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Future Internet
Special Issues
Technology Enhanced Learning and Mobile Learning
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Technology Enhanced Learning and Mobile Learning

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Smart System Infrastructure and Applications".

Deadline for manuscript submissions: closed (10 June 2022)

Special Issue Editor

Dr. Stavros A. Nikou

E-Mail Website
Guest Editor
School of Education, University of Strathclyde, Glasgow, UK
Interests: technology-enhanced teaching and learning; assessment; context-aware mobile learning; blended learning; teacher education, computational thinking; emerging technologies in STEM education

Special Issue Information

Dear Colleagues,

Teaching and Learning have always been influenced by technologies. However, thanks to the advancements in digital technologies, technology enhanced learning has seen a significant growth as means to improve learning experiences in a wide range of formal and informal settings. Digital systems can offer a series of capabilities to education, facilitate educational delivery, promote motivation and engagement and contribute to more efficient and effective learning. Along with the technological advancements, new pedagogical frameworks and instructional models that harness the affordances of emerging educational technologies have been considered. Moreover, online learning has become the delivery of choice for educational institutions worldwide due to the recent social distancing imposed by the pandemic. One of the research and development fields of interest that has been emerged during the last years is mobile learning: learning across contexts using mobile devices. Context aware ubiquitous learning is growing as means to support learners moving across locations, time, and social interactions.

The special issue “Technology Enhanced Learning and Mobile Learning” aims to continue and promote the discussion about technology supported learning environments and therefore invites original papers focusing on the latest developments in educational technologies and related pedagogies. Special focus will be given on mobile learning.  Researchers and practitioners are invited to share their latest research work and experience in the area of improving teaching and learning with the help of digital technologies.

The topics include, but are not limited to:

  1. Online and blended learning environments
  2. Mobile learning
  3. Context-aware and ubiquitous learning
  4. Adaptive and personalised learning
  5. Smart learning environments
  6. Artificial Intelligence in Education
  7. VR/AR/XR educational applications
  8. Game-based learning and gamification
  9. Learning analytics
  10. Technology enhanced STEM education
  11. Technology supported assessment methodologies
  12. Domain applications and case studies
  13. Instructional design an learning design with digital technologies
  14. Pedagogical aspects of technology enhanced learning environments
  15. Social aspects of technology enhanced learning environments  

Dr. Stavros A. Nikou
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at mdpi.longhoe.net 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.

Dr. Stavros A. Nikou
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at mdpi.longhoe.net 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

  • technology-enhanced learning
  • online and blended learning
  • mobile learning
  • instructional design with technology

Published Papers (2 papers)

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Research

20 pages, 599 KiB  
Article
A Performance Comparison of Different Cloud-Based Natural Language Understanding Services for an Italian e-Learning Platform
by Matteo Zubani, Luca Sigalini, Ivan Serina, Luca Putelli, Alfonso E. Gerevini and Mattia Chiari
Future Internet 2022, 14(2), 62; https://doi.org/10.3390/fi14020062 - 18 Feb 2022
Cited by 8 | Viewed by 2954
Abstract
During the COVID-19 pandemic, the corporate online training sector has increased exponentially and online course providers had to implement innovative solutions to be more efficient and provide a satisfactory service. This paper considers a real case study in implementing a chatbot, which answers [...] Read more.
During the COVID-19 pandemic, the corporate online training sector has increased exponentially and online course providers had to implement innovative solutions to be more efficient and provide a satisfactory service. This paper considers a real case study in implementing a chatbot, which answers frequently asked questions from learners on an Italian e-learning platform that provides workplace safety courses to several business customers. Having to respond quickly to the increase in the courses activated, the company decided to develop a chatbot using a cloud-based service currently available on the market. These services are based on Natural Language Understanding (NLU) engines, which deal with identifying information such as entities and intentions from the sentences provided as input. To integrate a chatbot in an e-learning platform, we studied the performance of the intent recognition task of the major NLU platforms available on the market with an in-depth comparison, using an Italian dataset provided by the owner of the e-learning platform. We focused on intent recognition, carried out several experiments and evaluated performance in terms of F-score, error rate, response time, and robustness of all the services selected. The chatbot is currently in production, therefore we present a description of the system implemented and its results on the original users’ requests. Full article
(This article belongs to the Special Issue Technology Enhanced Learning and Mobile Learning)
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15 pages, 1896 KiB  
Article
A Framework for Mobile-Assisted Formative Assessment to Promote Students’ Self-Determination
by Stavros A. Nikou and Anastasios A. Economides
Future Internet 2021, 13(5), 116; https://doi.org/10.3390/fi13050116 - 30 Apr 2021
Cited by 11 | Viewed by 3792
Abstract
Motivation is an important issue to consider when designing learning activities, including mobile learning and assessment. While previous research provides evidence for the motivational impact of mobile learning, not many pedagogical frameworks exist for the design of mobile-assisted learning and assessment. The current [...] Read more.
Motivation is an important issue to consider when designing learning activities, including mobile learning and assessment. While previous research provides evidence for the motivational impact of mobile learning, not many pedagogical frameworks exist for the design of mobile-assisted learning and assessment. The current study is grounded in the Self-Determination Theory of motivation and proposes a pedagogical framework for mobile-assisted formative assessment, aiming at enhancing student motivation. For a preliminary evaluation of the framework, fifty-one students from a public European high school participated in a series of formative assessment activities. The tasks that were implemented according to the proposed mobile-based formative assessment framework had a significant positive impact on student perceived levels of autonomy, competence, and relatedness, enhancing students’ intrinsic motivation levels. Study findings highlighted the capacity of the proposed framework to guide the design of mobile-based formative assessment activities that enhance and promote student motivation. The study makes a theoretical contribution by proposing a framework that aligns mobile learning and assessment with elements of the Self-Determination Theory of motivation and also has a practical contribution by implementing mobile learning and assessment practices that have the potential to promote student motivation. Full article
(This article belongs to the Special Issue Technology Enhanced Learning and Mobile Learning)
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