With advances in science and technology, several innovative researches have been developed trying to figure out the main problems related to children's learning. It is known that issues such as frustration and inattention, between others, affect student learning. In this fashion, robotics is an important resource that can be used towards helping to solve these issues, empowering our students in order to push their learning up. In this case, robotic tools are generally used considering two different paradigms: as the main focus and as a secondary focus. Actually, these paradigms define the way that Educational Robotics is implemented in schools. Most of the approaches have implemented it as the main focus, which is teaching Robotics. Nevertheless, there are quite a few works that implement robotics as a secondary focus, which is currently assisting the learning process in several disciplines. The main contribution of this work is a complete three steps methodology for Robotics in Education to guide projects in order to either use it alone or to teach robotics with others topics. Our experiments show the importance of devising a study plan and evaluation method because the process is iterative and could improve the final results. As a novelty, here we have joined and extended our previous works by proposing a new set of methods with guidelines and strategies for applying the educational robotics standard curriculum for kids, named EDUROSC-Kids. We propose several tools that have been developed to organize the learning topics of Robotics for children, including the desired outcomes during the learning process. As said our current approach is divided in three steps (or phases): setting up the environment, defining the project, and performing evaluation. The proposed curriculum organizes robotics contents into five disciplines: Robotics and Society, Mechanics, Electronics, Programming, and Control Theory. Also, it considers a set of topics for each discipline and defines the level of knowledge that is recommended to achieve each group of children based on Bloom's Nomenclature. The contribution on this paper is a crucial step towards linking the general learning process with Educational Robotics approaches. Our methodology is validated by presenting practical experiences with application of EDUROSC-kids and the proposed method with a rubric guidelines into groups of children.

The Content-based image retrieval (CBIR) systems and their application in different areas of development, are current research topics, however many of this systems are likely to fail due to use global features which cannot sufficiently capture the important properties of individual objects [1] because generally a typical query image includes relevant objects (e.g., Eiffel Tower), but also irrelevant image areas (including background). Then recently, many research has focused on region-based techniques that allow the user to specify a particular region of an image and the system will return images with similar regions to the query. For that reason this paper proposes a method of retrieval image based on irregular regions of interest where the user can to select one region. Preliminary experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods.Index Terms-Content based image retrieval CBIR, Region based image retrieval RBIR, regions of interest, Local Features, Global Features. I. INTRODUCCIÓNIn recent years, digital imaging has experienced tremendous growth in the world and it tends to increase exponentially. A way to retrieve this information is through the Content Based Image Retrieval (CBIR) systems, searching images based on a given query image [2]. Although a large amount of research has been developed in this field, the performance in this systems has not yet been successful due to the existence of semantic gap, the gap between the high level textual features and the low level image features is called the semantic gap [3]. In order to solve this semantic gap problem, one of the most popular approaches in recent years is to change the focus from the global content description of images into the local content description by regions (region-based image retrieval) or even the objects in images (object-based image retrieval) [4].Recently many researchers have focused on techniques Region-based [5], [6], namely Region-Based Image Retrieval -RBIR, which applies image segmentation to descompose an image into homogeneous regions based on visual properties. However an semantically-precise image segmentation is extremely difficult so an incorrect segmentation can lead to inadequate representation [1].For that reason this paper proposes a method of regionbased image retrieval without automatic segmentation, using color and texture features on irregular regions of interest, where the color features are obtained by clusterization using kmeans algorithm and the texture features are calculated using Haralick's texture descriptor. Also is impractical to match the queried region with all regions of the database images then an efficient indexing technique is essential then this paper use a binary code to each region in an image which permit to match only the queried region with the closest regions.The rest of this paper is organized as follows. In section 2, the state of the art is presented. The proposed method is presented in the section 3. Experimen...

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