Enabling peer-to-peer remote experimentation in distributed online remote laboratories

Remote Access Laboratories (RALs) are online platforms that allow human user interaction with physical instruments over the Internet. Usually RALs follow a client-server paradigm. Dedicated providers create and maintain experiments and corresponding educational content. In contrast, this dissertation focuses on a Peer-to-Peer (P2P) service model for RALs where users are encouraged to host experiments at their location. This approach can be seen as an example of an Internet of Things (IoT) system. A set of smart devices work together providing a cyber-physical interface for users to run experiments remotely via the Internet. The majority of traditional RAL learning activities focus on undergraduate education where hands-on experience such as building experiments, is not a major focus. In contrast this work is motivated by the need to improve Science, Technology, Engineering and Mathematics (STEM) education for school-aged children. Here physically constructing experiments forms a substantial part of the learning experience. In the proposed approach, experiments can be designed with relatively simple components such as LEGO Mindstorms or Arduinos. The user interface can be programed using SNAP!, a graphical programming tool. While the motivation for the work is educational in nature, this thesis focuses on the technical details of experiment control in an opportunistic distributed environment. P2P RAL aims to enable any two random participants in the system - one in the role of maker creating and hosting an experiment and one in the role of learner using the experiment - to establish a communication session during which the learner runs the remote experiment through the Internet without requiring a centralized experiment or service provider. The makers need to have support to create the experiment according to a common web based programing interface. Thus, the P2P approach of RALs requires an architecture that provides a set of heterogeneous tools which can be used by makers to create a wide variety of experiments. The core contribution of this dissertation is an automaton-based model (twin finite state automata) of the controller units and the controller interface of an experiment. This enables the creation of experiments based on a common platform, both in terms of software and hardware. This architecture enables further development of algorithms for evaluating and supporting the performance of users which is demonstrated through a number of algorithms. It can also ensure the safety of instruments with intelligent tools. The proposed network architecture for P2P RALs is designed to minimise latency to improve user satisfaction and learning experience. As experiment availability is limited for this approach of RALs, novel scheduling strategies are proposed. Each of these contributions has been validated through either simulations, e.g. in case of network architecture and scheduling, or test-bed implementations, in case of the intelligent tools. Three example experiments are discussed along with users' feedback on their experience of creating an experiment and using others’ experimental setup. The focus of the thesis is mainly on the design and hosting of experiments and ensuring user accessibility to them. The main contributions of this thesis are in regards to machine learning and data mining techniques applied to IoT systems in order to realize the P2P RALs system. This research has shown that a P2P architecture of RALs can provide a wide variety of experimental setups in a modular environment with high scalability. It can potentially enhance the user-learning experience while aiding the makers of experiments. It presents new aspects of learning analytics mechanisms to monitor and support users while running experiments, thus lending itself to further research. The proposed mathematical models are also applicable to other Internet of Things applications

Improving Laboratory Learning Outcomes: An Investigation Into the Effect of Contextualising Laboratories Using Virtual Worlds and Remote Laboratories.

This thesis presents research into improving learning outcomes in laboratories. It was hypothesised that domain specific context can aid students in understanding the relationship between a laboratory (as a proxy for reality), the theoretical model being investigated within the laboratory activity and the real world. Specifically, the research addressed whether adding domain context to a laboratory activity could improve students' ability to identify the strengths and limitations of models as predictors of real-world behaviour. The domain context was included in a laboratory activity with the use of a remote radiation lab set within a context-rich virtual world. The empirical investigation used a pretest-posttest control group design to assess whether there was a statistically significant difference in the learning outcome between a treatment group who completed the lab in a contextualised virtual world, and the control group who conducted the activity in an empty virtual world. The results showed that there were no statistically significant differences between the groups and therefore there are cases where contextualising a laboratory activity will not have an effect on students' ability to identify the strengths and limitations of models as predictors of real-world behaviour. This research postulates that previous exposure to the model, the level of awareness students had of the context and the lack time available for reflection may have masked or attenuated the effect of the context. This research has contributed a framework for the analysis and design of domain context in laboratory activities, and an interface for integrating iLabs laboratories into the Open Wonderland virtual world. It has explicitly clarified the relationship between context, labs, models and the real world. Most significantly, this research has contributed knowledge to the field of laboratory learning outcomes and the understanding of how domain context affects laboratory activities

XIV Conference on Technology, Teaching and Learning of Electronics

Livro de atas da TAEE2020.A conferencia TAEE conhecerá na sua 14ª edição um momento histórico. Não só é a primeira vez que a será organizada fora do território Espanhol, como terá lugar a verdadeiramente pioneira experiência de realizar esta conferência num formato puramente virtual no Instituto Superior de Engenharia do Porto. Esta opção representa a solução possível para um evidente problema mundial, que surgiu de forma repentina durante a preparação desta edição. Optamos por aplicar a típica abordagem de engenharia, instintivamente encarando este novo problema como uma verdadeira oportunidade, e aproveitando as limitações impostas para experimentar novas soluções para novas questões. Tentamos criar uma TAEE diferente, não melhor nem pior, mas indo buscar proveitos às tecnologias de comunicação emergentes de forma a criar e dinamizar um evento onde não estaremos fisicamente juntos, mas poderemos comunicar e conviver de forma virtual. A grande motivação da TAEE será sempre os visíveis entrosamentos, dedicação e motivação da comunidade e serão estes fatores que permitirão o sucesso nesta nova forma de estarmos e trabalharmos juntos, mas à distância.info:eu-repo/semantics/publishedVersio

Integración de laboratorios online de automática y telecomunicación en los sistemas de gestión de aprendizaje mediante SCORM

[ES]Los laboratorios online o WebLabs son valiosos recursos de apoyo a la docencia que se pueden definir como contenidos de e-learning. Una de las últimas tendencias en el desarrollo de WebLabs ha sido su integración en los Sistemas de Gestión de Aprendizaje (LMS). Esta tesis presenta una propuesta de integración avanzada Lab-LMS basada en el uso de SCORM (Shared Content Object Reference Model) para definir el contenido y realizar comunicaciones Lab-LMS. Se presenta una clasificación de modos de integración, se describen una serie de herramientas, desarrolladas específicamente para facilitar la integración propuesta, y una metodología genérica para crear laboratorios online. También se describen ejemplos de laboratorios online desarrollados siguiendo el modelo de integración propuesto que se han creado utilizando la metodología y las herramientas creadas en el ámbito de este trabajo. Los resultados obtenidos demuestran que los laboratorios obtenidos presentan una gran efectividad para el aprendizaje de los alumnos.[EN] WebLabs or online labs are valuable resources to support teaching that can be defined as e-learning content. One of the latest trends in the development of WebLabs has been its integration into Learning Management Systems (LMS). This thesis presents a Lab-LMS advanced-integration proposal based on using SCORM (Shared Content Object Reference Model) to define contents and perform Lab-LMS communications. A classification of modes of integration is presented and a set of tools, that has been developed specifically to facilitate the integration proposal, and a generic methodology to create online laboratories are described. Examples of online laboratories, developed following the proposed integration model, and using the methodology and tools developed within the scope of this work are also described. The results show that obtained laboratories show that they are highly effective for student learning.Tesis Univ. Jaén. Departamento de Ingeniería Electr´nica y Automatica, leída el 23 de noviembre de 201