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Standardization Layers for Remote Laboratories as Services and Open Educational Resources

Denis Gillet, Christophe Salzmann, Wissam Halimi

Deliveringeducationandeducationalresourceshasevolvedfromclass- centered settings towards distributed, cloud-based models. This is mainly the con- sequence of publicly available educational resources such as documents, videos, and web applications. At the same time, emerging technologies in information and communication are enabling the development and deployment of remote lab- oratories on the Web. Today, these freely and openly available educational inter- active media are known as Open Education Resources (OERs). Learning manage- ment systems, MOOC platforms, and educational social media platforms provide a medium for teachers to create their teaching activities around OERs in a struc- tured way. To enjoy an effective and productive learning experience, it is neces- sary for the educational resources to be fully integrated in the hosting platform. While most platforms have a ready-to-embed infrastructure for certain types of OERs, they are not ready to host remote laboratories in an integrated fashion. In this paper, we define the necessary integration layers for remote labs in on- line learning environments. The work is validated by two implementations with different target platforms.

Springer2018

Topics in Educational Cyber-Physical Labs

Wissam Halimi

Recent advances in remote sensing and actuation technologies, coupled with the large reach of the internet, allowed for the emergence of applications such as cyber-physical labs. Cyber-physical labs are the digital and remotely-accessible equivalent of the lab equipment students use in school to experiment, through web-based interfaces such as web applications. Students, teachers and lab owners derive value from these systems, they are our stakeholders. Students are the intended users, teachers are the educational content curators and lab owners are the service providers. In this thesis, we take a close look at issues pertaining to cyber-physical labs and propose new approaches to address them. We also analyze the use of such systems in a MOOC, to detect the impact of the exherted experimental behavior of students on their academic performance. First, we tackle the case of the generation of web apps interfacing cyber-physical labs. It is the equivalent of preparing experiments for teachers by arranging the equipment for multiple experiments with the same equipment. We propose an extension to the Smart Device Specification for cyber-phyiscal labs, and a tool which generates these apps based on it. The automatically generated apps implement the necessary functions to use a cyber-physical lab, and are ready to be integrated in online learning platfroms. Next, we investigate issues related to the collection and retrieval of students' generated data through their interaction with cyber-physical labs. We consider the needs of students and lab owners. Through questionnaires sent to both parties, we elicit the requirements for an activity-tracking infrastructure composed of a vocabulary and an architectural model. The proposed vocabulary ensures deriving value from the recorded activity, and the proposed architecture addresses privacy and data access issues pertaining to students and lab owners respectively. We evaluate our proposal with two example cyber-physical labs. Last, we collect the interaction data with a cyber-physical lab used in a MOOC. We devise computational analyses on the students activity statistics, in search for indicators of academic performance. We find that high and low performing students show statistically different activity statistics. Then, we sequence the steps students did in an experiment, and don't find any statistically significant patterns for low and high-performing students. This analysis provides insights on the usage of installed facilities to service a potential massive access to limited resources (lab installations), and shed light on possible indicators for academic performance.

EPFL2018

Enabling the Automatic Generation of User Interfaces for Remote Laboratories

Denis Gillet, Christophe Salzmann, Wissam Halimi, Hagop Jamkojian

Remote laboratories are an important component of blended and dis- tance science and engineering education. By definition, they provide access to a physical lab in a distant location. Many architectures enabling remote laboratory systems exist, the most common of which are Client-Server based. In this con- text, the Server interfaces the physical setup and makes it software-accessible. The Smart Device Specifications revisit a Client-Server architecture, with the main aim of cancelling the dependencies which inherently exist between a Client and a Server. This is done by describing the Server as a set of services, which are exposed as well-defined APIs. If a remote laboratory is built following the Smart Device Specifications, any person with programming skills can create a personalized client application to access the lab. But in practice, teachers rely on the mediated contact with a lab provider to have information about what kind of experiment(s) the lab in question implements. Even though there is a complete description of the available sensors and actuators making up a lab and how to be accessed, it is not clear how they are connected (relationships). In this sense, a list of sensors and actuators are not enough to make a guided selection of compo- nents to create the interface to an experiment. Therefore, the aim of this work is to support teachers in choosing the experiments and creating the respective UI on their own, in a pedagogically oriented scenario and by taking into consideration the target online learning environment. This is done by revisiting the Smart Device Specifications and extending them, in addition to proposing a tool that will automatically generate the user interface of the chosen experiment(s).

Springer2017