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Web of Things Platforms for Distance Learning Scenarios in Computer Science Disciplines: A Practical Approach

Communications and Control Systems Department, Computer Science Faculty, Spanish National University for Distance Education (UNED), 28040 Madrid, Spain
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Technologies 2019, 7(1), 17; https://doi.org/10.3390/technologies7010017
Received: 1 November 2018 / Revised: 14 January 2019 / Accepted: 19 January 2019 / Published: 27 January 2019
(This article belongs to the Special Issue Technology Advances on IoT Learning and Teaching)
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Abstract

Problem-based learning is a widely used learning methodology in the field of technological disciplines, especially in distance education environments. In these environments, the most used tools, which provide learning scenarios, are remote and virtual laboratories. Internet of Things (IoT) devices can be used as remote or virtual laboratories. In addition to this, they can be organized/orchestrated to build remote maker spaces through the web. These types of spaces are called the Web of Things (WoT). This paper proposes the use of these types of spaces and their integration as practical activities into the curricula of technological subjects. This approach will allow us to achieve two fundamental objectives: (1) To improve the academic results (grades) of students; and (2) to increase engagement and interest of students in the studied technologies, including IoT devices. These platforms are modeled using archetypes based on different typologies and usage scenarios. In particular, these usage scenarios will implement a learning strategy for each problem to be solved. The current work shows the evolution of these archetypes and their application in the teaching of disciplines/subjects defined in computer science, such as distributed computing and cybersecurity. View Full-Text
Keywords: Internet of Things (IoT); Web of Things (WoT); computer science education; cloud computing; learning analytics Internet of Things (IoT); Web of Things (WoT); computer science education; cloud computing; learning analytics
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Tobarra, L.; Robles-Gómez, A.; Pastor, R.; Hernández, R.; Cano, J.; López, D. Web of Things Platforms for Distance Learning Scenarios in Computer Science Disciplines: A Practical Approach. Technologies 2019, 7, 17.

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