ICTs in Education

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 40178

Special Issue Editors


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Guest Editor
Laboratory of NT and Distance Learning, School of Education, University of Ioannina, 451 10 Ioannina, Greece
Interests: ICT in education; learning theories in digital technologies; e-learning; digitalization in education
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Early Years Learning and Care Department, University of Ioannina, University of Ioannina, 451 10 Ioannina, Greece
Interests: methodological and theoretical issues on teaching and learning; ICT in Education
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The idea behind publishing this Special Issue is not to predict the future of teaching ICTs but to foresee the great potential of using ICTs in education.

The changes that entail the transition from teaching through ICTs to sustainable educational applications using ICTs often determines the strength with which they are adopted. The unprecedented public health crisis of the COVID-19 pandemic has given us a small taste of such a point, with its impact on teaching, learning, and the transition to online education in general. Education won’t be the same in the post-COVID-19 era. Learning will no longer all be about teaching but on developing a new learning environment and a reliable cooperative discovery-based understanding of new concepts in unpredictable situations.

Submissions on classroom studies, case studies, and teaching practices involving ICTs in education are welcome. The planned Special Issue aims to explore this field.

Prof. Dr. Jenny Pange
Dr. Zoi Nikiforidou
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. Applied Sciences 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 2400 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

  • ICT
  • education
  • teaching
  • learning

Published Papers (10 papers)

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Research

16 pages, 359 KiB  
Article
The Effects of an Ethics Education Program on Artificial Intelligence among Middle School Students: Analysis of Perception and Attitude Changes
by Jung-In Choi, Eunja Yang and Eun-Hee Goo
Appl. Sci. 2024, 14(4), 1588; https://doi.org/10.3390/app14041588 - 16 Feb 2024
Viewed by 913
Abstract
Artificial intelligence (AI) technology has brought convenience to human lives, but its pervasive impact extends beyond individuals, affecting society as a whole. Consequently, the necessity for an AI ethics education program has become increasingly apparent. This study aims to investigate the influence of [...] Read more.
Artificial intelligence (AI) technology has brought convenience to human lives, but its pervasive impact extends beyond individuals, affecting society as a whole. Consequently, the necessity for an AI ethics education program has become increasingly apparent. This study aims to investigate the influence of an experimental research study that developed and implemented an AI ethics education program for learners’ ethical awareness and attitude towards AI. The research methodology involved validating a model of the AI ethics education program by applying it to a group of 10 domain experts. Additionally, pre-test and post-test designs were employed with 17 middle school students as the experimental group. The same assessment was administered before and after the implementation of the AI ethics education program, and the data were analyzed using paired-sample t-tests. The findings of this study are as follows: Firstly, an AI ethics education program model was developed, incorporating key competencies such as AI literacy, critical thinking skills in AI, and AI problem-solving skills, all within the context of AI ethics. The implementation of this model was effective in the educational setting. Secondly, significant improvements were observed in the ethical awareness of middle school students across all domains after participating in the program. Thirdly, the attitudes of middle school students towards AI exhibited significant enhancements across all domains. These findings contribute to the broader field of AI ethics education by highlighting the importance of ethical awareness in AI and fostering favorable attitudes towards AI. The implications of this study are significant for the field of AI education. Full article
(This article belongs to the Special Issue ICTs in Education)
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20 pages, 1138 KiB  
Article
Effects of the International Training Program for Enhancing Intelligent Capabilities through Blended Learning on Computational Thinking, Artificial Intelligence Competencies, and Core Competencies for the Future Society in Graduate Students
by Yeong-Hwi Ahn and Eun-Young Oh
Appl. Sci. 2024, 14(3), 991; https://doi.org/10.3390/app14030991 - 24 Jan 2024
Viewed by 667
Abstract
Background: The purpose of this study is to find the effects of the international training program for enhancing intelligent capabilities through blended learning on computational thinking, artificial intelligence (AI) competency, and core competencies for the future society in graduated students enrolled in the [...] Read more.
Background: The purpose of this study is to find the effects of the international training program for enhancing intelligent capabilities through blended learning on computational thinking, artificial intelligence (AI) competency, and core competencies for the future society in graduated students enrolled in the Smart Information Communication Technology (SMART ICT) course. The teaching model followed the ADDIE framework. Methods: This study is a quasi-experimental study based on nonequivalent control group design. Study subjects were assigned to an experimental (n = 20) or control group (n = 20). The experimental group participated in the international training program in the blended learning form, real-time online classes (60 min per session for a week, six sessions) and face-to-face classes (4–8 h per session for 9 days, six sessions). The variables were measured with a self-report questionnaire and were evaluated before, right after, and in the 12th week of the program. Results: The AI competency of the experimental group was observed to be significantly changed at the points of time (F = 6.76, p = 0.002), and in comparison with that of a different group (F = 9.77, p = 0.003). Conclusions: This study suggests applying an international training program based on blended learning to strengthen intelligence capabilities such as artificial intelligence capabilities. Full article
(This article belongs to the Special Issue ICTs in Education)
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31 pages, 16043 KiB  
Article
A Java Application for Teaching Graphs in Undergraduate Courses
by Violeta Migallón and José Penadés
Appl. Sci. 2023, 13(23), 12945; https://doi.org/10.3390/app132312945 - 04 Dec 2023
Viewed by 995
Abstract
Graph theory is a common topic that is introduced as part of the curricula of computing courses such as Computer Science, Computer Engineering, Data Science, Information Technology and Software Engineering. Understanding graphs is fundamental for solving many real-world problems, such as network routing, [...] Read more.
Graph theory is a common topic that is introduced as part of the curricula of computing courses such as Computer Science, Computer Engineering, Data Science, Information Technology and Software Engineering. Understanding graphs is fundamental for solving many real-world problems, such as network routing, social network analysis, and circuit design; however, many students struggle to grasp the concepts of graph theory, as they often have difficulties in visualising and manipulating graphs. To overcome these difficulties, educational software can be used to aid in the teaching and learning of graph theory. This work focuses on the development of a Java system for graph visualisation and computation, called MaGraDa (Graphs for Discrete Mathematics), that can help both students and teachers of undergraduate or high school courses that include concepts and algorithms related to graphs. A survey on the use of this tool was conducted to explore the satisfaction level of students on a Discrete Mathematics course taken as part of a Computer Engineering degree at the University of Alicante (Spain). An analysis of the results showed that this educational software had the potential to enhance students’ understanding of graph theory and could enable them to apply these concepts to solve practical problems in the field of computer science. In addition, it was shown to facilitate self-learning and to have a significant impact on their academic performance. Full article
(This article belongs to the Special Issue ICTs in Education)
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26 pages, 1339 KiB  
Article
Applying Design Thinking to Enhance Programming Education in Vocational and Compulsory Secondary Schools
by Belkis Díaz-Lauzurica and David Moreno-Salinas
Appl. Sci. 2023, 13(23), 12792; https://doi.org/10.3390/app132312792 - 29 Nov 2023
Viewed by 815
Abstract
A proper and complete formation in technology (science, communications, programming, robotics, Computational Thinking, etc.) must be imparted at all educational levels for a lifelong education. However, students may lose motivation or interest due to the complexity and abstraction of some of the concepts [...] Read more.
A proper and complete formation in technology (science, communications, programming, robotics, Computational Thinking, etc.) must be imparted at all educational levels for a lifelong education. However, students may lose motivation or interest due to the complexity and abstraction of some of the concepts imparted. In line with this, the work at hand looks to improve the interest and commitment of students by presenting the programming concepts and contents in a practical way. The teaching–learning process is based on the development of projects about robotics, which are adapted for courses and groups of different educational levels. The Design Thinking methodology is used to impart the content. This methodology allows the students to experiment, design and test different solutions for a given problem, increasing their motivation and interest, promoting creativity, and making the students conscious of their learning process. Two different projects are considered, a simulated one based on a sensor network to localise and track a robot in a closed area for vocational education students, and an experimental one about constructing a robot with several capabilities using Lego Mindstorms for compulsory secondary education students. The results obtained over three different groups of students are analysed and compared, and show that the methodology and projects selected can be adopted and adapted for different educational levels, increasing the proficiency of the students, their development, motivation and self-learning despite the difficulty and complexity of some concepts related to computer science. Full article
(This article belongs to the Special Issue ICTs in Education)
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27 pages, 9388 KiB  
Article
GPT-Empowered Personalized eLearning System for Programming Languages
by Jennifer Jin and Mira Kim
Appl. Sci. 2023, 13(23), 12773; https://doi.org/10.3390/app132312773 - 28 Nov 2023
Viewed by 1255
Abstract
The eLearning approach to programming language instruction has gained widespread acceptance due to advantages such as accessibility, temporal flexibility, and content reusability. However, the current eLearning for programming predominantly employs the delivery of one-size-fits-all content, engendering elevated costs in both the development of [...] Read more.
The eLearning approach to programming language instruction has gained widespread acceptance due to advantages such as accessibility, temporal flexibility, and content reusability. However, the current eLearning for programming predominantly employs the delivery of one-size-fits-all content, engendering elevated costs in both the development of language coursework and administration of eLearning sessions, which includes the labor-intensive task of grading student submissions. A compelling research question to consider is how to construct an eLearning system capable of delivering personalized, student-centric content, automating the generation of coursework elements, and eliminating the need for instructor involvement in the management of eLearning sessions. Our approach to delivering a definite solution to the question involves the utilization of a suite of advanced software technologies: GPT to dynamically generate course contents/components, prompt engineering to personalize course content for each individual student, and autonomous computing to manage eLearning sessions without the need for human intervention. The research results encompass the design of an eLearning framework covering all programming languages, a fully functional Python-based implementation, seamless integration with ChatGPT for dynamic content generation, a high degree of content personalization, and the elimination of manual effort required for managing eLearning sessions. Full article
(This article belongs to the Special Issue ICTs in Education)
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16 pages, 3602 KiB  
Article
Effect of Block-Based Python Programming Environment on Programming Learning
by Yongcheon Kim, Jamee Kim and Wongyu Lee
Appl. Sci. 2023, 13(19), 10898; https://doi.org/10.3390/app131910898 - 30 Sep 2023
Viewed by 1014
Abstract
The advancement of computing technology has led to many changes in a variety of fields, and the importance of programming education has been emphasized in many countries worldwide. Despite the importance of programming education, the cognitive burden of text programming for beginners has [...] Read more.
The advancement of computing technology has led to many changes in a variety of fields, and the importance of programming education has been emphasized in many countries worldwide. Despite the importance of programming education, the cognitive burden of text programming for beginners has not been reduced. The goal of this study was to implement an environment where a text programming language is used in a block-based programming environment and to determine at which school level this learning environment affects positive perceptions of programming. To achieve this goal, we conducted programming classes targeting 128 middle school, high school, and university students for 14 weeks and analyzed the effects of the factors of “understanding of programming instructions”, “usage confidence”, and “usefulness” on “positive perceptions of programming”. The results of the analysis by school level show that “usefulness” influenced positivity toward programming for middle school students, “usefulness” and “understanding of programming instruction” for high school students, and “understanding of programming instruction” and “usage confidence” for university students. Therefore, the significance of this study confirms the need to construct the learning environment differently depending on school level, even for beginners. Full article
(This article belongs to the Special Issue ICTs in Education)
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29 pages, 1984 KiB  
Article
Analyzing the Alignment between AI Curriculum and AI Textbooks through Text Mining
by Hyeji Yang, Jamee Kim and Wongyu Lee
Appl. Sci. 2023, 13(18), 10011; https://doi.org/10.3390/app131810011 - 05 Sep 2023
Viewed by 2360
Abstract
The field of artificial intelligence (AI) is permeating education worldwide, reflecting societal changes driven by advancements in computing technology and the data revolution. Herein, we analyze the alignment between core AI educational curricula and textbooks to provide guidance on structuring AI knowledge. Text [...] Read more.
The field of artificial intelligence (AI) is permeating education worldwide, reflecting societal changes driven by advancements in computing technology and the data revolution. Herein, we analyze the alignment between core AI educational curricula and textbooks to provide guidance on structuring AI knowledge. Text mining techniques using Python 3.10.3 and frame-based content analysis tailored to the computing field are employed to examine a substantial amount of text data within educational curriculum textbooks. We comprehensively examine the frequency of knowledge incorporated in AI curricula, topic structure, and practical tool utilization. The degree to which keywords are reflected in curriculum textbooks and in the textbook characteristics are determined using Term Frequency (TF) and Term Frequency-Inverse Document Frequency (TF-IDF) analysis, respectively. The topic structure distribution is derived by Latent Dirichlet Allocation (LDA) topic modeling and the trained model is visualized using PyLDAvis. Furthermore, the variation in vertical content range or level is investigated by content analysis, considering the tools used to teach similar AI knowledge. Lastly, the implications for AI curriculum structure are discussed in terms of curriculum composition, knowledge construction, practical application, and curriculum utilization. This study provides practical guidance for structuring curricula that effectively foster AI competency based on a systematic research methodology. Full article
(This article belongs to the Special Issue ICTs in Education)
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18 pages, 780 KiB  
Article
An Adaptive Cybersecurity Training Framework for the Education of Social Media Users at Work
by Fai Ben Salamah, Marco A. Palomino, Matthew J. Craven, Maria Papadaki and Steven Furnell
Appl. Sci. 2023, 13(17), 9595; https://doi.org/10.3390/app13179595 - 24 Aug 2023
Viewed by 1513
Abstract
Formalizing the approach towards risk management on social media is critical for organizations. Regrettably, a review of the state-of-the-art on cybersecurity training highlighted that the existing frameworks are either too generic or too cumbersome to be adapted to different organizations and needs. Thus, [...] Read more.
Formalizing the approach towards risk management on social media is critical for organizations. Regrettably, a review of the state-of-the-art on cybersecurity training highlighted that the existing frameworks are either too generic or too cumbersome to be adapted to different organizations and needs. Thus, we developed the Adaptive Cybersecurity Training Framework for Social Media Risks (ACSTF-SMR), a framework that incorporates social media cybersecurity policies and best practices. The ACSTF-SMR enables organizations, trainers, and policymakers to address the challenges posed by social media in a way that satisfies employees’ training needs and adjusts to their preferences. We tested the ACSTF-SMR with 38 case studies. Employees’ behaviors, learning, and responses after training were assessed, and feedback was gathered to improve the framework. Interviews with policymakers were held to gain insight into the enforcement of social media policies. We conclude that the ACSTF-SMR is a reliable option to mitigate social media threats within organizations. Full article
(This article belongs to the Special Issue ICTs in Education)
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26 pages, 914 KiB  
Article
Software Development and Tool Support for Curriculum Design: A Systematic Mapping Study
by Aliwen Melillán, Ania Cravero and Samuel Sepúlveda
Appl. Sci. 2023, 13(13), 7711; https://doi.org/10.3390/app13137711 - 29 Jun 2023
Viewed by 1615
Abstract
Curriculum design is the systematic process of establishing how a learning process is designed, developed, supported, and delivered. This process is supported by software tools which can help improve curriculum alignment and facilitate the design of courses or programs. This article aims to [...] Read more.
Curriculum design is the systematic process of establishing how a learning process is designed, developed, supported, and delivered. This process is supported by software tools which can help improve curriculum alignment and facilitate the design of courses or programs. This article aims to analyze software proposals for curriculum design support that consider using models, methods, and techniques in software development. To do this, a systematic mapping of studies was conducted, including six research questions. This study includes 45 articles published from 2011 to 2022. The results indicate that 60% use some model, method, or technique in software development. Most software uses some models, such as ontologies, UML diagrams, or IMS-1D models. Although most articles use some model, method, or technique, there is a lack of use of software engineering models such as UML diagrams, which are standard in the software industry and research. Full article
(This article belongs to the Special Issue ICTs in Education)
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15 pages, 570 KiB  
Article
Exploring the Potential Impact of Artificial Intelligence (AI) on International Students in Higher Education: Generative AI, Chatbots, Analytics, and International Student Success
by Ting Wang, Brady D. Lund, Agostino Marengo, Alessandro Pagano, Nishith Reddy Mannuru, Zoë A. Teel and Jenny Pange
Appl. Sci. 2023, 13(11), 6716; https://doi.org/10.3390/app13116716 - 31 May 2023
Cited by 21 | Viewed by 27650
Abstract
International students face unique challenges in pursuing higher education in a foreign country. To address these challenges and enhance their academic experience, higher education institutions are increasingly exploring the use of artificial intelligence (AI) applications. This research essay aims to investigate the impact [...] Read more.
International students face unique challenges in pursuing higher education in a foreign country. To address these challenges and enhance their academic experience, higher education institutions are increasingly exploring the use of artificial intelligence (AI) applications. This research essay aims to investigate the impact of AI on the education of international students. Instead of a traditional literature review, it employs a research approach to examine the potential applications of AI and discuss associated concerns. The research paper explores various AI applications, such as personalized learning experiences, adaptive testing, predictive analytics, and chatbots for learning and research. By analyzing the role of AI in education for international students, this research paper sheds light on how AI can improve learning efficiency and provide customized educational support. Additionally, it identifies significant risks and limitations, including privacy concerns, cultural differences, language proficiency, and ethical implications, which must be effectively addressed. The findings contribute to a better understanding of the potential impact of AI on international students’ educational experiences and offer insights into the integration of AI into educational administration and learning processes. Full article
(This article belongs to the Special Issue ICTs in Education)
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