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Remote IoT Education Laboratory for Microcontrollers Based on the STM32 Chips
by
Kováčová, Irena
, Bereš, Matej
, Fecko, Branislav
, Kováč, Dobroslav
, Dziak, Jozef
, Vince, Tibor
, Jacko, Patrik
, Molnár, Ján
, Gans, Šimon
in
Arm Cortex-M
/ COVID-19
/ Distance learning
/ education
/ Educational technology
/ Humans
/ IoT
/ Laboratories
/ microcontroller
/ Microcontrollers
/ Monitoring, Physiologic
/ Online instruction
/ remote laboratory
/ Software
/ STM32
/ Students
/ Teachers
/ Teaching
2022
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Remote IoT Education Laboratory for Microcontrollers Based on the STM32 Chips
by
Kováčová, Irena
, Bereš, Matej
, Fecko, Branislav
, Kováč, Dobroslav
, Dziak, Jozef
, Vince, Tibor
, Jacko, Patrik
, Molnár, Ján
, Gans, Šimon
in
Arm Cortex-M
/ COVID-19
/ Distance learning
/ education
/ Educational technology
/ Humans
/ IoT
/ Laboratories
/ microcontroller
/ Microcontrollers
/ Monitoring, Physiologic
/ Online instruction
/ remote laboratory
/ Software
/ STM32
/ Students
/ Teachers
/ Teaching
2022
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Do you wish to request the book?
Remote IoT Education Laboratory for Microcontrollers Based on the STM32 Chips
by
Kováčová, Irena
, Bereš, Matej
, Fecko, Branislav
, Kováč, Dobroslav
, Dziak, Jozef
, Vince, Tibor
, Jacko, Patrik
, Molnár, Ján
, Gans, Šimon
in
Arm Cortex-M
/ COVID-19
/ Distance learning
/ education
/ Educational technology
/ Humans
/ IoT
/ Laboratories
/ microcontroller
/ Microcontrollers
/ Monitoring, Physiologic
/ Online instruction
/ remote laboratory
/ Software
/ STM32
/ Students
/ Teachers
/ Teaching
2022
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Remote IoT Education Laboratory for Microcontrollers Based on the STM32 Chips
Journal Article
Remote IoT Education Laboratory for Microcontrollers Based on the STM32 Chips
2022
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Overview
The article describes the implementation of IoT technology in the teaching of microprocessor technology. The method presented in the article combines the reality and virtualization of the microprocessor technology laboratory. A created IoT monitoring device monitors the students’ microcontroller pins and sends the data to the server to which the teacher is connected via the control application. The teacher has the opportunity to monitor the development of tasks and student code of the program, where the functionality of these tasks can be verified. Thanks to the IoT remote laboratory implementation, students’ tasks during the lesson were improved. As many as 53% (n = 8) of those students who could improve their results achieved an improvement of one or up to two tasks during class. Before the IoT remote laboratory application, up to 30% (n = 6) of students could not solve any task and only 25% (n = 5) solved two tasks (full number of tasks) during the class. Before implementation, 45% (n = 9) solved one problem. After applying the IoT remote laboratory, these numbers increased significantly and up to 50% (n = 10) of students solved the full number of tasks. In contrast, only 10% (n = 2) of students did not solve any task.
Publisher
MDPI AG,MDPI
Subject
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