A Neuroscience Approach regarding Student Engagement in the Classes of Microcontrollers during the COVID19 Pandemic
Iuliana Marin

TL;DR
This paper explores using neuroscience tools like EEG headsets to measure and enhance student engagement during microcontroller classes, especially in online settings prompted by COVID-19, by applying innovative teaching methods.
Contribution
It introduces a novel approach combining neuroscience and virtual simulation to assess and improve student engagement in microcontroller courses.
Findings
Game-based learning increased student problem-solving and software skills.
Neuroscience data provided insights into student engagement levels.
Virtual platforms and neuroscience tools can enhance online teaching effectiveness.
Abstract
The process of teaching has been greatly changed by the COVID-19 pandemic. It is possible that studying will not resemble anymore the process known by the previous generations of students. As the current generations learn by doing and use their intuition, new platforms need to be involved in the teaching process. The current paper proposes a new method to keep the students engaged while learning by involving neuroscience during the classes of Microcontrollers. Arduino and Raspberry Pi boards are studied at the course of Microcontrollers using online simulation environments. The Emotiv Insight headset is used by the professor during the theoretical and practical hours of the Microcontrollers course. The analysis performed on the brainwaves generated by the headset provides numerical values for the mood, focus, stress, relaxation, engagement, excitement and interest levels of the…
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