Design and implementation of a microcontroller training kit for blend learning
Computer Applications in Engineering Education
; 2022.
Article
in English
| Scopus | ID: covidwho-1825891
ABSTRACT
Today, microcontrollers are of paramount importance in various aspects of life. They are used for design in many industrial fields from simple to highly complex devices. With a COVID-19 crisis going on, blending learning is the ideal solution for a post-pandemic society. This paper proposes a blended learning system as a solution to address today's problem in teaching microcontroller courses through collaboration between distance learning with the proposed training toolkit for real work. Implementation of the proposed solution began by constructing an inexpensive training kit (100$), to empower all students, even those in remote rural areas. The distance learning model allows the simulation of the proposed IoT projects electronically anywhere and at any time using the Proteus design suite, which helps students to conduct them before the actual laboratory appointment. Two learning models are programmed in assembly language which is directly related to the internal architecture of the microcontroller and provides access to all the real capabilities of its central processing unit. To get acquainted with all the features offered by the microcontroller integrated circuit, various IoT projects were constructed, each one dedicated to learning its architecture features, important to engineering students. The proposed IoT systems operate with a minimum consuming power that is very important for portable devices. Questionnaire questions for students were formulated to measure the proposed system benefit over three academic years. © 2022 Wiley Periodicals LLC.
Assembly Language; ATMEGA2560 Microcontroller; IoT; Proteus (ISIS); training kit; Blending; Controllers; Distance education; Internet of things; Learning systems; Microcontrollers; Program processors; Assembly-language; Complex devices; Design and implementations; Distance-learning; Industrial fields; Learning models; Simple++; Students
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
Computer Applications in Engineering Education
Year:
2022
Document Type:
Article
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