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Information
Special Issues
The Evolutions of Blended Learning: New Forms of Mixed Learning
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The Evolutions of Blended Learning: New Forms of Mixed Learning

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Applications".

Deadline for manuscript submissions: closed (31 July 2021) | Viewed by 4175

Special Issue Editors

Prof. Dr. Pier Giuseppe Rossi

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Guest Editor
Full Professor, Education Department, University of Macerata, Macerata, Italy
Interests: TEL; post-digital; embodied cognition; third space; social robotic; blended learning; DEPIT
Prof. Dr. Chiara Panciroli

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Guest Editor
Associate Professor, Department of Education Studies "Giovanni Maria Bertin", University of Bologna, Italy
Interests: e-learning; didactics, technology enhanced learning; digital learning environments; visual learning; artificial intelligence
Prof. Dr. Livia Petti

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Guest Editor
Researcher, Human, Social Sciences and Education Department, University of Molise, Molise, Italy
Interests: e-learning; community online; didactics; teacher training; media education
Prof. Dr. Andrea Garavaglia

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Guest Editor
Associate Professor, Department of Philosophy, University of Milan, Milan, Italy
Interests: online learning; technology enhanced learning; media education; digital learning environments

Special Issue Information

Dear Colleagues,

The Covid-19 emergency has highlighted the weak points of blended learning. Before 2020, universities, schools, and training agencies had put forward and tested different forms of blended learning based on a balance between presence and distance for the same groups of students. We have been observing new and unusual ways to organize groups in teaching and learning activities, by means of new spaces, environments, and strategies. 

This Special Issue on the evolution of blended learning is addressed to researchers applying unconventional methods to teaching with technology.

The key areas of this Special Issue include the following:

e-learning models; teaching and methods activities; assessment; school equipment; university teaching; school teaching; inclusive teaching; learning environments; classroom interaction; learning design; learning objects; machine learning; predictive learning; school organization; university organization; and robotics.

Prof. Dr. Pier Giuseppe Rossi
Prof. Dr. Chiara Panciroli
Prof. Dr. Livia Petti
Prof. Dr. Andrea Garavaglia
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. Information 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

  • blended learning
  • online learning
  • emergency learning
  • hybrid learning
  • mixed learning

Published Papers (1 paper)

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Research

20 pages, 1185 KiB  
Article
From Traditional to VR-Based Online Education Platforms: A Model of the Mechanism Influencing User Migration
by Jing Chen, Chang Liu, Ronghua Chang, Pengfei Gui and Sanggyun Na
Information 2020, 11(9), 423; https://doi.org/10.3390/info11090423 - 31 Aug 2020
Cited by 8 | Viewed by 3417
Abstract
VR technology can help create optimal virtual learning spaces. Such spaces offer new visual experiences that break through the limitations of time and space and greatly stimulate people’s imagination and creativity in learning. Currently, the bandwidth required for such spaces limits the large-scale [...] Read more.
VR technology can help create optimal virtual learning spaces. Such spaces offer new visual experiences that break through the limitations of time and space and greatly stimulate people’s imagination and creativity in learning. Currently, the bandwidth required for such spaces limits the large-scale application of virtual reality (VR) technology for this purpose. With the large-scale deployment and application of high-speed networks, however, online education platforms based on VR technology will be better able to meet the diversified and personalized learning needs of learners. To promote the development and popularization of new online education platforms based on VR, the factors influencing the migration of learners from traditional online education platforms to new platforms need to be understood more clearly. A model based on the theory of negative, positive, and anchoring effects can explain learners’ migration behavior in this connection. To this end, a structural equation model based on the PLS variance algorithm was used to analyze data obtained through offline and online questionnaires. It was found that in terms of “negative effects”, the afunction and loyalty associated with traditional online education platforms reduced learners’ willingness to migrate to new platforms based on VR technology. In terms of “positive effects”, the novel interactivity and personalization brought by the new platform increased the willingness of users of traditional platforms to migrate to new platforms. In terms of “anchoring effects”, the system quality and relationship quality of learners’ use of traditional online education platforms, as well as the transfer costs associated with the new platform, generated learners’ risk perception about platform migration. In addition, risk perception not only negatively affects learners’ migration to the new platforms, but also strengthens their cognition of the system quality and relationship quality of the traditional platforms, while reducing their interactive awareness of those platforms. Therefore, by adjusting the psychological component of virtual learning, the online education platforms based on VR technology can create high-quality platforms migrating from traditional platforms. Full article
(This article belongs to the Special Issue The Evolutions of Blended Learning: New Forms of Mixed Learning)
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