Using Web-Based Technologies and Communities of Practice for Transformative Hybrid and Distance Education

2010 ◽  
pp. 156-166
Author(s):  
Nory Jones ◽  
Omar J. Khan
Keyword(s):  
Social Networks ◽  
Distance Education ◽  
Learning Styles ◽  
Communities Of Practice ◽  
Web 2.0 ◽  
Learning Environments ◽  
Learning Experience ◽  
Online Classes ◽  
Web Based

This chapter explores the use of Web-based technologies incorporating communities of practice and social networks to enhance the learning experience in hybrid and distance (online) classes. Research suggests that using a variety of technologies and methods to reach people with different learning styles improves overall learning in a class delivery though different methods are more effective in traditional vs. online classes. Moreover, using new, emerging Web-based technologies, including both Web 1.0 and Web 2.0 software, further enhances the engagement and value of the learning experience in these classes. This chapter examines the methods and technologies that can be potentially used to create excellence learning environments in traditional hybrid and online classes.

Individual Learning and Emotional Characteristics in Web-based Communities of Practice

2010 ◽  
pp. 113-127
Author(s):  
Nikos Tsianos ◽  
Zacharias Lekkas ◽  
Panagiotis Germanakos ◽  
Constantinos Mourlas
Keyword(s):  
Learning Styles ◽  
Communities Of Practice ◽  
Learning Environments ◽  
Learning Style ◽  
Individual Characteristics ◽  
Web Based ◽  
Shared Learning ◽  
Processing Styles ◽  
Theoretical Assumptions

The knowledge management paradigm of communities of practice can be efficiently realized in Web-based environments, especially if one considers the extended social networks that have proliferated within the Internet. In terms of increasing performance through the exchange of knowledge and shared learning, individual characteristics, such as learners’ preferences that relate to group working, may be of high importance. These preferences have been summarized in cognitive and learning styles typologies, as well as emotional characteristics which define implications that could serve as personalization guidelines for designing collaborative learning environments. This chapter discusses the theoretical assumptions of two distinct families of learning style models, cognitive personality and information processing styles (according to Curry’s onion model), and the role of affection and emotion, in order to explore the possibilities of personalization at the group level of CoP.

The Impact of Web 2.0 Technologies on the Learning Experience of Students in Higher Education

2018 ◽  
Vol 13 (3) ◽  
pp. 1-17 ◽  
Author(s):  
Afaf Mubarak Bugawa ◽  
Andri Mirzal
Keyword(s):  
Higher Education ◽  
Social Networks ◽  
Web 2.0 ◽  
Student Learning ◽  
Learning Experience ◽  
Learning Experiences ◽  
Traditional Classrooms ◽  
Web 2.0 Technologies ◽  
The Impact

This article describes how the use of Web 2.0 technologies in the field of learning is on the rise. By their nature, Web 2.0 technologies increase the interactivity between users where interactivity is considered to be a key to success in traditional classrooms. This article reviews recent studies in the field of Web 2.0 technologies for learning and their impacts on the learning experiences and investigates relationship between Web 2.0 technologies and pedagogy in higher education on student learning. Key findings about the impacts of using social networks like Facebook, Twitter, blogs and wikis on learning experiences are also discussed. Web 2.0 technologies' characteristics and the rationale of Web 2.0 technologies in learning will also be explored.

Development of Adaptive Social Network Based on Learners' Thinking and Learning Styles

2018 ◽  
pp. 90-107
Author(s):  
Mahnane Lamia ◽  
Hafidi Mohamed
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Learning Styles ◽  
Learning Experience ◽  
Social Network Sites ◽  
Innovative Approach ◽  
Thinking Styles ◽  
New Approach ◽  
Learning Content ◽  
Web Learning

Adaptive social network sites (ASNS) are an innovative approach to a web learning experience delivery. They try to solve the main shortcomings of classical social networks—“one-size-fits-all” approach and “lost-in-hyperspace” phenomena—by adapting the learning content and its presentation to needs, goals, thinking styles, and learning styles of every individual learner. This chapter outlines a new approach to automatically detect learners' thinking and learning styles, and takes into account that thinking and learning styles may change during the learning process in unexpected and unpredictable ways. The approach is based on the Felder learning styles model and Hermann thinking styles model.

Designing Web-Based Educational Virtual Reality Environments

2010 ◽  
pp. 157-178 ◽  
Author(s):  
Kosmas Dimitropoulos ◽  
Athanasios Manitsaris
Keyword(s):  
Distance Education ◽  
Virtual Reality ◽  
Learning Environments ◽  
World Wide ◽  
Virtual Learning Environments ◽  
Virtual Reality Technology ◽  
Web Based ◽  
Learning Content ◽  
The Web

This chapter aims to study the benefits that arise from the use of virtual reality technology and World Wide Web in the field of distance education, as well as to further explore the role of instructors and learners in such a network-centric mode of education. Within this framework, special emphasis is given on the design and development of web-based virtual learning environments so as to successfully fulfil their educational objectives. In particular, the chapter includes research on distance education on the Web and the role of virtual reality, as well as study on basic pedagogical methods focusing mainly on the efficient preparation, approach and presentation of the learning content. Moreover, specific designing rules are presented considering the hypermedia, virtual and educational nature of this kind of applications. Finally, an innovative virtual reality environment for distance education in medicine, which reproduces conditions of the real learning process and enhances learning through a real-time interactive simulator, is demonstrated.

scholarly journals Web-based Learning Environments: Do Libraries Matter?

2000 ◽  
Vol 61 (4) ◽  
pp. 367-379 ◽  
Author(s):  
Donald Beagle
Keyword(s):  
Distance Education ◽  
Learning Environments ◽  
Web Sites ◽  
Instructional Support ◽  
Active Role ◽  
Course Delivery ◽  
Resource Integration ◽  
Web Based ◽  
Web Based Learning

Web-based learning environments are becoming more widely used for on-campus and distance education course delivery. A review of articles on the topic by faculty shows that only a few mention issues related to library access or resource integration. Moreover, only a small number of courseware evaluations posted on academic Web sites include criteria related to libraries. However, a few articles and reviews share common themes that point to a greater library involvement in courseware implementation, which is consistent with arguments made by distance education librarians calling for an active role in technical, pedagogical, and instructional support decisions concerning Web-based learning environments.

scholarly journals Social Networks in Regulation Learning Process Quality

2015 ◽  
Vol 1 ◽  
pp. 271
Author(s):  
Rūdolfs Gulbis
Keyword(s):  
Social Networks ◽  
Learning Environments ◽  
Virtual Learning Environments ◽  
Learning Approaches ◽  
Learning Tools ◽  
Discussion Forums ◽  
Key Factors ◽  
Web Based ◽  
Web Based Learning

<p>Successful web-based learning depends on several key factors. These include the quality of the learning tools, the motivation of users, and the credibility of the learning materials as well as their significance in the eyes of users. It is possible to find numerous examples of web-based lifelong learning approaches that can be viewed on social networks and discussion forums. The research for this study included designing several blog-based discussion forums where user activities were logged and the results were compared to usercompleted questionnaires for similar activities. Several user behaviour identification models were designed based on algorithmically computed tallies of user behaviours. These models are currently being applied for further study to measure user behaviours in virtual learning environments.</p>

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