Effects of Gamified Augmented Reality in Public Spaces

Advancements in smartphone technology have resulted in the proliferation of Augmented Reality (AR) applications and games. Researchers have acknowledged the great potential of AR applications to enhance entertainment and improve learning experiences. In this study, we examined the potential effects of gamified AR in public places. We developed ARQuiz, an AR-based quiz game, for a public exhibition space and conducted a user study with respondents via survey (N = 176; 55.68% female, mean age 35.94 and SD = 11.89) and face-To-face interview (N = 28; 57.14% female, mean age 31.07 and SD = 7.42). We analyzed the relationship between perceived application usefulness, perceived application enjoyment, perceived exhibition enjoyment, and perceived quiz enjoyment. In addition, we examined perceived sociability before and after the quiz, quiz score, and user behavior in the exhibition space. The results indicate that visitors who enjoyed playing the ARQuiz game enjoyed the exhibition more, obtained better quiz results and felt more social after visiting the exhibition. Furthermore, the ARQuiz was regarded as a possible platform for improving visitors learning and overall experiences in public exhibitions. Although some players expressed concerns about the privacy and intrusiveness of AR, our results indicate that a well-designed AR game may boost the overall satisfaction of an exhibition visit and increase players sociabilitys. © 2013 IEEE.Peer reviewe

Eye tracking in maritime immersive safe oceans technology

This paper presents the integration of eye tracking in the MarSEVR (Maritime Safety Education with VR) technology to increase the precision of the trainee focus on delivering the learning episodes of the technology with enhanced impressiveness and user engagement. MarSEVR is part of the Safe Oceans concept, a green ocean technology that integrates several VR safety training applications to reduce maritime accidents that result into human casualties, sea pollution and other environmental damages. The paper indicates the research delivery architecture driven by Hevner's design science in information systems Research for usability, use experience (UX) and effectiveness. Furthermore, this technology integration is approached from a game design perspective for user engagement but also from a cognitive and neuroscience perspective for pedagogical use and purposes. The paper addressees the impact of the eye tracking technology in the maritime sector operations, training market, and competitive research. Lastly areas of further research are presented and the efforts to link and align finger tracking and hand recognitions technologies with eye tracking for a more complete VR training environment

Introduction to the Special Issue on Emotions in Reading, Learning, and Communication

In our current era, learners are confronted with many and varying sources of information, such as news media, books, websites, social media, scientific articles, communicative interactions, and more. In addition, individuals must learn from such sources, making it important to critically examine the factors underlying learning from text and discourse. Importantly, the valence and activation of readers' emotions can influence the quality of readers' processing, which could help or hinder the learner's ability to understand and learn from text related to important issues. Although theoretical and empirical work documents the role of emotions in learning and motivation, reading- and discourse-specific models are needed. At present, the literature examining reading presents conflicting findings related to the influence of emotion on textual processing. However, asproposed in the Process, Emotion, Task (PET) framework, the discrepant findings related to reading processes may be explained by interactions between specific reader emotions and the type of task. Hence, examining both emotions and features of the text are critical when considering how to support readers' ability to comprehend, evaluate, and learn from text. This article introduces a special issue of Discourse Processes that brings together experts engaging in empirical studies on how emotion influences learning and processing for varying text types in different contexts. Our goal is to further work toward developing a more cohesive understanding of the influence of reader emotions in supporting learning, comprehension, processing, and conceptual change and to draw important connections to the broader fields of text and discourse, learning, and motivation. Such connections are critical for improving learning experiences across a variety of settings and enhancing the relevance of discourse-processing research

Eye tracking as an MT evaluation technique

Eye tracking has been used successfully as a technique for measuring cognitive load in reading, psycholinguistics, writing, language acquisition etc. for some time now. Its application as a technique for measuring the reading ease of MT output has not yet, to our knowledge, been tested. We report here on a preliminary study testing the use and validity of an eye tracking methodology as a means of semi-automatically evaluating machine translation output. 50 French machine translated sentences, 25 rated as excellent and 25 rated as poor in an earlier human evaluation, were selected. Ten native speakers of French were instructed to read the MT sentences for comprehensibility. Their eye gaze data were recorded non-invasively using a Tobii 1750 eye tracker. The average gaze time and fixation count were found to be higher for the “bad” sentences, while average fixation duration and pupil dilations were not found to be substantially different for output rated as good and output rated as bad. Comparisons between HTER scores and eye gaze data were also found to correlate well with gaze time and fixation count, but not with pupil dilation and fixation duration. We conclude that the eye tracking data, in particular gaze time and fixation count, correlate reasonably well with human evaluation of MT output but fixation duration and pupil dilation may be less reliable indicators of reading difficulty for MT output. We also conclude that eye tracking has promise as a semi-automatic MT evaluation technique, which does not require bi-lingual knowledge, and which can potentially tap into the end users’ experience of machine translation output

MARV: a tool for genome-wide multi-phenotype analysis of rare variants

Background: Genome-wide association studies have enabled identification of thousands of loci for hundreds of traits. Yet, for most human traits a substantial part of the estimated heritability is unexplained. This and recent advances in technology to produce high-dimensional data cost-effectively have led to method development beyond standard common variant analysis, including single-phenotype rare variant and multi-phenotype common variant analysis, with the latter increasing power for locus discovery and providing suggestions of pleiotropic effects. However, there are currently no optimal methods and tools for the combined analysis of rare variants and multiple phenotypes. Results: We propose a user-friendly software tool MARV for Multi-phenotype Analysis of Rare Variants. The tool is based on a method that collapses rare variants within a genomic region and models the proportion of minor alleles in the rare variants on a linear combination of multiple phenotypes. MARV provides analyses of all phenotype combinations within one run and calculates the Bayesian Information Criterion to facilitate model selection. The running time increases with the size of the genetic data while the number of phenotypes to analyse has little effect both on running time and required memory. We illustrate the use of MARV with analysis of triglycerides (TG), fasting insulin (FI) and waist-to-hip ratio (WHR) in 4,721 individuals from the Northern Finland Birth Cohort 1966. The analysis suggests novel multi-phenotype effects for these metabolic traits at APOA5 and ZNF259, and at ZNF259 provides stronger support for association (P TG+FI = 1.8 × 10−9) than observed in single phenotype rare variant analyses (P TG = 6.5 × 10−8 and P FI = 0.27). Conclusions: MARV is a computationally efficient, flexible and user-friendly software tool allowing rapid identification of rare variant effects on multiple phenotypes, thus paving the way for novel discoveries and insights into biology of complex traits

SCOPA and META-SCOPA: software for the analysis and aggregation of genome-wide association studies of multiple correlated phenotypes

Abstract Background: Genome-wide association studies (GWAS) of single nucleotide polymorphisms (SNPs) have been successful in identifying loci contributing genetic effects to a wide range of complex human diseases and quantitative traits. The traditional approach to GWAS analysis is to consider each phenotype separately, despite the fact that many diseases and quantitative traits are correlated with each other, and often measured in the same sample of individuals. Multivariate analyses of correlated phenotypes have been demonstrated, by simulation, to increase power to detect association with SNPs, and thus may enable improved detection of novel loci contributing to diseases and quantitative traits