(Una Herramienta Software de Emulación para la Mejora del Aprendizaje de Convertidores CC-CC)
Authors:
Ferreiro, Alfonso Lago and Simón, Ana Rey-Alvite and Casas, Sergio Lamas
Abstract:
Power electronics disciplines involve different fundamental topics and technologies. The use of the Internet facilitates and supports the transmission of the theoretical concepts of the teacher to the student and improve the sequence of activities within the available time. The main goal of this work is to develop an emulator software tool to facilitate the usage of control loop fundamentals when applied to DC-to-DC converters. This emulator is a very solid tool for the educational community, and it allows students to analyze and design control circuits in a very flexible way. This resource is available online without time restrictions, allowing users to choose where and when they can learn and interact with the tool which offers a variety of different DC-DC converters, compensation networks and feedback topologies. Once the selection has been made and the different values of the components have been established, a frequency response analysis is shown. The development of the software tool can be operated using any modern browser under any platform and device. The effectiveness of the presented emulator software tool was assessed with the feedback obtained for the students and the results obtained therefor.
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Authors:
Talavera, Alvaro and Luna, Ana
Abstract:
In this work, we integrate computational techniques based on machine learning (ML) and computational intelligence (CI) to conventional methodologies used in the Operational Research (OR) degree course for Engineers. That synergy between those techniques and methods allows students to deal with decision-making complex problems. The primary goals of this research work are to present potential interactions between the two computational fields and show some examples of them. This is a contribution to engineering education research where we present how ML techniques, such as neural networks, fuzzy logic, and reinforcement learning are integrated through applications in an OR course, being able to increase the approach of more complex problems in a simpler way compared to traditional OR methods. The current paper is a different proposal for OR courses that uses the symbiosis between mathematical models employing computer simulations, CI and different hybrid models.
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(Patrones de Aplicaciones Educativas sobre Dislexia en Alumnos de Educación Básica)
Authors:
Muñoz-Arteaga, Jaime
Abstract:
Dyslexia is one of the learning disabilities frequently manifested at elementary school, and then teachers require to identify extra educative resources, in particular, educational applications are useful. This work preconizes the educational patterns as best practices to use these kinds of interactive applications. In addition, a simple and an effective procedure is proposed to obtain some educational patterns for dyslexia considering pedagogical as well as technological aspects. the proposed procedure is applied to obtain a classification of educational patterns considering dyslexia in pupils at elementary school. Several educational patterns are specified in detail. Finally, the current proposal is compared versus related work and a case study is presented.
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(Predicción Temprana del Abandono y Desempeño en el Examen Final en una Asignatura de Estadística en Línea)
Authors:
Figueroa-Cañas, Josep and Sancho-Vinuesa, Teresa
Abstract:
Higher education students who either do not complete the courses they have enrolled on or interrupt their studies indefinitely remain a major concern for practitioners and researchers. Within each course, early prediction of student dropout helps teachers to intervene in time to reduce dropout rates. Early prediction of course achievement helps teachers suggest new learning materials aimed at preventing at-risk students from failing or not completing the course. Several machine learning techniques have been used to classify or predict at-risk students, including tree-based methods, which, though not the best performers, are easy to interpret. This study presents two procedures for identifying at-risk students (dropout-prone and non-achievers) early on in an online university statistics course. These enable us to understand how classifiers work. We found that student dropout and course performance prediction was only determined by their performance in the first half of the formative quizzes. Nevertheless, other elements of participation on the virtual campus were initially considered. The classifiers will serve as a reference for intervention, despite their moderate performance metrics.
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(Processo de Aprendizagem da Metodologia Ágil Scrum com Blocos de Lego em Jogos Acadêmicos Interativos: Ponto de Vista dos Estudantes)
Authors:
Barcelos Bica, Douglas Augusto and Silva, Carlos Alexandre Gouvea da
Abstract:
The rapid growth of Information Technology led to the development of a multitude of smartphone systems worldwide. As a result, the number of educational institutions offering courses in areas such as programming and software engineering increased. However, traditional processes for software development did not keep pace with changing technologies. In the last few years, software development became more dynamic and iterative, requiring stakeholders to work as a team and deliver higher quality projects in less time, by using methods such as Agile Development (e.g., Scrum and Extreme Programming (XP)). Although some institutions approach this content in graduation courses, many students and professor are indifferent towards it, resulting in low enthusiasm and practice. This article presents the real case of a classroom activity to teach Scrum concepts by using Lego blocks. At the end of the classes, students were asked to rate the effectiveness of the activity. The results showed that dynamic games and palpable activities are more effective than theoretical or video lessons.
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(Experiencia de laboratorio virtual mejorada para el aprendizaje de planificacion de redes inalámbricas)
Authors:
Zapata-Rivera, Luis Felipe and Aranzazu-Suescun, Catalina
Abstract:
Online education is benefiting from advanced digital resources that now can offer interactive activities. Videos, animations, virtual and remote laboratories, and online games are just some examples of these activities. Educational standards and Virtual Learning Environments VLEs allow the integration of all these materials into learning objects that can be deployed in online courses or MOOCs. Virtual Laboratories provide an opportunity to train students and give to them the confidence for future interactions with real laboratory settings, with advantages such as: cost, portability, concurrency, and safety. Educational video games can improve the students' knowledge acquisition and develop abilities such as: mental speed, reaction, connection between thoughts and movements and concentration. This paper shows the implementation of a virtual laboratory learning experience that includes the use of video games, multimedia content and virtual simulations. The objective of this resource is to help in the learning of wireless network planning problem and improve the students' knowledge in the field of wireless networks key concepts. The virtual laboratory allows students to solve simple problems of antennas distribution and progressively increase the level by adding constraints and including new concepts in the design of the network.
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Authors:
Shankar, Shashi Kant and Rodríguez-Triana, María Jesús and Ruiz-Calleja, Adolfo and Prieto, Luis P. and Chejara, Pankaj and Martínez-Monés, Alejandra
Abstract:
Multimodal Learning Analytics (MMLA) systems, understood as those that exploit multimodal evidence of learning to better model a learning situation, have not yet spread widely in educational practice. Their inherent technical complexity, and the lack of educational stakeholder involvement in their design, are among the hypothesized reasons for the slow uptake of this emergent field. To aid in the process of stakeholder communication and systematization leading to the specification of MMLA systems, this paper proposes a Multimodal Data Value Chain (M-DVC). This conceptual tool, derived from both the field of Big Data and the needs of MMLA scenarios, has been evaluated in terms of its usefulness for stakeholders, in three authentic case studies of MMLA systems currently under development. The results of our mixed-methods evaluation highlight the usefulness of the M-DVC to elicit unspoken assumptions or unclear data processing steps in the initial stages of development. The evaluation also revealed limitations of the M-DVC in terms of the technical terminology employed, and the need for more detailed contextual information to be included. These limitations also prompt potential improvements for the M-DVC, on the path towards clearer specification and communication within the multi-disciplinary teams needed to build educationally-meaningful MMLA solutions.
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