Javier Alejandro Corredor

Deciding on optimal assistance policies in haptic shared control tasks

This paper presents a haptic assistant that enhances task performance and human-machine interaction via a gain-scheduled impedance controller. The assistance strategy proposed builds on decision-making studies and models first proposed in the field of cognitive science and combines these models with a gain-scheduled impedance control technique in order to enhance human machine interaction in a tracking task with environmental uncertainties. This paper explores the Drift-Diffusion Model as decision making model and proposes an adaptive impedance control strategy that enhances both, task performance and human-machine interaction.

Shared control based on roles for telerobotic systems

The classic approach to teleoperation system design seeks to augment human capabilities and allow the execution fo tasks in a remote (possible hazardous) environment. Recent developments have provided robotic systems with additional autonomy, thus allowing the possibility of having collaboration between humans and robots in local scenarios. This paper presents preliminary ideas where the concept of human-robot collaboration is extended to the area of robotic systems operated remotely. Thanks to the studies made to ascertain how humans interact when performing physical tasks in a collaborative manner, it is possible to use such concepts to study human-robot interactions and create more trasnparent teleoperation systems. The idea of using role-based strategies to perform tasks via remote robotic interfaces is explored, where different interaction models are analysed via the observation of how the “role” of the interacting agents evolves as the task is being perfromed. Additionally, the paper presents some of the research areas that have provided the basis of the proposed approach, as well as the main challenges for the application of such teleoperation system. It is noteworthy to mention that one of the main challenges is to provide the system with adaptive and learning strategies that allow the agents to dynamically specialize and provide a more natural human-robot interaction.

Narrative and Conceptual Expertise in Massively Multiplayer Online Role Playing Games

This article aims at investigating the differences among three groups having distinct levels of experience in massively multiplayer online role-playing games MMORPG, when solving a character design task in the videogame World of Warcraft WoW, and when planning how to use the character during gameplay. These groups consisted of inexperienced players, general experts in MMORPGs and specialized WoW domain experts. The evaluation showed that MMORPG experience developed character design abilities that could be applied to other videogames e.g., general expertise skills. Such skills were related to the ability to identify deep features related to particular types of characters e.g., Rogue. The results also showed that there are domain expertise specific abilities, which only experts in WoW have. Such abilities were related to building game descriptions that could be considered narrative in the cognitive sense of the term, because they include time, intention and interaction, and also to identifying WoW-specific variables.

Learning, Reasoning and Modeling in Social Gaming

In the last two years, the introduction of social gaming - playing video games in the context of social media - has created new possibilities for playing and learning. Social games attract a huge base of players that represents a different demographic than traditional video games. For this reason, it is worth asking whether or not they can be used for educational purposes. This paper examines the comments made on a single article within a wiki devoted to the characteristics of the Facebook-based social game FarmVille. In order to identify whether or not there is any evidence of learning or knowledge-construction around the game, this study explores and analyzes the conversations around the wiki article. Such evidence is reviewed with the goal of identifying the educational potential of social gaming in general, and FarmVille in particular.

Decision-Making Model for Adaptive Impedance Control of Teleoperation Systems

This paper presents a haptic assistance strategy for teleoperation that makes a task and situation-specific compromise between improving tracking performance or human-machine interaction in partially structured environments via the scheduling of the parameters of an admittance controller. The proposed assistance strategy builds on decision-making models and combines one of them with impedance control techniques that are standard in bilateral teleoperation systems. Even though several decision-making models have been proposed in cognitive science, their application to assisted teleoperation and assisted robotics has hardly been explored yet. Experimental data supports the Drift-Diffusion model as a suitable scheduling strategy for haptic shared control, in which the assistance mechanism can be adapted via the parameters of reward functions. Guidelines to tune the decision making model are presented. The influence of the reward structure on the realized haptic assistances is evaluated in a user study and results are compared to the no assistance and human assistance case.

Fostering Situated Conversation Through Game Play

Background. Prior research suggests that video games function as spaces for informal interaction. In this way, they foster spontaneous conversation that supports gameplay. Such conversation can facilitate learning. In particular, conversations that connect gameplay with the learning materials have positive effects on learning. In this article, those conversations are called situated conversations and used as an important concept to understand video games as educational tools. Aim. This study explores the conversations produced in educational activities supported by video games and the effects of these conversations on the learning of subject matter. Method. This randomized design experiment compares the conversations of a group of students using traditional text-based learning materials with the conversations of a group of students using an educational video game, during a four week intervention focused on the viral-replication process. In both conditions, spontaneous conversation among students was allowed and registered, and learning was assessed using a think-aloud task at the end of the intervention. Results. Students using the video game produced high-quality conversations focused on disciplinary content. The results show, additionally, that only conversations connecting different resources in the learning setting had a significant effect on learning, highlighting the importance of situated conversations for video game learning. Conclusions. The concept of situated conversation is proposed to characterize conversations that connect different resources available in the social environment. This type of conversation increases knowledge levels by bringing external information into the learning process.

Historical memory education for peace and justice: definition of a field

Abstract This article proposes a new of field of research in social sciences education: Historical Memory Education (HME). Despite the large amount of educational experiences following the end of violent conflicts and totalitarian regimes during the twentieth century, historical memory has not been recognized as a field in educational research. From a review of research and experiences worldwide, the authors identify a new field in education research that cannot be reduced to peace education, bullying prevention, or history education, but that takes elements from all these fields, as well as from local pedagogical experiences, to face the challenge of healing the wounds of longstanding violent conflicts. This article organizes prior research in a comprehensive framework that describes the levels, pedagogical principles, and spaces of HME.