Digital Learning: Exploring the Use of Educational Technology in Educational Environments

A special issue of Education Sciences (ISSN 2227-7102). This special issue belongs to the section "Technology Enhanced Education".

Deadline for manuscript submissions: closed (20 January 2024) | Viewed by 58172

Special Issue Editor


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Guest Editor
Department of Education, Chonnam National University, Gwangju 61186, Republic of Korea
Interests: multimedia for language acquisition; multimedia design for educational purposes; virtual humans in computer-based environments; cognitive load in multimedia environments; social presence of virtual humans; virtual human gesture production and learning; virtual reality in education

Special Issue Information

Dear Colleagues,

Digital technologies have greatly changed education, introducing online learning that has made education more accessible to all ages and people all over the world. The growing emphasis on educational technology continues to change traditional teaching methods and requires a continuous exploration of its effectiveness and influence on learning outcomes. This research area is growing in importance due to the increasing implementation of digital learning, especially after global events such as the COVID-19 pandemic that required a quick shift to online education. Due to the rapidly changing nature of technology, it is important that research continues to assess and evaluate the use of technology in educational environments.

The aim of this Special Issue is to explore of the use of educational technology in various educational environments. This subject aligns with the journal's scope to provide inclusive and equitable access to research. By focusing on educational technology in online and classroom environments, this Special Issue seeks to contribute to an understanding of how digital tools and platforms are shaping learning experiences, outcomes and the broader educational landscape.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:

  • design and implementation of online courses: best practices, challenges and innovations;
  • design of multimedia environments: research on a wide range of design elements in multimedia environments;
  • the role of AI in education: the use of artificial intelligence in personalizing learning and assessment;
  • digital tools and platforms: the evaluation of existing tools and the development of new ones;
  • virtual and augmented reality: the impact of VR, AR and XR on education;
  • learning analytics: the use of data to enhance learning outcomes.

I/We look forward to receiving your contributions.

Prof. Dr. Robert Otto Davis
Guest Editor

Manuscript Submission Information

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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 double-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Education Sciences 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 1800 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

  • educational technology
  • online learning
  • artificial intelligence in education
  • virtual and augmented reality in education
  • digital tools and platforms
  • learning analytics
  • adaptive learning systems
  • policy and regulation in digital education
  • multimedia learning environments

Published Papers (5 papers)

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Research

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17 pages, 2900 KiB  
Article
The Impact of Teachable Machine on Middle School Teachers’ Perceptions of Science Lessons after Professional Development
by Terri L. Kurz, Suren Jayasuriya, Kimberlee Swisher, John Mativo, Ramana Pidaparti and Dawn T. Robinson
Educ. Sci. 2024, 14(4), 417; https://doi.org/10.3390/educsci14040417 - 16 Apr 2024
Viewed by 258
Abstract
Technological advances in computer vision and machine learning image and audio classification will continue to improve and evolve. Despite their prevalence, teachers feel ill-prepared to use these technologies to support their students’ learning. To address this, in-service middle school teachers participated in professional [...] Read more.
Technological advances in computer vision and machine learning image and audio classification will continue to improve and evolve. Despite their prevalence, teachers feel ill-prepared to use these technologies to support their students’ learning. To address this, in-service middle school teachers participated in professional development, and middle school students participated in summer camp experiences that included the use of Google’s Teachable Machine, an easy-to-use interface for training machine learning classification models. An overview of Teachable Machine is provided. As well, lessons that highlight the use of Teachable Machine in middle school science are explained. Framed within Personal Construct Theory, an analysis of the impact of the professional development on middle school teachers’ perceptions (n = 17) of science lessons and activities is provided. Implications for future practice and future research are described. Full article
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16 pages, 722 KiB  
Article
Social Media Influence on Students’ Knowledge Sharing and Learning: An Empirical Study
by Arunkumar Sivakumar, Sudarsan Jayasingh and Shahenaz Shaik
Educ. Sci. 2023, 13(7), 745; https://doi.org/10.3390/educsci13070745 - 20 Jul 2023
Cited by 8 | Viewed by 38896
Abstract
Social media brought new opportunities not only for entertainment and marketing but also for knowledge sharing and learning. This research attempted to examine the effectiveness of social media as an educational tool and its impact on knowledge sharing among college and university students. [...] Read more.
Social media brought new opportunities not only for entertainment and marketing but also for knowledge sharing and learning. This research attempted to examine the effectiveness of social media as an educational tool and its impact on knowledge sharing among college and university students. The study used social cognitive and connective theories to develop a model that examines the influence of personal motivations (such as reputation) and social networking features (such as file sharing and student engagement) on information sharing. The study concluded that social media can promote knowledge sharing and can increase student motivation and performance. The findings suggest that social networking is a valuable method of information dissemination and can be used to encourage student engagement. The article also provides implications, restrictions, and future research directions for using social media in education. This study provides valuable insights for educators and institutions looking to incorporate social media into their teaching and learning strategies. Full article
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12 pages, 859 KiB  
Case Report
Prompt: ChatGPT, Create My Course, Please!
by Robert O. Davis and Yong Jik Lee
Educ. Sci. 2024, 14(1), 24; https://doi.org/10.3390/educsci14010024 - 25 Dec 2023
Viewed by 2057
Abstract
The introduction of ChatGPT for public use has generated increasing interest among educational researchers in evaluating the utility of artificial intelligence (AI) in pedagogical settings. This study aims to contribute to this growing body of research by developing an entire course curriculum and [...] Read more.
The introduction of ChatGPT for public use has generated increasing interest among educational researchers in evaluating the utility of artificial intelligence (AI) in pedagogical settings. This study aims to contribute to this growing body of research by developing an entire course curriculum and lesson plans exclusively using ChatGPT. Case study findings support many of the affordances and limitations observed in previous studies, such as identifying appropriate topics and subtopics for lessons, as well as identifying the occurrence of hallucinations that fabricate data. This study also revealed new limitations in the design capabilities of ChatGPT. Specifically, lessons are designed as standalone units of information. Unlike human educators, AI lacks the ability to integrate prior lessons with current learning experiences or strategically prepare students for future learning outcomes. Understanding these affordances and limitations allows ChatGPT to be a useful tool for educators engaging in instructional design. Full article
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28 pages, 758 KiB  
Systematic Review
Adaptive Learning Using Artificial Intelligence in e-Learning: A Literature Review
by Ilie Gligorea, Marius Cioca, Romana Oancea, Andra-Teodora Gorski, Hortensia Gorski and Paul Tudorache
Educ. Sci. 2023, 13(12), 1216; https://doi.org/10.3390/educsci13121216 - 06 Dec 2023
Cited by 1 | Viewed by 12267
Abstract
The rapid evolution of e-learning platforms, propelled by advancements in artificial intelligence (AI) and machine learning (ML), presents a transformative potential in education. This dynamic landscape necessitates an exploration of AI/ML integration in adaptive learning systems to enhance educational outcomes. This study aims [...] Read more.
The rapid evolution of e-learning platforms, propelled by advancements in artificial intelligence (AI) and machine learning (ML), presents a transformative potential in education. This dynamic landscape necessitates an exploration of AI/ML integration in adaptive learning systems to enhance educational outcomes. This study aims to map the current utilization of AI/ML in e-learning for adaptive learning, elucidating the benefits and challenges of such integration and assessing its impact on student engagement, retention, and performance. A comprehensive literature review was conducted, focusing on articles published from 2010 onwards, to document the integration of AI/ML in e-learning. The review analyzed 63 articles, employing a systematic approach to evaluate the deployment of adaptive learning algorithms and their educational implications. Findings reveal that AI/ML algorithms are instrumental in personalizing learning experiences. These technologies have been shown to optimize learning paths, enhance engagement, and improve academic performance, with some studies reporting increased test scores. The integration of AI/ML in e-learning platforms significantly contributes to the personalization and effectiveness of the educational process. Despite challenges like data privacy and the complexity of AI/ML systems, the results underscore the potential of adaptive learning to revolutionize education by catering to individual learner needs. Full article
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17 pages, 480 KiB  
Systematic Review
Digital Learning and Self-Regulation in Students with Special Educational Needs: A Systematic Review of Current Research and Future Directions
by Aleksandra Stalmach, Paola D’Elia, Sergio Di Sano and Gino Casale
Educ. Sci. 2023, 13(10), 1051; https://doi.org/10.3390/educsci13101051 - 19 Oct 2023
Viewed by 3497
Abstract
Self-regulation plays a crucial role in the overall well-being of students, including those with learning disabilities (LD) and social, emotional, and behavioral disorders (SEBD). Conceptually, digital learning offers great potential for supporting students with special educational needs (SEN) in learning and social-emotional development [...] Read more.
Self-regulation plays a crucial role in the overall well-being of students, including those with learning disabilities (LD) and social, emotional, and behavioral disorders (SEBD). Conceptually, digital learning offers great potential for supporting students with special educational needs (SEN) in learning and social-emotional development at inclusive schools and can effectively promote self-regulation processes. This systematic review aims to shed light on the potential of digital learning to promote the self-regulation of students with SEN in inclusive contexts. A systematic literature search was conducted on selected databases. Seven studies met the inclusion criteria and were analyzed regarding the empirical evidence, characteristics of digital learning methods, and factors influencing their effectiveness. The results showed that digital learning methods can foster improvements in academic outcomes, e.g., students’ persuasive writing skills, and in enhancing emotion regulation in students. The effectiveness of the digital learning methods depends mostly on their implementation by teachers. Full article
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