Mariano Luis Alcañiz Raya

Learning in serious virtual worlds: Evaluation of learning effectiveness and appeal to students in the E-Junior project

The objective of this study is to present and to evaluate the E-Junior application: a serious virtual world (SVW) for teaching children natural science and ecology. E-Junior was designed according to pedagogical theories and curricular objectives to help children learn about the Mediterranean Sea and its environmental issues while playing. In this study, we present data about the E-Junior evaluation. A class in a serious virtual world (virtual group) was compared with a traditional type of class (traditional group) that contained identical learning objectives and contents but lacked a gaming aspect. Data collection consisted of quantitative and qualitative measures on a sample of 48 children. With regards to learning effectiveness, the results showed that the serious virtual world does not present statistically significant differences with the traditional type of class. However, students from the virtual group reported enjoying the class more, being more engaged, and having greater intentions to participate than students from the traditional group. The plausible explanation for this can be found in the qualitative data. The implications of these results and improvement proposals are also discussed in this work.

A Comparison of Physiological Signal Analysis Techniques and Classifiers for Automatic Emotional Evaluation of Audiovisual Contents

This work focuses on finding the most discriminatory or representative features that allow to classify commercials according to negative, neutral and positive effectiveness based on the Ace Score index. For this purpose, an experiment involving forty-seven participants was carried out. In this experiment electroencephalography (EEG), electrocardiography (ECG), Galvanic Skin Response (GSR) and respiration data were acquired while subjects were watching a 30-min audiovisual content. This content was composed by a submarine documentary and nine commercials (one of them the ad under evaluation). After the signal pre-processing, four sets of features were extracted from the physiological signals using different state-of-the-art metrics. These features computed in time and frequency domains are the inputs to several basic and advanced classifiers. An average of 89.76% of the instances was correctly classified according to the Ace Score index. The best results were obtained by a classifier consisting of a combination between AdaBoost and Random Forest with automatic selection of features. The selected features were those extracted from GSR and HRV signals. These results are promising in the audiovisual content evaluation field by means of physiological signal processing.

Hierarchical image segmentation using a correspondence with a tree model

A new general image segmentation system is presented, based on the calculation of a tree representation of the original image in which image regions are assigned to tree nodes, followed by a correspondence process with a model tree, which embeds the a priori knowledge about the images. For this correspondence, an original algorithm is proposed, which performs the minimization of an error function that quantifies the difference between the input image tree and the model tree. We also present a new algorithm for automatically calculating the model tree from a set of manually segmented images. Results on synthetic and MR brain images are presented.

HumanTop: a multi-object tracking tabletop

In this paper, a computer vision based interactive multi-touch tabletop system called HumanTop is introduced. HumanTop implements a stereo camera vision subsystem which allows not only an accurate fingertip tracking algorithm but also a precise touch-over-the-working surface detection method. Based on a pair of visible spectra cameras, a novel synchronization circuit makes the camera caption and the image projection independent from each other, providing the minimum basis for the development of computer vision analysis based on visible spectrum cameras without any interference coming from the projector. The assembly of both cameras and the synchronization circuit is not only capable of performing an ad-hoc version of a depth camera, but it also introduces the recognition and tracking of textured planar objects, even when contents are projected over them. On the other hand HumanTop supports the tracking of sheets of paper and ID-code markers. This set of features makes the HumanTop a comprehensive, intuitive and versatile augmented tabletop that provides multitouch interaction with projective augmented reality on any flat surface. As an example to exploit all the capabilities of HumanTop, an educational application has been developed using an augmented book as a launcher to different didactic contents. A pilot study in which 28 fifth graders participated is presented. Results about efficiency, usability/satisfaction and motivation are provided. These results suggest that HumanTop is an interesting platform for the development of educational contents.

Consumer Neuroscience-Based Metrics Predict Recall, Liking and Viewing Rates in Online Advertising

The purpose of the present study is to investigate whether the effectiveness of a new ad on digital channels (YouTube) can be predicted by using neural networks and neuroscience-based metrics (brain response, heart rate variability and eye tracking). Neurophysiological records from 35 participants were exposed to 8 relevant TV Super Bowl commercials. Correlations between neurophysiological-based metrics, ad recall, ad liking, the ACE metrix score and the number of views on YouTube during a year were investigated. Our findings suggest a significant correlation between neuroscience metrics and self-reported of ad effectiveness and the direct number of views on the YouTube channel. In addition, and using an artificial neural network based on neuroscience metrics, the model classifies (82.9% of average accuracy) and estimate the number of online views (mean error of 0.199). The results highlight the validity of neuromarketing-based techniques for predicting the success of advertising responses. Practitioners can consider the proposed methodology at the design stages of advertising content, thus enhancing advertising effectiveness. The study pioneers the use of neurophysiological methods in predicting advertising success in a digital context. This is the first article that has examined whether these measures could actually be used for predicting views for advertising on YouTube.

E-Junior: a serious virtual world for natural science and ecology learning

The objective of this study is to present the E-Junior application: a serious virtual world (SVW) for teaching children natural science and ecology. E-Junior was designed according to pedagogical theories and curricular objectives in order to help students learn about the Mediterranean Sea and its ecological issues while playing. In this paper, we present the technical description of E-Junior and its pedagogical and curricular foundations.

A Novel Integrating Virtual Reality Approach for the Assessment of the Attachment Behavioral System

Virtual reality (VR) technology represents a novel and powerful tool for behavioral research in psychological assessment. VR provides simulated experiences able to create the sensation of undergoing real situations. Users become active participants in the virtual environment seeing, hearing, feeling, and actuating as if they were in the real world. Currently, the most psychological VR applications concern the treatment of various mental disorders but not the assessment, that it is mainly based on paper and pencil tests. The observation of behaviors is costly, labor-intensive, and it is hard to create social situations in laboratory settings, even if the observation of actual behaviors could be particularly informative. In this framework, social stressful experiences can activate various behaviors of attachment for a significant person that can help to control and soothe them to promote individual’s well-being. Social support seeking, physical proximity, and positive and negative behaviors represent the main attachment behaviors that people can carry out during experiences of distress. We proposed VR as a novel integrating approach to measure real attachment behaviors. The first studies on attachment behavioral system by VR showed the potentiality of this approach. To improve the assessment during the VR experience, we proposed virtual stealth assessment (VSA) as a new method. VSA could represent a valid and novel technique to measure various psychological attributes in real-time during the virtual experience. The possible use of this method in psychology could be to generate a more complete, exhaustive, and accurate individual’s psychological evaluation.

Virtual representations of the self: engaging teenagers in emotional regulation strategies learning

The aim of this paper is to present digital representations of humans (i.e., avatars) that look like the self, applied to the Mental Health (MH) field. Virtual Representations of the Self (VRS) are in our opinion a tool with a great potential for engaging teenagers in emotional regulation strategies learning and an excellent example of new technology application to the basic concept in psychology field such as Banduras modeling [1]. VRSs have already demonstrated their potential on human behavior modification (e.g. modification of physical activity; eating habits) in general population [2]. Thus, the same technology can bring in our opinion a lot to the Mental Health field, especially in emotional regulation learning. This paper presents a theoretical background and describes the methodology that we plan to apply in order to validate the efficacy of VRSs in clinical settings. Also, the implications of such technology and future research lines are discussed.

Balance recovery through virtual stepping exercises using Kinect skeleton tracking: a follow-up study

Stroke patients often suffer from hemiparesis, which affects their balance condition and consequently their self-dependency and quality of life. Balance rehabilitation can be a long and tedious process. Virtual rehabilitation systems have been reported to provide therapeutic benefits to the balance recovery of stroke patients while increasing their motivation. This paper presents a follow-up study involving chronic stroke patients to evaluate the clinical effectiveness of a virtual stepping exercise using skeleton tracking through a low-cost Kinect depth sensor.

Individuals’ Variables in Cognitive Abilities Using a Narrative Serious Game

Age, gender, and education represent crucial variables in the assessment and interpretation of traditional neuropsychological measures as regards the executive functions (EF). Currently, traditional measures are showing limitations in capturing real life behaviors and new technologies, such as serious games, are allowing creating more real situations with higher ecological validity. In the present study, we applied a serious game approach to investigate individual variables-related differences in the EF assessment. 268 healthy subjects participated in the study, completing 14 tasks (6 standard tasks; 8 serious games) randomly presented. The results showed that younger participants completed tasks in less time than older and with higher correct answers. Furthermore, males registered shorter reaction times, while females showed higher percentages of correct answers. The university studies group obtained higher total score and correct answers than high school studies group. Finally, since the study involved technology, we divided the group in high and low use technology level, obtaining that participants with a lower level of use technologies reported higher latency times and lower correct answers in high order EF tasks than the group with higher level of use of technology. As the traditional measure, these findings suggest that individuals’ differences are critical variables to consider in the development of more ecological measures for the assessment of EFs.