Using Computer Vision for Student-Centred Remote Lab in Electronics

Abstract : Technology is affecting students' life in different ways. Nowadays, students are more interested in social media, games and Internet of Things. On the other hand, most current teaching techniques appear outdated and uninteresting to students due to the fact that they do not follow the technological advances. For these reasons, students nowadays do not show much interest in education and learning. On the other hand, there is an urgent need for new learning approaches that take into account both the interests of today's students and the technological advances in several fields like telecommunication and gaming. Particularly for STEM curricula (Science, Technology, Engineering, and Math), labs play a crucial role to help students fully understand the material given during lectures. However, traditional hands-on labs are tied to space-time constraints: a student must perform the lab activity in a pre-scheduled time and in a given space. Furthermore, traditional labs are not suited for all students: some students may need more help and more motivating factors in order to take the most of the lab experience and to enhance their learning outcomes. This is not always best done in hands-on labs due to large number of students and to the presence of only one teacher that has to do lots of effort to adapt to each student's needs. Remote labs provide an alternative experience to the traditional lab, eliminating time-space constraints and introducing students to a new way of working by manipulating hardware remotely, which is used frequently in industry (SCADA: Supervisory Control and Data Acquisition). It can also be adapted to each student's needs if one is capable to infer student's mood, emotion and competence. In this paper we present the implementation of a remote lab in electronics, called LaboREM, which takes advantage of the technological advances in telecommunication and takes into consideration what current students are interested in. It is based on three parts: a remote laboratory, a learning management system and a game-like approach. The remote laboratory consists of remotely-controlled measurement devices, plus a simple robotic arm that mimics the student hand to construct electronic circuits. The robotic arm picks up electronics components equipped with magnets and places them on a breadboard. A wide angle camera is installed in order that students see what is physically happening in the lab. The electronic lab activity consists of short-time experiments (mainly tests on active filters) that last less than 5 minutes. The scenario is based on a game-like approach: a treasure hunt and a Top 10. Furthermore, a mini drone that can be controlled by the student remotely complements the static camera to add more immersion to the lab experience. The student can send specific requests to the drone in order to see some electronic instruments in a more interesting way. Moreover image processing and pattern recognition techniques are also used to infer student mood, concentration and motivation. Clues of boredom, lack of motivation and concentration (closed eyes, student not looking at the screen, student keeping moving.) are detected from the video of students' face taken from a webcam in order to adapt the scenario and the lab to each student.
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Fawzi Khattar, Franck Luthon, Benoit Larroque, Fadi Dornaika. Using Computer Vision for Student-Centred Remote Lab in Electronics. 8th Int. Conf. on Education and New Learning Technologies (EDULEARN 2016), Jul 2016, Barcelona, Spain. pp.614-623. ⟨hal-01907082⟩

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