full article

Students’ motivation is a fundamental factor in the educational process, and can be facilitated through new methodologies and technologies, including gamification, video games, collaborative learning, or, in particular, the methodology called “collaborative learning with video games” (which is presented and can be understood as the implementation of educational activities in which students have to work together to achieve a goal, and the main resource of the activity is a video game). However, if teachers themselves are not motivated, or if they lack a positive attitude towards implementing these new methodologies, it will be difficult for students to feel motivated when approaching said resources. Therefore, it is important to know what teachers’ attitudes towards them are. The aim of this research is the creation of an attitudes scale towards collaborative learning with video games, aimed at in-service primary school teachers. Different methodological steps were followed that made its construction possible, such as the analysis of items and the verification of their reliability, resulting in a rigorous attitudes scale of 33 items, with a reliability of α = 0.947. This implies that the measurement instrument is validated and allows one to know the attitudes of in-service primary school teachers towards a new methodology related to the implementation of video games in education. Full article

Uncertainty is a standard condition under which large parts of art-historical and curatorial knowledge creation and communication are operating. In contrast to standard levels of data quality in non-historical research domains, historical object and knowledge collections contain substantial amounts of uncertain, ambiguous, contested, or plainly missing data. Visualization approaches and interfaces to cultural collections have started to represent data quality and uncertainty metrics, yet all existing work is limited to representations for isolated metadata dimensions only. With this article, we advocate for a more systematic, synoptic and self-conscious approach to uncertainty visualization for cultural collections. We introduce omnipresent types of data uncertainty and discuss reasons for their frequent omission by interfaces for galleries, libraries, archives and museums. On this basis we argue for a coordinated counter strategy for uncertainty visualization in this field, which will also raise the efforts going into complex interface design and conceptualization. Building on the PolyCube framework for collection visualization, we showcase how multiple uncertainty representation techniques can be assessed and coordinated in a multi-perspective environment. As for an outlook, we reflect on both the strengths and limitations of making the actual wealth of data quality questions transparent with regard to different target and user groups. Full article

Massive Open Online Courses (MOOCs), regardless of their topic, are a perfect space to generate, through virtual learning communities associated with them, very valuable resources for their participants and, in general, anyone interested in the topic covered. If in the design of these learning spaces, elements specific to games are added to them, which is known as gamification, we can try to increase the engagement of the student towards the course and, therefore, towards the community. This paper presents an experience of a MOOC of Universidad Rey Juan Carlos (Spain) with a connectivist approach. Aspects such as fun and motivation have been worked on in the design, through the application of gamified activities and the use of elements from social networks, considered as gamification, with the aim of increasing participation and engagement within a Facebook group, used as a community to support the course. We have analyzed aspects such as enjoyment and motivation, the result of which has been active participation and high engagement within the MOOC community in the form of content and especially great interaction, highlighting the existence of continuous activity once the edition of the MOOC is finished, as a consequence of a habit generated in the student. Full article

Entrepreneurship is currently one of the most fundamental economic activities in the 21st century. Entrepreneurship encourages young generations to generate their self-employment and develop key soft-skills that will be useful throughout their professional career. This study aims to present and explore a case study of a higher education institution that adopts FLIGBY as a serious game, which allows students to develop entrepreneurship skills in an immersive way and based on real challenges that can be found in business environments. The findings indicate that FLIGBY offers relevant potentials and new possibilities in the development of management, leadership, and entrepreneurship skills. Furthermore, the game allows the inclusion of summative and formative assessment elements, which are essential in the process of monitoring and analyzing the student’s performance. Full article

The recent arrival on the market of high-performing neural MT engines will likely lead to a profound transformation of the translation profession. The purpose of this study is to explore how this paradigm change impacts the post-editing process, with a focus on lexico-grammatical patterns that are used in the communication of specialized knowledge. A corpus of 109 medical abstracts pre-translated from English into French by the neural MT engine DeepL and post-edited by master’s students in translation was used to study potential distortions in the translation of lexico-grammatical patterns. The results suggest that neural MT leads to specific sources of distortion in the translation of these patterns, not unlike what has previously been observed in human translation. These observations highlight the need to pay particular attention to lexico-grammatical patterns when post-editing neural MT in order to achieve functional equivalence in the translation of specialized texts. Full article