Integrating internet of things in electrical engineering education

Alharbi, Fahd

doi:10.1177/0020720920903422

Cited by 16 publications

(9 citation statements)

References 14 publications

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“…Examples of new technologies introduction into educational process is a topic of many papers, i.e. augmented reality (Yüzüak et al 2020) or internet of things (Alharbi 2020), and improvements in laboratory exercises is reviewed in (Mohan et al 2019). Implementation of 3D printing into education is addressed in (Jaksic 2016;Sharif et al 2020) Low-cost 3D additive manufacturing has become quite popular and this technique is developing very rapidly, with seemingly unlimited potential.…”

Section: Introductionmentioning

confidence: 99%

Introduction Of 3D Printing Into Marine Electrical Engineering Education – A Case Study

Kuzmanić¹,

Vujović²,

Kulenović³

et al. 2021

ped

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The research on 3D printing aboard ships is already under way. The private sector and the navy are both experimenting with its usage. This type of education is however missing in mariner education (e.g. Electrotechnical Officer) and in International Convention on Standards of Training, Certification and Watchkeeping for Seafarers (STCW) alike. Various authors have proposed that 3D printing should be included in the STCW standard courses. This paper describes an example of introduction of 3D printing into marine electrical engineering education at the Faculty of Maritime Studies in Split. The class is mandatory for this study. This is performed through “learning by doing” technique.

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Section: Introductionmentioning

confidence: 99%

Introduction Of 3D Printing Into Marine Electrical Engineering Education – A Case Study

Kuzmanić¹,

Vujović²,

Kulenović³

et al. 2021

ped

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“…One of the global trends in the industrial and educational fields is known as Industry 4.0, which enables the design of intelligent and automated production systems providing digital technologies such as the Internet, integrated sensors, artificial intelligence, and big data. ese technologies allow complex industrial applications [1] focused on satisfying customer needs and production standards in the modern industry [2].…”

Section: Introductionmentioning

confidence: 99%

“…A specific competence of this subject focuses on the use of fuzzy logic algorithms for the design of controllers which are applied in the design of process control, power electronics converters, electric machines, vehicles, and numerical control machines, among others. e objective of this competency is for students to be able to (1) know the general structure of a fuzzy logic controller (FLC), (2) design an FLC, (3) apply an FLC, and (4) implement an FLC by designing the stages of fuzzification, fuzzy inference rules, and defuzzification.…”

Section: Introductionmentioning

confidence: 99%

“…Another use of the LabVIEW virtual instrumentation software in the educational field is the one proposed in [25], where they used this tool for the development of computer programming skills in the physics area in a course of computer-assisted instrumentation; the effectiveness of the proposal was evaluated through the statistical analysis of questionnaires and responses to interviews, obtaining, as a result, an increase in the knowledge acquired and an increase in motivation and confidence of the students. In contrast, in [2], the integration of IoT technology and electrical engineering education to develop future skills in students was proposed. To evaluate the results of the workshop given, a survey of 23 students was conducted, where the students expressed positive comments about the knowledge and skills acquired in the workshop.…”

Section: Introductionmentioning

confidence: 99%

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Development of a Didactic Educational Tool for Learning Fuzzy Control Systems

Aguilera-Alvarez

Padilla-Medina

Martínez-Nolasco

et al. 2021

Mathematical Problems in Engineering

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This paper presents the development of a virtual didactic tool for students of mechatronic engineering taking an intelligent system course. The objective of the tool is for students to learn the structures for fuzzy control systems. This tool makes it easier for students to understand the behavior of the membership functions of input and output variables, the evaluation of the set of fuzzy rules, and the method of defuzzification, giving the students the possibility of applying a fuzzy controller in industrial processes using a data acquisition board. The proposed tool was developed with the virtual instrumentation software LabVIEW. It has the advantage that students can manipulate the internal structure of the fuzzy logic control system in a unique window where students can analyze the behavior of internal signals by looking at the response graphs. The fuzzy controller can be easily translated to a real application by using LabVIEW compatible hardware. To have feedback from students on the use of the tool and to understand if this tool allows an improvement in their academic performance, a 2-hour workshop on the proposed application was given to a group of 93 students. At the end of the workshop, a knowledge assessment and a perception survey were applied to the participants. The academic performance achieved by students who were given the workshop using the proposed teaching tool was compared with the academic performance of students who witnessed the workshop using Matlab tools. The statistical analysis of the results obtained for the knowledge assessment shows that the students that had taken the workshop using the proposed teaching tool had better compression of the topic compared to the students that had taken the workshop using the Fuzzy Logic Toolbox provided by Matlab MathWorks. The students that had taken the workshop using the proposed teaching tool obtained a mean grade of 89.63/100, while students that had taken the workshop using Matlab’s tools obtained a mean grade of 69.85/100. Also, the students’ perception of the proposed tool was that it allowed the design of fuzzy control systems in a simple and intuitive way.

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“…In addition, research is continuing to be conducted to improve skills in the fields of nursing, robot education, and IoT practical education [13][14][15]. However, learning that utilizes IoT-based training kits such as the Arduino Uno, Raspberry Pi, and Atmega 128 are difficult to learn even if computer programming is practiced [16]. For example, if the instructor presented a circuit diagram, but the learner does not fully grasp the concept due to an incorrect implementation, or the malfunction of a part, or a typo in the programming process and the compilation fails, then the student can lose motivation.…”

Section: Introductionmentioning

confidence: 99%

Design and Development of a Self-Diagnostic Mobile Application for Learning Progress in Non-Face-to-Face Practice Learning

Kim

Mun

2021

Applied Sciences

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Due to COVID-19, non-F2F (non-face-to-face) learning is being conducted in educational sites around the world. Unlike theoretical subjects, which have a variety of applicable non-F2F learning content, in practical subjects, learners may undergo many difficulties due to many learning activities. Therefore, this research tries to design and develop a mobile application that allows learners to perform a self-diagnostic on their learning progress. In this research, we conducted a mobile application usability evaluation for 36 students who participated in non-F2F Arduino practice learning. To this end, we applied the ADDIE (Analysis, Design, Development, Implement, and Evaluation) model to develop a self-diagnostic mobile application for students’ learning progress according to the learning content. The research tool modified and distributed the question item appropriate for this subject’s study for the mobile usability evaluation that was used in the previous study. This research applied the ADDIE model to analyze the characteristics of students and learning contents, including designed learning contents, database, menu structure, developed learning contents, and mobile application. After using this in non-F2F practice learning for 15 weeks, a mobile application usability evaluation was conducted. As a result of the study, due to receiving usability scores between 3.53 and 4.42, it was found that the learning progress self-diagnostic in non-F2F practice learning was essential and that mobile applications were useful in non-F2F practice learning. Additionally, 33 out of 36 students responded that it would be useful for their learning if they actively used it in other subjects as well. We have found that leveraging self-diagnostic mobile applications through the mobile application usability evaluation tool can be useful for non-F2F practice learning. Additionally, it is expected to be useful for non-F2F practice learning if additional research is conducted on other factors as well such as teaching presence, online learning engagement, and learning flow in the future.

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Integrating internet of things in electrical engineering education

Cited by 16 publications

References 14 publications

Introduction Of 3D Printing Into Marine Electrical Engineering Education – A Case Study

Introduction Of 3D Printing Into Marine Electrical Engineering Education – A Case Study

Development of a Didactic Educational Tool for Learning Fuzzy Control Systems

Design and Development of a Self-Diagnostic Mobile Application for Learning Progress in Non-Face-to-Face Practice Learning

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