Manos Garefalakis
Manos Garefalakis received a B.Sc. in Electronic Computing Systems Engineering from the Technological Institute of Piraeus (1997) and a B.Sc. in Electrical Engineering from the Technological Institute of Crete (2018), the Master in "Adult Education" from the Hellenic Open University (2012) and the M.Sc. degree in “Informatics & Multimedia” from the department of Informatics Engineers of the Technological Institute of Crete (2016). He is currently working towards a Ph.D. degree at the Hellenic Mediterranean University, specializing in the sector of the Remote Laboratories. Professionally, since 2001, he has worked as an IT teacher in the Secondary Education of Heraklion in Crete, Greece.
Sessions
In this work, it will be presented a Remote Laboratory, design, and implementation. The architecture
and the technologies used, in order to work as an external tool in Moodle Learning
Management System (LMS).
The Remote Laboratory provides learning experience on programming Arduino microcontrollers and working with pre-set electronic circuits. The Arduino can’t be programmed by the user for reading sensors or be an actuator by activating different components motors and lights. Apart from the programming part the Remote Laboratory provides the ability for the user to interact with the Remote Laboratory, by activating Lights, motors, and servo motors, in order to trigger the sensors connected to the Arduino.
To accomplish the interconnection of the Remote Laboratory with the Moodle platform, it is used
the Learning Tools Interoperability (LTI) technology, and with this way, it is achieved from Moodle users to connect to the Remote Laboratory and have a learning experience on a remote system. The Remote Laboratory provides users with access to a pre-set infrastructure, which logs and evaluates the user’s actions on the Remote Laboratory, and when the user logs out from the Remote Laboratory, the user’s grade book in the course is updated. Using the user’s learning analytics it is achievable to create a user’s adaptive learning path.
Additionally, the user’s learning analytics using Experience API (xAPI) are stored in a database
for further evaluation and decision-making. In order to show the capabilities of the Remote Laboratory, which is created on the Project’s site moodle.iot.hmu.gr, a course that demonstrates the above-mentioned, and this course will be presented and discussed in this presentation.