The Efficacy of a Novel Video Game Intervention (MindLight) in Reducing Children's Anxiety

Anxiety disorders are the most prevalent form of psychopathology among children and adolescents. Because demand for treatment far exceeds availability, there is a need for alternative approaches that are engaging, accessible, cost-effective, and incorporate practice to reach as many youth as possible. One novel approach is a video game intervention called MindLight that uses two evidence-based strategies to target childhood anxiety problems. Using neurofeedback mechanics to train players to: (1) attend to positive rather than threatening stimuli and (2) down-regulate arousal during stressful situations, MindLight teaches children how to practice overcoming anxious thoughts and arousal in a fun and engaging context. The present study examined the effectiveness of MindLight versus online cognitive-behavioural therapy (CBT) based psychoeducation sessions as a comparison in reducing anxiety in a sample of 144 anxious children, which was measured in three ways: (1) anxiety symptoms, (2) state anxiety in response to stress, and (3) psychophysiological arousal in response to stress. Children between the ages of 8.05–17.78 years (M=13.61, SD=1.79) were randomly assigned to play MindLight or complete psychoeducation for five hours over three weeks. State anxiety and psychophysiological arousal were assessed in response to two stress tasks before and after exposure to MindLight or psychoeducation. Anxiety symptoms were also measured via a questionnaire. Overall, participants showed significant reductions in anxiety symptoms and state anxiety in response to stress, but not psychophysiological arousal in response to stress. Moreover, the magnitude of reductions in anxiety did not differ between interventions but by age and sex. Specifically, older participants showed a greater decrease in severity of state anxiety in response to a social stressor than younger participants and girls showed a greater decrease in severity of state anxiety in response to a cognitive stressor than boys. The present study suggests that playing MindLight results in similar reductions in anxiety as one of the more common means of delivering CBT principles to youth.

Preferencias, dedicación y problemáticas generadas por los videojuegos: Una perspectiva de género

Entre las actividades de ocio de los/as jóvenes, cabe mencionar las asociadas con los videojuegos. Por ello, la finalidad central de este estudio es analizar las preferencias del colectivo de adolescentes con los videojuegos, así como conocer su dedicación y problemáticas que generan, teniendo en cuenta principalmente la variable de género. El presente trabajo se encuadra en un enfoque metodológico cuantitativo-cualitativo, a partir de la recogida de datos con un cuestionario y la técnica del grupo de discusión. En el estudio han participado un total de 151 adolescentes. 124 a partir de la aplicación de un cuestionario cerrado (62 hombres y 62 mujeres) y 27 a través de la realización de 6 grupos de discusión (17 hombres y 10 mujeres). Como resultados y conclusiones, cabe destacar la existencia diferenciada en el uso de los videojuegos en función de la edad y por razón de género. A su vez, las mujeres muestran una responsabilidad mayor en esta actividad, tanto en el tiempo de dedicación como en la elección. Los chicos destinan una gran cantidad de tiempo a los videojuegos de contenido violento, mientras las chicas prefieren los de estrategia. En general, el juego con videojuegos no genera problemáticas sustanciales y controversias, aunque algunos participantes reflejan manifestaciones de mal humor. Por último, cabe indicar que las prácticas con los videojuegos en la adolescencia se ciñen al mero hecho de divertirse, desperdiciando las posibilidades educativas que esta actividad ofrece.

Transgresión de las identidades tradicionales de género mediante la representación gráfica de mujeres protagonistas para videojuegos desarrollada por niños y niñas

El artículo identifica y analiza el discurso predominante que poseen 12 niños y 7 niñas de 7° y 8° año básico pertenecientes a 4 establecimientos educacionales en la ciudad de Talca en Chile, en torno a la transgresión de las identidades tradicionales de la mujer en los videojuegos. Para ello durante el 1° semestre del año 2014 al interior de un programa de formación de profesores/as en Artes Visuales se implementa una estrategia didáctica centrada en la expresión gráfica denominada “Crea tu propia personaje para videojuego”. Haciendo partícipes a niños y niñas junto a profesionales en formación de una propuesta metodológica basada en la Investigación-Acción enmarcada en las prácticas profesionales. Concluyendo tras el análisis semántico de dibujos y relatos, que las imágenes representativas de la mujer en los videojuegos transgreden las identidades tradicionales de género al interior de un marco androcéntrico predominante.

A First Step Towards Video Enhanced Rubrics for the Formative Assessment of Complex Skills : A literature review and a plea

Paper presentation at the TEA2016 conference, Tallinn, Estonia.

Applying standards to systematize learning analytics in serious games

Learning Analytics is an emerging field focused on analyzing learners’ interactions with educational content. One of the key open issues in learning analytics is the standardization of the data collected. This is a particularly challenging issue in serious games, which generate a diverse range of data. This paper reviews the current state of learning analytics, data standards and serious games, studying how serious games are tracking the interactions from their players and the metrics that can be distilled from them. Based on this review, we propose an interaction model that establishes a basis for applying Learning Analytics into serious games. This paper then analyzes the current standards and specifications used in the field. Finally, it presents an implementation of the model with one of the most promising specifications: Experience API (xAPI). The Experience API relies on Communities of Practice developing profiles that cover different use cases in specific domains. This paper presents the Serious Games xAPI Profile: a profile developed to align with the most common use cases in the serious games domain. The profile is applied to a case study (a demo game), which explores the technical practicalities of standardizing data acquisition in serious games. In summary, the paper presents a new interaction model to track serious games and their implementation with the xAPI specification.

Game Learning Analytics: Learning Analytics for Serious Games

Video games have become one of the largest entertainment industries, and their power to capture the attention of players worldwide soon prompted the idea of using games to improve education. However, these educational games, commonly referred to as serious games, face different challenges when brought into the classroom, ranging from pragmatic issues (e.g. a high development cost) to deeper educational issues, including a lack of understanding of how the students interact with the games and how the learning process actually occurs. This chapter explores the potential of data-driven approaches to improve the practical applicability of serious games. Existing work done by the entertainment and learning industries helps to build a conceptual model of the tasks required to analyze player interactions in serious games (gaming learning analytics or GLA). The chapter also describes the main ongoing initiatives to create reference GLA infrastructures and their connection to new emerging specifications from the educational technology field. Finally, it explores how this data-driven GLA will help in the development of a new generation of more effective educational games and new business models that will support their expansion. This results in additional ethical implications, which are discussed at the end of the chapter.

Real-time detection of faces in video streams

[EN]This paper describes a face detection system which goes beyond traditional approaches normally designed for still images. First the video stream context is considered to apply the detector, and therefore, the resulting system is designed taking into consideration a main feature available in a video stream, i.e. temporal coherence. The resulting system builds a feature based model for each detected face, and searches them using various model information in the next frame. The results achieved for video stream processing outperform Rowley-Kanade's and Viola-Jones' solutions providing eye and face data in a reduced time with a notable correct detection rate.

A comparative study of translation strategies applied in dealing with role languages. : A translation analysis of the video game Final Fantasy XIV

Localisation is the process of taking a product and adapting it to fit the culture in question. This usually involves making it both linguistically and culturally appropriate for the target audience. While there are many areas in video game translations where localisation holds a factor, this study will focus on localisation changes in the personalities of fictional characters between the original Japanese version and the English localised version of the video game Final Fantasy XIV: A Realm Reborn and its expansion Heavensward for PC, PS3 and PS4. With this in mind, specific examples are examined using Satoshi Kinsui's work on yakuwarigo, role language as the main framework for this study. Five non-playable characters were profiled and had each of their dialogues transcribed for a comparative analysis. This included the original Japanese text, the officially localised English text and a translation of the original Japanese text done by myself. Each character were also given a short summary and a reasoned speculation on why these localisation changes might have occurred. The result shows that there were instances where some translations had been deliberately adjusted to ensure that the content did not cause any problematic issues to players overseas. This could be reasoned out that some of the Japanese role languages displayed by characters in this game could potentially cause dispute among the western audience. In conclusion, the study shows that localisation can be a difficult process that not only requires a translator's knowledge of the source and target language, but also display some creativity in writing ability to ensure that players will have a comparable experience without causing a rift in the fanbase.

Od Pacmana do Lary Croft. Jak badać postać w grach wideo?

This article offers an overview of various approaches, which have been used to examine video game characters. In its first part I am introducing several methodological directions, focusing on: characters as functions, characters as drivers of agency, representational gendered icons, and as players’ re-embodied realisations. In the second part I am focusing on the first holistic research method for player character in offline computer role-playing games (cRPGs). The proposed Pivot Player Character Model provides a method replicable across the cRPG genre and illustrates the experience of gameplay as perceived through the PC’s eyes. It has been largely inspired by Anne Ubersfeld’s semiological dramatic character research.

A contribution to semantic description of images and videos: an application of soft biometrics

Humans have a high ability to extract visual data information acquired by sight. Trought a learning process, which starts at birth and continues throughout life, image interpretation becomes almost instinctively. At a glance, one can easily describe a scene with reasonable precision, naming its main components. Usually, this is done by extracting low-level features such as edges, shapes and textures, and associanting them to high level meanings. In this way, a semantic description of the scene is done. An example of this, is the human capacity to recognize and describe other people physical and behavioral characteristics, or biometrics. Soft-biometrics also represents inherent characteristics of human body and behaviour, but do not allow unique person identification. Computer vision area aims to develop methods capable of performing visual interpretation with performance similar to humans. This thesis aims to propose computer vison methods which allows high level information extraction from images in the form of soft biometrics. This problem is approached in two ways, unsupervised and supervised learning methods. The first seeks to group images via an automatic feature extraction learning , using both convolution techniques, evolutionary computing and clustering. In this approach employed images contains faces and people. Second approach employs convolutional neural networks, which have the ability to operate on raw images, learning both feature extraction and classification processes. Here, images are classified according to gender and clothes, divided into upper and lower parts of human body. First approach, when tested with different image datasets obtained an accuracy of approximately 80% for faces and non-faces and 70% for people and non-person. The second tested using images and videos, obtained an accuracy of about 70% for gender, 80% to the upper clothes and 90% to lower clothes. The results of these case studies, show that proposed methods are promising, allowing the realization of automatic high level information image annotation. This opens possibilities for development of applications in diverse areas such as content-based image and video search and automatica video survaillance, reducing human effort in the task of manual annotation and monitoring.

Análise gráfica de estruturas porosas sobre a ótica da estereologia

In this work we developed a computer simulation program for physics porous structures based on programming language C + + using a Geforce 9600 GT with the PhysX chip, originally developed for video games. With this tool, the ability of physical interaction between simulated objects is enlarged, allowing to simulate a porous structure, for example, reservoir rocks and structures with high density. The initial procedure for developing the simulation is the construction of porous cubic structure consisting of spheres with a single size and with varying sizes. In addition, structures can also be simulated with various volume fractions. The results presented are divided into two parts: first, the ball shall be deemed as solid grains, ie the matrix phase represents the porosity, the second, the spheres are considered as pores. In this case the matrix phase represents the solid phase. The simulations in both cases are the same, but the simulated structures are intrinsically different. To validate the results presented by the program, simulations were performed by varying the amount of grain, the grain size distribution and void fraction in the structure. All results showed statistically reliable and consistent with those presented in the literature. The mean values and distributions of stereological parameters measured, such as intercept linear section of perimeter area, sectional area and mean free path are in agreement with the results obtained in the literature for the structures simulated. The results may help the understanding of real structures.

Del videojuego a la realidad : sistema interactivo para la seguridad vial

El vertiginoso crecimiento de los centros urbanos, las tecnologías emergentes y la demanda de nuevos servicios por parte de la población plantea encaminar esfuerzos hacia el desarrollo de las ciudades inteligentes. Éste concepto ha tomado fuerza entre los sectores político, económico, social, académico, ambiental y civil; de forma paralela, se han generado iniciativas que conducen hacia la integración de la infraestructura, la tecnología y los servicios para los ciudadanos. En éste contexto, una de las problemáticas con mayor impacto en la sociedad es la seguridad vial. Es necesario contar con mecanismos que disminuyan la accidentalidad, mejoren la atención a incidentes, optimicen la movilidad urbana y planeación municipal, ayuden a reducir el consumo de combustible y la emisión de gases de efecto de invernadero, así como ofrecer información dinámica y efectiva a los viajeros. En este artículo se describen dos (2) enfoques que contribuyen de manera eficiente dicho problema: los videojuegos como juegos serios y los sistemas de transporte inteligente. Ambos enfoques están encaminados a evitar colisiones y su diseño e implementación requieren componentes altamente tecnológicos (e.g. sistemas telemáticos e informáticos, inteligencia artificial, procesamiento de imágenes y modelado 3D).

Exploring Hidden Coherent Feature Groups and Temporal Semantics for Multimedia Big Data Analysis

Thanks to the advanced technologies and social networks that allow the data to be widely shared among the Internet, there is an explosion of pervasive multimedia data, generating high demands of multimedia services and applications in various areas for people to easily access and manage multimedia data. Towards such demands, multimedia big data analysis has become an emerging hot topic in both industry and academia, which ranges from basic infrastructure, management, search, and mining to security, privacy, and applications. Within the scope of this dissertation, a multimedia big data analysis framework is proposed for semantic information management and retrieval with a focus on rare event detection in videos. The proposed framework is able to explore hidden semantic feature groups in multimedia data and incorporate temporal semantics, especially for video event detection. First, a hierarchical semantic data representation is presented to alleviate the semantic gap issue, and the Hidden Coherent Feature Group (HCFG) analysis method is proposed to capture the correlation between features and separate the original feature set into semantic groups, seamlessly integrating multimedia data in multiple modalities. Next, an Importance Factor based Temporal Multiple Correspondence Analysis (i.e., IF-TMCA) approach is presented for effective event detection. Specifically, the HCFG algorithm is integrated with the Hierarchical Information Gain Analysis (HIGA) method to generate the Importance Factor (IF) for producing the initial detection results. Then, the TMCA algorithm is proposed to efficiently incorporate temporal semantics for re-ranking and improving the final performance. At last, a sampling-based ensemble learning mechanism is applied to further accommodate the imbalanced datasets. In addition to the multimedia semantic representation and class imbalance problems, lack of organization is another critical issue for multimedia big data analysis. In this framework, an affinity propagation-based summarization method is also proposed to transform the unorganized data into a better structure with clean and well-organized information. The whole framework has been thoroughly evaluated across multiple domains, such as soccer goal event detection and disaster information management.

Compétences en littératie visuelle chez les étudiantEs en biologie au niveau collégial: bilan des apprentissages selon des activités digitales ou des activités de dessins à la main

This study examines the role of visual literacy in learning biology. Biology teachers promote the use of digital images as a learning tool for two reasons: because biology is the most visual of the sciences, and the use of imagery is becoming increasingly important with the advent of bioinformatics; and because studies indicate that this current generation of teenagers have a cognitive structure that is formed through exposure to digital media. On the other hand, there is concern that students are not being exposed enough to the traditional methods of processing biological information - thought to encourage left-brain sequential thinking patterns. Theories of Embodied Cognition point to the importance of hand-drawing for proper assimilation of knowledge, and theories of Multiple Intelligences suggest that some students may learn more easily using traditional pedagogical tools. To test the claim that digital learning tools enhance the acquisition of visual literacy in this generation of biology students, a learning intervention was carried out with 33 students enrolled in an introductory college biology course. The study compared learning outcomes following two types of learning tools. One learning tool was a traditional drawing activity, and the other was an interactive digital activity carried out on a computer. The sample was divided into two random groups, and a crossover design was implemented with two separate interventions. In the first intervention students learned how to draw and label a cell. Group 1 learned the material by computer and Group 2 learned the material by hand-drawing. In the second intervention, students learned how to draw the phases of mitosis, and the two groups were inverted. After each learning activity, students were given a quiz on the material they had learned. Students were also asked to self-evaluate their performance on each quiz, in an attempt to measure their level of metacognition. At the end of the study, they were asked to fill out a questionnaire that was used to measure the level of task engagement the students felt towards the two types of learning activities. In this study, following the first testing phase, the students who learned the material by drawing had a significantly higher average grade on the associated quiz compared to that of those who learned the material by computer. The difference was lost with the second “cross-over” trial. There was no correlation for either group between the grade the students thought they had earned through self-evaluation, and the grade that they received. In terms of different measures of task engagement, there were no significant differences between the two groups. One finding from the study showed a positive correlation between grade and self-reported time spent playing video games, and a negative correlation between grade and self-reported interest in drawing. This study provides little evidence to support claims that the use of digital tools enhances learning, but does provide evidence to support claims that drawing by hand is beneficial for learning biological images. However, the small sample size, limited number and type of learning tasks, and the indirect means of measuring levels of metacognition and task engagement restrict generalisation of these conclusions. Nevertheless, this study indicates that teachers should not use digital learning tools to the exclusion of traditional drawing activities: further studies on the effectiveness of these tools are warranted. Students in this study commented that the computer tool seemed more accurate and detailed - even though the two learning tools carried identical information. Thus there was a mismatch between the perception of the usefulness of computers as a learning tool and the reality, which again points to the need for an objective assessment of their usefulness. Students should be given the opportunity to try out a variety of traditional and digital learning tools in order to address their different learning preferences.

Methods for integrating machine learning and constrained optimization

In the framework of industrial problems, the application of Constrained Optimization is known to have overall very good modeling capability and performance and stands as one of the most powerful, explored, and exploited tool to address prescriptive tasks. The number of applications is huge, ranging from logistics to transportation, packing, production, telecommunication, scheduling, and much more. The main reason behind this success is to be found in the remarkable effort put in the last decades by the OR community to develop realistic models and devise exact or approximate methods to solve the largest variety of constrained or combinatorial optimization problems, together with the spread of computational power and easily accessible OR software and resources. On the other hand, the technological advancements lead to a data wealth never seen before and increasingly push towards methods able to extract useful knowledge from them; among the data-driven methods, Machine Learning techniques appear to be one of the most promising, thanks to its successes in domains like Image Recognition, Natural Language Processes and playing games, but also the amount of research involved. The purpose of the present research is to study how Machine Learning and Constrained Optimization can be used together to achieve systems able to leverage the strengths of both methods: this would open the way to exploiting decades of research on resolution techniques for COPs and constructing models able to adapt and learn from available data. In the first part of this work, we survey the existing techniques and classify them according to the type, method, or scope of the integration; subsequently, we introduce a novel and general algorithm devised to inject knowledge into learning models through constraints, Moving Target. In the last part of the thesis, two applications stemming from real-world projects and done in collaboration with Optit will be presented.