Pedro A. Toledo

Learning healthy lifestyles through active videogames, motor games and the gamification of educational activities

The World Health Organization (WHO) has declared obesity as a 21st-century epidemic after reaching global proportions. In Spain, this disease is suffered by 62% of the population, leading to the emergence of new health problems. Increasing childhood obesity in the world is a direct result of changes in the lifestyles of the population. Therefore, in this paper we present a gamification training program to prevent childhood obesity based on motor games, and active videogames developed for overweight children ages 8-12. The design of the program consisted of: group sessions in a school setting, individual sessions at home for the children, and developing healthy habits to help families. The motivation and the effectiveness of the gamification training program were studied. The results involving biometric variables, learning healthy habits and experience in the intervention were highly satisfactory. We design a training program based on a GBL and gamification approaches.We work in formal and informal contexts (school and home) as informal learning.We present a cuasi-experimental study developed with children from 8 to 12 years old.We analyze the experience from different dimensions (medical, learning and UX).

Gamification in intelligent tutoring systems

Gamification is the use of game mechanics and strategies in nongame contexts. Currently, according to various reports, is an emerging trend in many application fields, including education. It seeks to encourage people, behavior change and improve troubleshooting. Furthermore, mobile and ubiquitous learning make possible to extend the teaching-learning beyond formal contexts such as classrooms. Moreover, while the intelligent tutoring systems have been shown to improve student achievement and enhance learning, they still have major problems in their use and need further investigation. Among them, one of the main problems found is the inappropriate use of these systems by the students, perhaps due to boredom, lack of interest or motivation and monotony, which among other factors, cause the student to behave incorrectly when interacting with these kind systems. For this reason, in this paper we present a conceptual architecture proposal for an Intelligent Tutorial System (ITS) known as EMATIC (Mathematics Education through ICT) that includes gamification elements as key components of the system.

Using an induced relational decision tree for rule injection in a learning classifier system

Transfer learning, using systems with rich and general representations, to improve adaptive rule based systems designed to efficiently react in changing environments is the idea behind the problem studied in this paper. In this framework, the aim of this research is studying the benefits of using relational learning in combination with an evolutionary propositional learning system as XCS. The proposed method starts by learning a first order relational decission tree using a set of simplified instances of a problem. The learned relational model is then used to help a learning classifier system to deal with a more complex instance of the task. The researched strategy is based on injecting rules derived from the relational model in the discovering subsystem of the XCS. Results show that this method can be used to automatically adapt the behaviour of a learning rule based system when the environment increases its complexity.

TANGO:H: Creating Active Educational Games for Hospitalized Children

This paper presents an interactive platform called TANGO:H (Tangible Goals: Health) for the creation of social active play with gestural interaction. This platform has been specially designed and adapted for its recreational, educational and rehabilitation use in children at hospital. The platform has a game editor called TANGO:H Designer, which allows the creation of physical and cognitive exercises in single and multiplayer, so that children can play sequentially or simultaneously both competitively and collaboratively. Similarly, the design of the platform was taken into account various criteria of playability and gamification to maximize the user experience with the game. This article presents the requirements that have been followed in the design of Tango-H, and the developed solution.

Inclusive educational software design with agile approach

In this paper we present a proposal of inclusive educational software design based on principles of user-centered design (UCD), user experience design (UXD) and agile methodologies (SCRUM). The main goal of this proposal is to identify usability problems and UX factors in early stages of educational software development for users with special educational needs. Furthermore, we also present a User Interface (UI) design and its evaluation conducted with experts and students. This UI evaluation has been divided in several phases, using diverse methods with different actors. Prototyping and usability heuristics are presented as a fast and cost-efficient but still effective and accurate evaluation method for user experience with educational software.

A laboratory experiment for teaching automation inspired by the smart home

This paper presents a laboratory experiment for teaching Automation. The objective of this project is to allow the students of the Technical Engineering Schools of the University of La Laguna (Spain) to learn the theoretical and practical fundamentals of Automation Systems through a laboratory experiment based on a home automation application. Automation plays an increasingly important role in the centred of Engineering; as a result, several subjects in the curriculum plan at the Engineering School focus on this discipline. In recent years, our teaching efforts have been centred on designing appealing and modern laboratory experiments. With these practical experiments, students acquire a basic knowledge of Automation, along with complementary knowledge of the latest developments in the field. The laboratory session presented in this article draws its inspiration from the Smart Home, a recent field in applied Automation. Due to the impossibility of carrying out the control of a smart installation in a real house, a simulation experiment was designed for educational tasks. A scale model of a house was built, and all the sensors, the actuators and the control system were adapted to this scale model. A Programmable Logic Controller was selected as the control system.

EMATIC: an inclusive educational application for tablets

EMATIC project (Mathematics Education through ICT) is a multi-device Intelligent Tutorial System (ITS) focused on the teaching of mathematics, especially for children with educational difficulties. Logical thinking and learning different aspects of basic math are the main learning goals of EMATIC. Also, EMATIC allows students to perform non-repetitively the same type of exercise, making the process of learning something as dynamic and entertaining as if it were a game. This paper examines key issues to support students with special education needs (SEN) in their learning of math, involving the interaction design and usability of the applications interface. The research goals include the identification of the main interaction difficulties and the improvement of the interaction design to get a better suit to these groups of users.

Gamified Platform for Physical and Cognitive Rehabilitation

In this paper is described the design and development of a KINECT based interactive platform application aimed to physical rehabilitation and cognitive training of the minors in situations of illness. This platform, called TANGO:H, is highly configurable and customizable, thanks to exercises editor: TANGO:H Designer. So, the platform allows the adaptation of exercises and activities according to the specific characteristics of each user and user group.

Guiding a relational learning agent with a learning classifier system

This paper researches a collaborative strategy between an XCS learning classifier system (LCS) and a relational learning (RL) agent. The problem here is to learn a relational policy for a stochastic markovian decision process. In the proposed method the XCS agent is used to improve the performance of the RL agent by filtering the samples used at the induction step. This research shows that in these conditions, one of the main benefits of using the XCS algorithm comes from selecting the examples for relational learning using an estimation for the accuracy of the predicted value at each state-action pair. This kind of transfer learning is important because the characteristics of both agents are complementary: the RL agent incrementally induces a high level description of a policy, while the LCS agent offers adaptation to changes in the environment.