Submit to Special Issue Submit Abstract to Special Issue Review for Sensors Propose a Special Issue

Journal Menu

Journal Browser

► Journal Browser

Smart Educational Systems: Hardware and Software Aspects

Special Issue Editors
Special Issue Information
Keywords
Published Papers

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 31649

Share This Special Issue

Special Issue Editors

Prof. Dr. Sapounidis Theodosios

E-Mail Website
Guest Editor

Department of Information and Electronic Engineering, International Hellenic University (I.H.U.), 57001 Nea Moudania, Greece
Interests: tangible programming; tangible user interfaces; educational robotics; augmented reality in education
Special Issues, Collections and Topics in MDPI journals

Dr. Christos Troussas

E-Mail Website
Guest Editor

Department of Informatics and Computer Engineering, University of West Attica, 12243 Egaleo, Greece
Interests: adaptive hypermedia systems; artificial intelligence in education; human-centered artificial intelligence; human–computer interaction; personalized software
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Efkleidis Keramopoulos

E-Mail Website
Guest Editor

Department of Information and Electronic Engineering, International Hellenic University (I.H.U.), Thessaloniki, Greece
Interests: human–computer interaction; augmented reality in education

Dr. Christina Volioti

E-Mail Website
Guest Editor

Department of Information and Electronic Engineering, International Hellenic University (I.H.U.), Thessaloniki, Greece
Interests: augmented reality; gesture recognition; human-computer interaction; 3D virtual worlds; games

Special Issue Information

Dear Colleagues,

Current educational software/hardware systems incorporate intelligent tools and sensor technologies that work towards creating prosperous learning environments for students. Such environments can offer several benefits to education, facilitate the delivery of learning material, enhance engagement and motivation, and promote more effective and efficient education while reducing drop-out rates. The means to achieve the above lies in solutions offered by sensor usage in education, educational robotics, tangible user interfaces, artificial intelligence, augmented reality, simulation-based learning, etc.

The Special Issue (SI) “Smart educational systems: Hardware and Software Aspects” aims to continue and promote the discussion about intelligent tutoring systems that might combine hardware/software with multiple sensors in order to make more efficient and attractive educational systems. Our goal is to further extend the focus on the state-of-the-art developments in fields that can be employed in papers of the SI topic and fall within the scope of Sensors, such as:

Physical sensors;
Remote sensors;
Smart/intelligent sensors;
Sensor devices;
Sensor technology and application;
Sensor interfaces;
Human–computer interaction;
Sensing systems;
Vision/camera-based sensors;
Machine/deep learning and artificial intelligence in sensing;
3D sensing;
Communications and signal processing;
Wearable sensors, devices, and electronics.

Towards this direction, this Special Issue is soliciting original research papers as well as review articles and short communications in specific relevant areas. The topics of interest include, but are not limited to, the following:

Sensor usage in education;
Educational systems with sensors;
Usability in educational sytems;
Educational robotics;
Tangible user interfaces;
Augmented reality;
Intelligent and adaptive learner interfaces;
Intelligent tutoring systems;
Personalized educational software or hardware;
Artificial intelligence tools in educational systems;
Educational games, edutainment and gamification;
Mobile and ubiquitous learning;
Security and privacy issues in educational systems;
User acceptance and the impact of smart educational systems;
User experience in educational sytems;
Teaching topics related with sensors.

Prof. Dr. Sapounidis Theodosios
Dr. Christos Troussas
Prof. Dr. Efkleidis Keramopoulos
Dr. Christina Volioti
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

sensors in education
educational robotics
tangible or tactile user interfaces
artificial intelligence in education
smart learning environments
multimodal learner interfaces
personalized technologies in education
virtual reality
augmented reality
mixed reality
user experience

Published Papers (11 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

Jump to: Review

33 pages, 8608 KiB

Open AccessArticle

MagnetoShield: A Novel Open-Source Magnetic Levitation Benchmark Device for Mechatronics Education and Research

by Gergely Takács, Jakub Mihalík, Martin Gulan, Anna Vargová, Erik Mikuláš and Štepán Ožana

Sensors 2024, 24(2), 538; https://doi.org/10.3390/s24020538 - 15 Jan 2024

Viewed by 1037

Abstract

This article presents an open-source device illustrating the well-known magnetic levitation experiment. The uniqueness of this particular device lies in its exceptionally small dimensions, affordability and availability, which makes it a perfect design for take-home experiments for education but it can also serve as a referential design for testing various control algorithms in research. In addition, this paper provides a comprehensive hardware design for reproducibility along with the detailed derivation of the mathematical model, system identification and validation. Moreover, the introduced hardware comes with an easy-to-use open-source application programming interface in C/C++ for the Arduino IDE, Simulink and CircuitPython. REXYGEN, another environment similar to Simulink, had also been used to demonstrate the capabilities of the MagnetoShield. Full article

(This article belongs to the Special Issue Smart Educational Systems: Hardware and Software Aspects)

► Show Figures

Figure 1

17 pages, 7388 KiB

Open AccessArticle

Rapid IoT Prototyping: A Visual Programming Tool and Hardware Solutions for LoRa-Based Devices

by Juan José López and Paula Lamo

Sensors 2023, 23(17), 7511; https://doi.org/10.3390/s23177511 - 29 Aug 2023

Viewed by 3444

Abstract

LoRa technology has gained popularity as one of the most widely used standards for device interconnection due to its ability to cover long distances and energy efficiency, making it a suitable choice for various Internet of Things (IoT) monitoring and control applications. In this sense, this work presents the development of a visual support tool for creating IoT devices with LoRa and LoRaWAN connectivity. This work significantly advances the state of the art in LoRa technology by introducing a novel visual support tool tailored for creating IoT devices with LoRa and LoRaWAN connectivity. By simplifying the development process and offering compatibility with multiple hardware solutions, this research not only facilitates the integration of LoRaWAN technology within educational settings but also paves the way for rapid prototyping of IoT nodes. The incorporation of block programming for LoRa and LoRaWAN using the Arduinoblocks framework as a graphical environment enhances the capabilities of the tool, positioning it as a comprehensive solution for efficient firmware generation. In addition to the visual tool for firmware generation, multiple compatible hardware solutions enable easy, economical, and stable development, offering a comprehensive hardware and software solution. The hardware proposal is based on an ESP32 microcontroller, known for its power and low cost, in conjunction with an RFM9x module that is based on SX127x LoRa transceivers. Finally, three successfully tested use cases and a discussion are presented. Full article

(This article belongs to the Special Issue Smart Educational Systems: Hardware and Software Aspects)

► Show Figures

Figure 1

28 pages, 16671 KiB

Open AccessArticle

Location-Based Augmented Reality for Cultural Heritage Communication and Education: The Doltso District Application

by Alexandros Kleftodimos, Athanasios Evagelou, Amalia Triantafyllidou, Magdalini Grigoriou and Georgios Lappas

Sensors 2023, 23(10), 4963; https://doi.org/10.3390/s23104963 - 22 May 2023

Cited by 4 | Viewed by 2450

Abstract

Location-based Augmented Reality applications are increasingly used in many research and commercial fields. Some of the fields that these applications are used are recreational digital games, tourism, education, and marketing. This study aims to present a location-based augmented reality (AR) application for cultural heritage communication and education. The application was created to inform the public, especially K12 students, about a district of their city with cultural heritage value. Furthermore, Google Earth was utilized to create an interactive virtual tour for consolidating the knowledge acquired by the location-based AR application. A scheme for evaluating the AR application was also constructed using factors suitable for location-based applications: challenge, educational usefulness (knowledge), collaboration, and intention to reuse. A sample of 309 students evaluated the application. Descriptive statistical analysis showed that the application scored well in all factors, especially in challenge and knowledge (mean values 4.21 and 4.12). Furthermore, structural equation modeling (SEM) analysis led to a model construction that represents how the factors are causally related. Based on the findings, the perceived challenge significantly influenced the perceived educational usefulness (knowledge) (b = 0.459, sig = 0.000) and interaction levels (b = 0.645, sig = 0.000). Interaction amongst users also had a significant positive impact on users’ perceived educational usefulness (b = 0.374, sig = 0.000), which in turn influenced users’ intention to reuse the application (b = 0.624, sig = 0.000). Full article

(This article belongs to the Special Issue Smart Educational Systems: Hardware and Software Aspects)

► Show Figures

Figure 1

14 pages, 5768 KiB

Open AccessArticle

Research on Educational Robot System Based on Vision Processing

by Jianwei Zhao, Yutian Gu, Qifeng Hou and Zhiwei Zhang

Sensors 2023, 23(2), 1038; https://doi.org/10.3390/s23021038 - 16 Jan 2023

Cited by 1 | Viewed by 1411

Abstract

Aimed at the poor recognition effect of current educational robots on objects with complex shapes and colors and the single design of related experiments, this paper proposes a robot teaching instrument. The robot adopts a servo motor with an encoder, a drive, and a variety of sensors to realize a motor current loop, speed loop, position loop, and closed-loop control functions. Three experimental schemes were designed: a PID adjustment experiment, a robot obstacle avoidance and object-grasping program writing experiment, and a complex object recognition experiment based on cascade classifiers. The robot is conducive to improving students’ self-initiative ability, deepening their understanding of PID closed-loop control, multi-sensor fusion, and deep learning knowledge. It can improve students’ programming ability, enabling them to effectively combine theory and practice, as well as to comprehensively apply professional knowledge. Full article

(This article belongs to the Special Issue Smart Educational Systems: Hardware and Software Aspects)

► Show Figures

Figure 1

19 pages, 7797 KiB

Open AccessArticle

Design of 3D Virtual Reality in the Metaverse for Environmental Conservation Education Based on Cognitive Theory

by Shih-Che Lo and Hung-Hsu Tsai

Sensors 2022, 22(21), 8329; https://doi.org/10.3390/s22218329 - 30 Oct 2022

Cited by 17 | Viewed by 3986

Abstract

Background: Climate change causes devastating impacts with extreme weather conditions, such as flooding, polar ice caps melting, sea level rise, and droughts. Environmental conservation education is an important and ongoing project nowadays for all governments in the world. In this paper, a novel 3D virtual reality architecture in the metaverse (VRAM) is proposed to foster water resources education using modern information technology. Methods: A quasi-experimental study was performed to observe a comparison between learning involving VRAM and learning without VRAM. The 3D VRAM multimedia content comes from a picture book for learning environmental conservation concepts, based on the cognitive theory of multimedia learning to enhance human cognition. Learners wear VRAM helmets to run VRAM Android apps by entering the immersive environment for playing and/or interacting with 3D VRAM multimedia content in the metaverse. They shake their head to move the interaction sign to initiate interactive actions, such as replaying, going to consecutive video clips, displaying text annotations, and replying to questions when learning soil-and-water conservation course materials. Interactive portfolios of triggering actions are transferred to the cloud computing database immediately by the app. Results: Experimental results showed that participants who received instruction involving VRAM had significant improvement in their flow experience, learning motivation, learning interaction, self-efficacy, and presence in learning environmental conservation concepts. Conclusions: The novel VRAM is highly suitable for multimedia educational systems. Moreover, learners’ interactive VRAM portfolios can be analyzed by big-data analytics to understand behaviors for using VRAM in the future to improve the quality of environmental conservation education. Full article

(This article belongs to the Special Issue Smart Educational Systems: Hardware and Software Aspects)

► Show Figures

Figure 1

17 pages, 1747 KiB

Open AccessArticle

Watcher: Cloud-Based Coding Activity Tracker for Fair Evaluation of Programming Assignments

by Youngpil Kim, Kyungwoon Lee and Hyunchan Park

Sensors 2022, 22(19), 7284; https://doi.org/10.3390/s22197284 - 26 Sep 2022

Cited by 1 | Viewed by 1402

Abstract

Online learning has made it possible to attend programming classes regardless of the constraint that all students should be gathered in a classroom. However, it has also made it easier for students to cheat on assignments. Therefore, we need a system to deal with cheating on assignments. This study presents a Watcher system, an automated cloud-based software platform for impartial and convenient online programming hands-on education. The primary features of Watcher are as follows. First, Watcher offers a web-based integrated development environment (Web-IDE) that allows students to start programming immediately without the need for additional installation and configuration. Second, Watcher collects and monitors the coding activity of students automatically in real-time. As Watcher provides the history of the coding activity to instructors in log files, the instructors can investigate suspicious coding activities such as plagiarism, even for a short source code. Third, Watcher provides facilities to remotely manage and evaluate students’ hands-on programming assignments. We evaluated Watcher in a Unix system programming class for 96 students. The results showed that Watcher improves the quality of the coding experience for students through Web-IDE, and it offers instructors valuable data that can be used to analyze the various coding activities of individual students. Full article

(This article belongs to the Special Issue Smart Educational Systems: Hardware and Software Aspects)

► Show Figures

Figure 1

14 pages, 617 KiB

Open AccessArticle

Personalization of the Learning Path within an Augmented Reality Spatial Ability Training Application Based on Fuzzy Weights

by Christos Papakostas, Christos Troussas, Akrivi Krouska and Cleo Sgouropoulou

Sensors 2022, 22(18), 7059; https://doi.org/10.3390/s22187059 - 18 Sep 2022

Cited by 23 | Viewed by 1758

Abstract

Adaptive systems and Augmented Reality are among the most promising technologies in teaching and learning processes, as they can be an effective tool for training engineering students’ spatial skills. Prior work has investigated the integration of AR technology in engineering education, and more specifically, in spatial ability training. However, the modeling of user knowledge in order to personalize the training has been neither sufficiently explored nor exploited in this task. There is a lot of space for research in this area. In this work, we introduce a novel personalization of the learning path within an AR spatial ability training application. The aim of the research is the integration of Augmented Reality, specifically in engineering evaluation and fuzzy logic technology. During one academic semester, three engineering undergraduate courses related to the domain of spatial skills were supported by a developed adaptive training system named PARSAT. Using the technology of fuzzy weights in a rule-based decision-making module and the learning theory of the Structure of the Observed Learning Outcomes for the design of the learning material, PARSAT offers adaptive learning activities for the students’ cognitive skills. Students’ data were gathered at the end of the academic semester, and a thorough analysis was delivered. The findings demonstrated that the proposed training method outperformed the traditional method that lacked adaptability, in terms of domain expertise and learning theories, considerably enhancing student learning outcomes. Full article

(This article belongs to the Special Issue Smart Educational Systems: Hardware and Software Aspects)

► Show Figures

Figure 1

21 pages, 978 KiB

Open AccessArticle

A Model to Develop Chatbots for Assisting the Teaching and Learning Process

by Sonia Mendoza, Luis Martín Sánchez-Adame, José Fidel Urquiza-Yllescas, Beatriz A. González-Beltrán and Dominique Decouchant

Sensors 2022, 22(15), 5532; https://doi.org/10.3390/s22155532 - 25 Jul 2022

Cited by 9 | Viewed by 6861

Abstract

Recently, in the commercial and entertainment sectors, we have seen increasing interest in incorporating chatbots into websites and apps, in order to assist customers and clients. In the academic area, chatbots are useful to provide some guidance and information about courses, admission processes and procedures, study programs, and scholarly services. However, these virtual assistants have limited mechanisms to suitably help the teaching and learning process, considering that these mechanisms should be advantageous for all the people involved. In this article, we design a model for developing a chatbot that serves as an extra-school tool to carry out academic and administrative tasks and facilitate communication between middle-school students and academic staff (e.g., teachers, social workers, psychologists, and pedagogues). Our approach is designed to help less tech-savvy people by offering them a familiar environment, using a conversational agent to ease and guide their interactions. The proposed model has been validated by implementing a multi-platform chatbot that provides both textual-based and voice-based communications and uses state-of-the-art technology. The chatbot has been tested with the help of students and teachers from a Mexican middle school, and the evaluation results show that our prototype obtained positive usability and user experience endorsements from such end-users. Full article

(This article belongs to the Special Issue Smart Educational Systems: Hardware and Software Aspects)

► Show Figures

Figure 1

18 pages, 636 KiB

Open AccessArticle

Predicting Students’ Academic Performance with Conditional Generative Adversarial Network and Deep SVM

by Samina Sarwat, Naeem Ullah, Saima Sadiq, Robina Saleem, Muhammad Umer, Ala’ Abdulmajid Eshmawi, Abdullah Mohamed and Imran Ashraf

Sensors 2022, 22(13), 4834; https://doi.org/10.3390/s22134834 - 26 Jun 2022

Cited by 13 | Viewed by 2314

Abstract

The availability of educational data obtained by technology-assisted learning platforms can potentially be used to mine student behavior in order to address their problems and enhance the learning process. Educational data mining provides insights for professionals to make appropriate decisions. Learning platforms complement traditional learning environments and provide an opportunity to analyze students’ performance, thus mitigating the probability of student failures. Predicting students’ academic performance has become an important research area to take timely corrective actions, thereby increasing the efficacy of education systems. This study proposes an improved conditional generative adversarial network (CGAN) in combination with a deep-layer-based support vector machine (SVM) to predict students’ performance through school and home tutoring. Students’ educational datasets are predominantly small in size; to handle this problem, synthetic data samples are generated by an improved CGAN. To prove its effectiveness, results are compared with and without applying CGAN. Results indicate that school and home tutoring combined have a positive impact on students’ performance when the model is trained after applying CGAN. For an extensive evaluation of deep SVM, multiple kernel-based approaches are investigated, including radial, linear, sigmoid, and polynomial functions, and their performance is analyzed. The proposed improved CGAN coupled with deep SVM outperforms in terms of sensitivity, specificity, and area under the curve when compared with solutions from the existing literature. Full article

(This article belongs to the Special Issue Smart Educational Systems: Hardware and Software Aspects)

► Show Figures

Figure 1

22 pages, 3937 KiB

Open AccessArticle

iArm: Design an Educational Robotic Arm Kit for Inspiring Students’ Computational Thinking

by Chengze Zeng, Hong Zhou, Weiwei Ye and Xiaoqing Gu

Sensors 2022, 22(8), 2957; https://doi.org/10.3390/s22082957 - 12 Apr 2022

Cited by 4 | Viewed by 3453

Abstract

Educational robotics is an effective carrier of information technology education, making its way into classrooms. However, the design of the educational robotic arm kit and the study on the effect of robotic arms on students’ thinking literacy remain to be completed. In this paper, iArm, a 6-DOF robotic arm consisting of a drive chassis, an arm body, and end tools, is presented. Its auxiliary modules, including the vision module and conveyor belt, and the curriculum targeting students’ computational thinking are also developed to refine the current educational robotic arm kit. Furthermore, to explore the effectiveness of the iArm kit, thirteen high school students participated in the semester-long curriculum, completed assigned projects, and filled out the pre-test and post-test scales. By formative and summative evaluation, the result shows that the iArm kit effectively enhanced students’ computational thinking. Full article

(This article belongs to the Special Issue Smart Educational Systems: Hardware and Software Aspects)

► Show Figures

Figure 1

Review

Jump to: Research

21 pages, 1167 KiB

Open AccessReview

Assisted Robots in Therapies for Children with Autism in Early Childhood

by Ana Gómez-Espinosa, José Carlos Moreno and Sagrario Pérez-de la Cruz

Sensors 2024, 24(5), 1503; https://doi.org/10.3390/s24051503 - 26 Feb 2024

Viewed by 1021

Abstract

Children with autism spectrum disorder (ASD) have deficits that affect their social relationships, communication, and flexibility in reasoning. There are different types of treatment (pharmacological, educational, psychological, and rehabilitative). Currently, one way to address this problem is by using robotic systems to address the abilities that are altered in these children. The aim of this review will be to analyse the effectiveness of the incorporation of the different robotic systems currently existing in the treatment of children up to 10 years of age diagnosed with autism. A systematic review has been carried out in the PubMed, Scopus, Web of Science, and Dialnet databases, with the following descriptors: child, autism, and robot. The search yielded 578 papers, and nine were selected after the application of the PRISMA guideline. The quality of the studies was analysed with the PEDRo scale, and only those with a score between four and six were selected. From this study, the conclusion is that the use of robots, in general, improves children’s behaviour in the short term, but longer-term experiences are necessary to achieve more conclusive results. Full article

(This article belongs to the Special Issue Smart Educational Systems: Hardware and Software Aspects)

► Show Figures

Journal Menu

Journal Browser

Smart Educational Systems: Hardware and Software Aspects

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Published Papers (11 papers)

Research

Review

Further Information

Guidelines

MDPI Initiatives

Follow MDPI