Silvia Margarita Baldiris Navarro

Gremlings in My Mirror: An Inclusive AR-Enriched Videogame for Logical Math Skills Learning

Implications on a simultaneous application of Augmented Reality (AR) and Digital Game Based Learning (DGBL) to inclusive learning have yet to be observed. We designed an AR enriched videogame for Logical Math Skills Learning. Then we tested the game with a set of 20 students with diverse learning needs. Our experiment showed that the performance on the game is similar for kids with different needs. The results and feedback from teaching staff suggest that AR and DGBL allow the integration of children with special needs in the learning process.

Recommending Learning Routes for Heritage Education

Heritage education allows people to understand and take advantage of patrimonial assets. Emerging technologies can offer new and innovative ways for people to learn about their own patrimonial assets. The Framework for Heritage Education supported in emerging technologies gives insights about how to design learning experience and systems to support heritage education. This article describes the method of recommending patrimonial learning routes defined on the Framework for Heritage Education to personalize the learning experience based on the visitor/citizen interests. An evaluation scenario of the method was carried out in the city of Cartagena de Indias – Colombia obtaining promising results.

Indicadores de síntomas ADHD en el contexto de aprendizaje virtual, utilizando técnicas de aprendizaje automático

Rev.esc.adm.neg This paper presents a user model for students performing virtual learning processes. This model is used to infer the presence of Attention Deficit Hyperactivity Disorder (ADHD) indicators in a student. The user model is built considering three user characteristics, which can be also used as variables in different contexts. These variables are: behavioral conduct (BC), executive functions performance (EFP), and emotional state (ES). For inferring the ADHD symptomatic profile of a student and his/her emotional alterations, these features are used as input in a set of classification rules. Based on the testing of the proposed model, training examples are obtained. These examples are used to prepare a classification machine learning algorithm for performing, and improving, the task of profiling a student. The proposed user model can provide the first step to adapt learning resources in e-learning platforms to people with attention problems, specifically, young-adult students with ADHD.