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Future Internet
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Artificial Neural Networks for Educational Data Mining in Higher Education
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Artificial Neural Networks for Educational Data Mining in Higher Education

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Big Data and Augmented Intelligence".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 9137

Special Issue Editor

Dr. Rytis Maskeliūnas

E-Mail Website
Guest Editor
Department of Multimedia Technologies, Kaunas University of Technology, 51311 Kaunas, Lithuania
Interests: artificial intelligence; signal processing; computer vision; human–machine interfaces
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Collegues, 

In a way that no other factor has done before, COVID-19 has most significantly moved focus to educational issues related to digitally enhanced distance learning. Efforts to raise the bar of education in order to adapt to the changing needs of society and industry have sparked a slew of educational data mining efforts. 

This Special Issue intends to encourage contributions that address the implementations and challenges of artificial intelligence-based analysis (but not limited to this) of massive amounts of data from academic institutions in today's distance education situations, especially the way they have had to adapt due to the pandemic. Harnessing data bias, augmenting traditional data media converted for distance learning, innovative digital ways to promote data-intensive adaptive learning, data-driven techniques to aid improve student retention, student development, and general cost savings in remote education are the primary topics of interest. This Special Issue also looks at state-of-the-art reviews and artificial intelligence applications for successfully recognizing learning behaviour, dynamically reacting to it and properly anticipating change in performance through machine learning.

Finally, I would like to thank Prof. Sanjay Misra and his valuable work for assisting me with this Special Issue.

Dr. Rytis Maskeliūnas
Guest Editor

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. Future Internet is an international peer-reviewed open access monthly 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 1600 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

  • Artificial Neural Networks
  • Data Mining
  • Higher Education

Published Papers (3 papers)

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Research

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18 pages, 326 KiB  
Article
Teachers’ Views on Integrating Augmented Reality in Education: Needs, Opportunities, Challenges and Recommendations
by Maria Perifanou, Anastasios A. Economides and Stavros A. Nikou
Future Internet 2023, 15(1), 20; https://0-doi-org.brum.beds.ac.uk/10.3390/fi15010020 - 29 Dec 2022
Cited by 13 | Viewed by 4339
Abstract
The integration of augmented reality (AR) in education is promising since it enhances teaching and offers more engaging and appealing learning experiences. Teachers can have a catalytic role towards the adoption of AR in education; therefore, their perspectives with regard to AR in [...] Read more.
The integration of augmented reality (AR) in education is promising since it enhances teaching and offers more engaging and appealing learning experiences. Teachers can have a catalytic role towards the adoption of AR in education; therefore, their perspectives with regard to AR in teaching and learning are very important. The current study explores teachers’ views on the integration of AR in education through an open-ended questionnaire that has been answered by 93 educators worldwide. A set of digital skills that can support student-centered pedagogies in an appropriate infrastructure are the main requirement for effective teaching with AR. Among the perceived benefits and opportunities are interactive teaching and learning, increased interest and engagement, better understanding of complex concepts. As barriers, participants reported the lack of AR educational applications, the cost of buying and maintaining AR equipment and resources, the lack of teachers’ and students’ digital skills, classroom management issues, and security and ethical issues. Moreover, survey participants highlighted the need for raising teachers’ awareness for the added value of AR in education and the need for teachers’ continuous professional development. Implications and future research recommendations on the integration of AR in education are discussed. Full article
(This article belongs to the Special Issue Artificial Neural Networks for Educational Data Mining in Higher Education)
18 pages, 2808 KiB  
Article
Assistance System for the Teaching of Natural Numbers to Preschool Children with the Use of Artificial Intelligence Algorithms
by William Villegas-Ch., Angel Jaramillo-Alcázar and Aracely Mera-Navarrete
Future Internet 2022, 14(9), 266; https://doi.org/10.3390/fi14090266 - 15 Sep 2022
Cited by 2 | Viewed by 1479
Abstract
This research was aimed at designing an image recognition system that can help increase children’s interest in learning natural numbers between 0 and 9. The research method used was qualitative descriptive, observing early childhood learning in a face-to-face education model, especially in the [...] Read more.
This research was aimed at designing an image recognition system that can help increase children’s interest in learning natural numbers between 0 and 9. The research method used was qualitative descriptive, observing early childhood learning in a face-to-face education model, especially in the learning of numbers, with additional data from literature studies. For the development of the system, the cascade method was used, consisting of three stages: identification of the population, design of the artificial intelligence architecture, and implementation of the recognition system. The method of the system sought to replicate a mechanic that simulates a game, whereby the child trains the artificial intelligence algorithm such that it recognizes the numbers that the child draws on a blackboard. The system is expected to help increase the ability of children in their interest to learn numbers and identify the meaning of quantities to help improve teaching success with a fun and engaging teaching method for children. The implementation of learning in this system is expected to make it easier for children to learn to write, read, and conceive the quantities of numbers, in addition to exploring their potential, creativity, and interest in learning, with the use of technologies. Full article
(This article belongs to the Special Issue Artificial Neural Networks for Educational Data Mining in Higher Education)
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Review

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16 pages, 987 KiB  
Review
Gamification with Scratch or App Inventor in Higher Education: A Systematic Review
by David Pérez-Jorge and María Carmen Martínez-Murciano
Future Internet 2022, 14(12), 374; https://0-doi-org.brum.beds.ac.uk/10.3390/fi14120374 - 13 Dec 2022
Cited by 5 | Viewed by 2763
Abstract
Programming skills should be taught and developed; Scratch and App Inventor are two tools that can contribute significantly to developing this competence in university students. This study aims to investigate the use and effect of the programming language Scratch and App Inventor on [...] Read more.
Programming skills should be taught and developed; Scratch and App Inventor are two tools that can contribute significantly to developing this competence in university students. This study aims to investigate the use and effect of the programming language Scratch and App Inventor on the development of skills and competencies for learning (autonomy, attention, motivation, critical thinking, creative thinking, computational thinking, communication, problem solving and social interaction) in higher education. To achieve this goal, a systematic review of articles in English and Spanish was carried out using the PRISMA statement (research publication guidelines designed to improve the integrity of systematic review and meta-analysis reports). A search for studies was conducted in the Web of Science (WOS), Dialnet, and SCOPUS. A total of 405 papers were analyzed, of which 11 were finally selected. The results showed that both Scratch and App Inventor favor the development of skills and competencies for learning in the context of higher education, despite being underutilized strategies that all knowledge disciplines should promote. Full article
(This article belongs to the Special Issue Artificial Neural Networks for Educational Data Mining in Higher Education)
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