Remote IoT Education Laboratory for Microcontrollers Based on the STM32 Chips

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 pin...

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Main Authors: Patrik Jacko, Matej Bereš, Irena Kováčová, Ján Molnár, Tibor Vince, Jozef Dziak, Branislav Fecko, Šimon Gans, Dobroslav Kováč
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/22/4/1440
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author Patrik Jacko
Matej Bereš
Irena Kováčová
Ján Molnár
Tibor Vince
Jozef Dziak
Branislav Fecko
Šimon Gans
Dobroslav Kováč
author_facet Patrik Jacko
Matej Bereš
Irena Kováčová
Ján Molnár
Tibor Vince
Jozef Dziak
Branislav Fecko
Šimon Gans
Dobroslav Kováč
author_sort Patrik Jacko
collection DOAJ
description 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% (<i>n</i> = 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% (<i>n</i> = 6) of students could not solve any task and only 25% (<i>n</i> = 5) solved two tasks (full number of tasks) during the class. Before implementation, 45% (<i>n</i> = 9) solved one problem. After applying the IoT remote laboratory, these numbers increased significantly and up to 50% (<i>n</i> = 10) of students solved the full number of tasks. In contrast, only 10% (<i>n</i> = 2) of students did not solve any task.
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spelling doaj.art-ca30b3afeba942b6b1ab30539f999c522023-11-23T21:59:35ZengMDPI AGSensors1424-82202022-02-01224144010.3390/s22041440Remote IoT Education Laboratory for Microcontrollers Based on the STM32 ChipsPatrik Jacko0Matej Bereš1Irena Kováčová2Ján Molnár3Tibor Vince4Jozef Dziak5Branislav Fecko6Šimon Gans7Dobroslav Kováč8Department of Theoretical and Industrial Electrical Engineering, Technical University of Košice, 04200 Košice, SlovakiaDepartment of Theoretical and Industrial Electrical Engineering, Technical University of Košice, 04200 Košice, SlovakiaDepartment of Theoretical and Industrial Electrical Engineering, Technical University of Košice, 04200 Košice, SlovakiaDepartment of Theoretical and Industrial Electrical Engineering, Technical University of Košice, 04200 Košice, SlovakiaDepartment of Theoretical and Industrial Electrical Engineering, Technical University of Košice, 04200 Košice, SlovakiaDepartment of Theoretical and Industrial Electrical Engineering, Technical University of Košice, 04200 Košice, SlovakiaDepartment of Theoretical and Industrial Electrical Engineering, Technical University of Košice, 04200 Košice, SlovakiaDepartment of Theoretical and Industrial Electrical Engineering, Technical University of Košice, 04200 Košice, SlovakiaDepartment of Theoretical and Industrial Electrical Engineering, Technical University of Košice, 04200 Košice, SlovakiaThe 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% (<i>n</i> = 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% (<i>n</i> = 6) of students could not solve any task and only 25% (<i>n</i> = 5) solved two tasks (full number of tasks) during the class. Before implementation, 45% (<i>n</i> = 9) solved one problem. After applying the IoT remote laboratory, these numbers increased significantly and up to 50% (<i>n</i> = 10) of students solved the full number of tasks. In contrast, only 10% (<i>n</i> = 2) of students did not solve any task.https://www.mdpi.com/1424-8220/22/4/1440remote laboratoryIoTeducationmicrocontrollerSTM32Arm Cortex-M
spellingShingle Patrik Jacko
Matej Bereš
Irena Kováčová
Ján Molnár
Tibor Vince
Jozef Dziak
Branislav Fecko
Šimon Gans
Dobroslav Kováč
Remote IoT Education Laboratory for Microcontrollers Based on the STM32 Chips
Sensors
remote laboratory
IoT
education
microcontroller
STM32
Arm Cortex-M
title Remote IoT Education Laboratory for Microcontrollers Based on the STM32 Chips
title_full Remote IoT Education Laboratory for Microcontrollers Based on the STM32 Chips
title_fullStr Remote IoT Education Laboratory for Microcontrollers Based on the STM32 Chips
title_full_unstemmed Remote IoT Education Laboratory for Microcontrollers Based on the STM32 Chips
title_short Remote IoT Education Laboratory for Microcontrollers Based on the STM32 Chips
title_sort remote iot education laboratory for microcontrollers based on the stm32 chips
topic remote laboratory
IoT
education
microcontroller
STM32
Arm Cortex-M
url https://www.mdpi.com/1424-8220/22/4/1440
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