Aware that the lack of mathematical knowledge and skills is a major problem for the development
of a modern, inclusive and informed society, the MathE partnership has developed a tool that is
aimed at bridging the gap that moves students away from courses that rely on a mathematical
core. The MathE collaborative learning platform offers higher education students a package of
scientific and pedagogical resources that allow them to be active agents in their learning pathway,
by self-managing their study. The MathE platform is currently being used by a significant number
of users, from all over the world, as a tool to support and engage students, ensuring new and
creative ways to encourage them to improve their mathematical skills and therefore increasing
their confidence and capacities. In order to enhance this platform, a visual representation of
the performance of the students is already implemented, based on the recorded performance
historic data for each student. This paper contains a literature review about the implementation
of data mining techniques in education, followed by a description of the features of the MathE
learning system and suggestions of data parameters to support the improvement of the students’
performance. Future work includes the application of optimization and learning algorithms so
that the MathE platform will have a dynamical structure and act as a virtual tutor for the users.
Internet of Things, IoT, is a promising methodology that has
been increasing over the last years. It can be used to allow the connection
and exchange data with other devices and systems over the Internet.
One of the IoT connection protocols is the LoRaWAN, which has several
advantages but has a low bandwidth and limited data transfer. There is
a necessity of optimising the data transfer between devices. Some sensors
have a 10 or 12 bits resolution, while LoRaWAN owns 8 bits or multiples
slots of transmission remaining unused bits. This paper addresses
a communication optimisation for wireless sensors resorting to encoding
and decoding procedures. This approach is applied and validated on the
real scenario of a wildfire detection system.
