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Computational Thinking is a competence that is developed more in the last few years. This is due to the multitude of benefits it has in the classroom. Throughout this article we show a series of activities that promote the development of Computational Thinking using tools that allow visual block programming. The particularity of these activities is that some of them were performed during the confinement due to the COVID-19 and other activities were performed later, in the period known as the new normality. Throughout the article, details are provided about the different sessions. The different visual programming tools by blocks and the educational scenarios used are also indicated. In addition, the results obtained are shown.

In this paper a model to track learning experiences from an interactive e-book is presented. For this a digital book coherent with the EPUB3 standards has been made by exporting an existing course in a learning management system and replicating its interactive behavior. Defining trigger points throughout the book and amongst the interactions made by the students, that send data to a learning record store, enrich the e-book and provide the possibility to analyze and preview statistical data for students’ commitment to learning the material and their actions over the whole course. The xAPI specification helps collect educational data and store it in a database, which can be used for creating a further set of reports anytime in the future.

Tau protein neurofibrillary tangles (NFT) are linked to neuronal and synaptic loss and cognitive decline in Alzheimer's disease (AD) and related dementias. In AD, NFT pathology is known to spread through the cortex in a characteristic pattern, starting in the medial temporal lobe. However, the exact 3D pattern of NFT progression has not been described, and capturing this pattern quantitatively can help inform in vivo AD imaging biomarkers. We present a computational framework for generating 3D maps of NFT load from ex vivo MRI and serial histology. Weakly supervised deep learning is used to detect NFTs on histology slides prepared with an anti-tau immunohistochemistry stain, and a multi-stage registration pipeline that leverages 3D printing is used for histology-MRI alignment. Derived maps of NFT density are strongly concordant with manual NFT counting, as well as categorical NFT severity ratings used for clinical diagnosis.

Earliest neuropathological changes in Alzheimer's Disease (AD) emerge in the medial temporal lobe (MTL). In order for MRI biomarkers to detect changes linked specifically to AD pathology (as opposed to aging or other pathological factors) macroscopic patterns of structural change in the MTL must be linked to the underlying neuropathology. To provide such a linkage, we are conducting an autopsy imaging study combining ex vivo MRI and serial histopathology. Information from multiple subjects can be studied by creating a “population average” atlas of the MTL. We present a groupwise registration approach for constructing the atlas that is able to successfully capture the complex structure of the MTL, and anatomical variability across subjects. This atlas allows us to generate maps of cortical thickness measurements and identify regions in the MTL where structural changes correlate most strongly with AD progression. We show that using this atlas, we are able to find a significant correlation between atrophy and AD pathology in the MTL sub-regions associated with the earliest stages of AD pathology as described by Braak and Braak [1].

This study analyzes a gamification experience in a Network Security Management subject of an Information Technology Engineering degree to evaluate whether the spaced-education methodology contributes to the learning improvement. The gamification experience is carried out by an automatic daily delivery of technical questions to students by e-mail.

In the process of searching for open educational resources, the use of ontologies is a key aspect in the reusability of resources for instructional purposes. In this paper, we address the issue of automatic tagging and classifying open educational resources by means of text mining techniques. The purpose is to set up a semantic framework in order to be used in the process of authoring educational material. Thus, authoring can be turned from a simple aggregation process into a dynamic and automatic selection of appropriate resources based on instructional needs and learning design.

This paper presents the main results achieved in the program eMadrid Program in Open Educational Resources, Free Software, Open Data, and about formats and standardization of content and services. © 2016 IEEE.

This article describes in detail the main achievements in authoring and reuse of educational materials within the eMadrid project.

The arrival of new electronic devices and high-speed Internet connections have provoked a revolution on the Web design, introducing new concepts as responsive web and OneWeb. Web developments should be able to adapt to any device. Applying these concepts it has been created a web application called "Formulas App", which is a perfect complement for enriching learning scenarios, mainly dictated to science fields such as physics, mathematics or electronics. Such application provides added value to virtual and remote laboratories, PDF files, videos or education tools, such as quizzes, forums or chats. In addition all of them could be integrated inside Learning Management Systems (LMS) and Personal Learning Environment (PLE) and create complete and efficient learning scenarios, scaffoldings.

Universities and educational organizations or institutions, when designing any electronics course, trust in experimentation through laboratory practices in order to build successful cross-curricular capabilities and capacities. In electronics courses there is a need to have practical experiences, the benefits of electronics laboratory practices are widely known for professionals and necessary for any person who seeks for a broad comprehension of the real-time performance beyond the ideal modelling. Therefore, when designing any electronics course, the laboratory practices are one of the pillars on which the learning is established. Distance education has become widespread in the last decade and has fostered lifelong learning and continuing education patterns, allowing access to learning resources at any time and from everywhere. It has been possible thanks to the internet development and technologies associated with learning tools for a new teaching pedagogy. To support life-long learning and students' autonomous learning activities, remote experimentation has become a challenge in electronics courses; rather, the way the universities and educational organizations or institutions deliver remote experimentation to students in distance learning environments, has become a challenge. Nowadays, there is an extensive variety for providing theoretical contents in distance learning (videos, documents, tutorials, scaffolding activities, peer-to-peer reviews, forums, etc.) to students. These tools, by an efficiently and appropriate selection from professors and use from students, can complement or replace successfully in-person education, even they can reach some aspects that in-person education cannot achieve. Unfortunately, practical issues are not as developed as theoretical ones are. A first approach to this problem is clearly the use of simulators and virtual labs. Although, they are still a bit far from providing to student the real performance and features of equipment under real-life operation conditions. The major challenge is the provision of laboratory working online along with the theoretical contents in a massive context.

This paper presents a new educational system to automatically adapt the evaluation activities to the students' needs in the context of Higher Engineering Education. As an example, a subject focused on the configuration of network services has been chosen to implement our proposal. Therefore, the system will be able to guide each student through the learning process based on his/her particular knowledge-level. In addition to this, specific techniques are needed to dynamically evolve the system depending on the students' progress. In our case, this is analyzed by using data mining techniques. Finally, we show survey results, which illustrate the ease of use and usefulness of the system.

Assessment and evaluation of students' performance has always played an important role in the learning process as it provides information about the level of knowledge acquired on a subject, and the progress that has been achieved. However, another main issue is detecting the thematic core in which the students have learning problems because they are evaluated in terms of competencies. This study proposes an adaptive approach to diagnose and feedback students, and makes use of the Item Response Theory to estimate skill levels and classify the students. In addition, it uses a model of concepts' relationship between the concepts and the items of the test. The purpose is to diagnose students' cognitive problems and provide personalized and intelligent learning suggestions. This approach can be used as a system of intelligent diagnosis that receives a set of responses, and generates a data set of weak concepts for each student, specifying their learning path and resulting in clustering individuals who share the same shortcomings to ease any process of group feedback.

Merging a Learning Management System (LMS) and a social network has social advantages for students. Among others, students can show off their achievements among their acquaintances, which in turn improves their social leadership and self-esteem. This is specially true in the case of distance learning, where there are no physical interactions between students, so their student life is totally isolated from their everyday life (e.g. students do not go out together, since they may live in different cities or even countries although they study the same subjects). All these points suggest that the use of social networks for distance teaching has clear advantages that can be harnessed. In order to achieve the aforementioned benefits, we are working on integrating a commonly used LMS, Moodle, into one of the most widely-used social network, Facebook. This integration allows students and faculty to use Facebook as a communication tool that improves the learning process and social life of students in the ways presented before.

Mobile learning is impacting education using different technologies and methodologies. This article introduces two relevant learning experiences at UNED where new mobile technologies and pedagogical methodologies were applied. The first experience was based on a ubiquitous annotation system, while the second one used augmented reality to create an engaging mobile collaborative and open environment where students were learners and teachers at the same time, publishing content and learning from the content published by other peers.

This paper shows an approach to build communities of students working collaboratively to create educational content. We present an evaluation of the usability of a customized semantic environment and show how it interacts with a semantic wiki-based approach. Additionally, a proposal for a manageable hybrid methodology for the creation of ontologies is given. The result is a tool: OntoWikiUTPL and SemanticWikiUTPL, which allows the academic community to create semantic content. Thus, it is an interesting step toward innovation in interactive educational projects and collaborative activities in the Universidad Tecnica Particular de Loja (UTPL).

Concept maps are commonly used as knowledge representation mechanisms to classify a given domain in the scope of a constructivist knowledge building process. In this paper we carry out social constructivist learning experiences using concept maps as a collaborative knowledge-sharing tool with applications in the coordination of virtual communities for learning. In our experiment, the community studies an environmental area-theoretically and in-situ, collects data from a variety of experiments and makes a representation of it. Then, they build a common concept map representing their understanding of this area using a set of tools developed ad-hoc and integrated by a metamodel wrapping approach. Finally, they complete it linking their node with the collected information as a way to organize and to navigate through the different pieces of knowledge that they have been accumulating during several fieldtrips.

The optimization process in intensity-modulated radiation therapy (IMRT) is closely related to an inverse problem and is therefore ill-conditioned. Besides, it is a computationally complex and intensive task, leading to numerical instabilities and solutions sensitive to high-frequency perturbations. For these reasons, a regularizer is needed for smoothing the intensity maps generated, thus removing the unwanted noise. However, regularization has to be performed taking into account the physical meaning of the solution, i.e., the delivery of radiation. In this work, we propose a new term within the objective function, which uses a discrete Laplacian filter adapted to each position for excluding the inactive neighbours that do not radiate a tumour. The term was tested in six cancer cases and the results show that the final decomposition of the maps for delivering the treatment are improved in terms of the number of segments and total number of monitor units, thus reducing the treatment time, while the quality of the solution is equivalent to the original.

This paper proposes an agent-based adaptive Architecture to extend Moodle in order to support instructional decisions and adaptive behaviour in engineering education. The paper describes the characteristics, functions, and interactions of the agents which take part in each module of the adaptive architecture. In addition, we describe the origin and function of ToDei, the proposed intelligent agent for Instructional Decisions Making. This agent is in charge of collecting information generated by the rest of agents and deciding what is best for the final users, tutors and students, taking into account their attitudes towards the learning environment. © 2010 IEEE.

In the last years, authoring based on e-learning standards has been consolidated as a core factor of industry and development of interoperable and effective virtual learning environments. However, there is a need for further research on abstraction to provide a more instructional view in the context of authoring tools in a variety of ways, in order to avoid being driven by Learning Technology (LT) specifications, facilitate instructional knowledge aggregation, and to provide an appropriate level of clarity and semantics in the design of collaborative activities. We propose a combination of techniques to provide this instructional abstraction in the context of the new European educational model, combining instructional layers and collaborative scripts in authoring tools, and semantic web techniques for extending e-learning material in order to harness the wealth of existing web content and semantically labeled repositories.

In the context of the authoring process of educational material in e-learning, the notion of learning specification has been considered the fundamental step for the development of an e-learning industry, based on reusability and interoperability of interchangeable components. However, when considering authoring based on instructional and pedagogical aspects, it is necessary to avoid being driven by LT specifications, and better rely on an abstract reference model based on instructional semantics. This paper proposes this instructional layer stack to provide independence from content specification in the authoring process and develop an authoring tool based on it with exporting capabilities to IMS specifications.

Intensity modulated radiotherapy is a technique used in the treatment of cancer based on the use of different spatially distributed X-Ray beams. The task of treatment planning is to determine the dose quantity that each beam of radiation should deliver, and for each spatial direction, and so determining a specific dosage distribution for the patient. In this paper a conditional optimization problem is studied, proposing a new reduction method for the dimensions of this problem. The procedure proposed has been used in the planning of the treatment for a real case of prostate cancer, where satisfactory results have been obtained.

The Intensity Modulated Radiotherapy (IMRT) is a technique currently under development for the treatment of carcinogenic tumours, whose main objective is to concentrate the radiation dose in the tumour limiting the dose received by adjacent healthy tissue. The treatment by means of IMRT uses a discreet set of spatially distributed beams of radiation. Habitually, the radiation beams are placed separated with a fixed distance in the space around the patient, although sometimes the radiotherapist sets their position based on his own experience. In this article a new method is offered to determine the optimal position of the radiation beams, in such a way that the geometry of the patient is considered and the required dose in the different organs. The selection of positions is based on the study of a Figure of Merit (FoM), that allows the dose to be evaluated that the patient will receive. The proposed method has been applied on a real case of cancer, where the results obtained demonstrate a greater effectiveness in the treatments when considering the positioning of the beams according to the proposed method.