Exploring factors of media characteristic influencing flow in learning through virtual worlds
Highlights
► This study aims to find out media characteristics influencing flow in virtual worlds. ► Distinct media characteristics of virtual worlds affecting flow were identified. ► The media characteristics are positively correlated to flow. ► Some media characteristics predict flow in learning through virtual worlds.
Introduction
The development and advent of emerging technologies has greatly impacted education by motivating new learners. It has also contributed to the creation of a new instructional paradigm. Recently, three-dimensional virtual worlds, where unlimited numbers of people can interact simultaneously within network-based simulated environments, have been emerging and have become popularity. More and more educators are debating its implications for teaching and learning. According to a recent survey, the number of users of virtual worlds has exceeded more than 1.8 billion people (Kzero corp, 2011). Gartner, Inc., a leading information technology research and advisory company, have stated that virtual worlds might be adopted mainstream for education within five to ten years (Gartner Inc, 2009).
Some researchers predict that this new media, virtual worlds, will bring major changes to the current instructional paradigm just as the Internet did in the past (Aldrich, 2009, Clarke and Dede, 2005, Zemsky and Massy, 2004). These same researchers are examining the educabilities of the emerging virtual worlds. As reflected in recent achievements, diverse research organizations such as the National Science Foundation (NSF), The New Media Consortium (NMC) and EDUCAUS have conducted several research projects associated with using virtual worlds for educational purpose. Other associations such as the AERA1, AECT2 and ISTE3 have organized a special group interested specifically in virtual worlds and they are conducting and sharing research on current issues in virtual worlds.
In spite of the prospects and consideration of the educability being given to virtual worlds, there is still a lack of empirical research about how learners progress within these environments (Jarmon et al., 2009, Oliver and Carr, 2009). Most researchers discuss the possibility and effectiveness of using this medium as an educational tool. However, little research focuses on how people learn within this environment and specifically how certain features relate to effective learning. Many researchers are interested in the levels of engagement with which virtual worlds provide students. However, some focus their research interests on learner variables such as attitudes, skills and stimulus level (Shen & Eder, 2009), while others are interested in teaching variables such as instructional designs and methods (Clarke and Dede, 2005, Omale et al., 2009, Wang and Hsu, 2009). Even though virtual worlds are media with characteristics distinct from other media, these characteristics have not drawn much attention from researchers. Thus, this research seeks to determine virtual worlds’ suitability as a learning environment through empirical inquiries as to how specific characteristics of virtual worlds affect student engagement. Prior to this determination, media characteristics should be identified and listed in terms of their influences on teaching and learning. Overall, this study aims to explore the media characteristics of virtual worlds influencing on engagement of residents and to determine the relationship between media characteristics and residents’ engagement in learning through virtual worlds.
Research questions are as below:
Question 1. What are the media characteristics affecting residents’ engagement in learning through virtual worlds?
Question 2. How are the media characteristics related to engagement in learning through virtual worlds?
Question 3. What are the comparative effects of media characteristics on residents’ engagement in learning through virtual worlds?
Section snippets
Possibilities and characteristics of virtual worlds in education
Being resident in a virtual environment has already become a daily routine for today’s youth (Oblinger and Oblinger, 2005, Prensky, 2001, Tapscott, 2009). Oblinger and Oblinger (2005) indicated them as ‘Millenials’ who have grown up with technology. Prensky (2001), also, identified them as ‘Digital natives’ who were born and live with digital technology. They spend much of their free time in virtual spaces including computer games, where they not only enjoy emotional satisfaction through
The definition and media characteristics of virtual Worlds
There are various definitions of virtual worlds. Aldrich (2009) explained this media as HIVEs (Highly Interactive Virtual Environments); including concept of games and simulations. The term MUVEs (Multi-User Virtual Environments) is used, because multiple users can interact with others synchronously. Bell (2008) indicated that the term of virtual worlds has been used in different ways to each field of study. Thus a common definition of this medium would help avoid misunderstandings. In this
Media and flow
The theory of flow has been conducted through studies in diverse fields since Csikszentmihalyi published this concept in his 1975 article. Since then, the computer, a new technology has emerged and many researchers have tried to apply flow theory to this new technology. Trevino and Webster (1992) who define this as an interaction with media describe how, “flow characterizes the perceived interaction with CMC technologies as more or less playful and exploratory” (p. 540). Novack and Hoffmann
Effectiveness of learning in virtual worlds
Ketelhut, Nelson, Dede, and Clarke (2006) designed a scientific experiment in the virtual environment, which was called ‘Rivercity’, in order to identify the effectiveness of virtual worlds as learning environments (see Fig. 2). They found the same effects in a virtual environment as in a real lab. They concluded that the virtual experiment is significant in its effectiveness in terms of instructional design. Teachers and students who participated in this inquiry recognized this environment as
Participants
One hundred ninety eight elementary students who are eleven to twelve years old participated in this study. Questionnaires for analyzing data were administered to one hundred twenty participants to satisfy minimum numbers for factor analysis. Seventeen participants’ responses were not relevant for analysis, so one hundred three participants’ data were used for factor analysis to identify factors’ validity of the relationship between media characteristics and flow. After the exploratory factor
Factor analysis
In order to explore factors of media characteristics influencing flow, an exploratory factor analysis was adopted. To validate the communality, the Kaiser-Meyer-Olkin measure of sampling adequacy (KMO) and the Bartlett’s test of sphericity were utilized. As a result, the KMO measure of sampling adequacy was .90, and the Bartlett’s test of sphericity was .00 at significance level .001. Thus, it could be interpreted as fit for factor analysis, and that there were common factors. Kaiser criterion,
Conclusions
Whenever new technologies emerge, the efforts to link them to educability have continued even before they have become generally accepted. Until recently, the core interests of media researchers have focused on the effectiveness of using media for education.
Even though studies have been conducted on effectiveness, there is a little research about for what reason these media can affect learning meaningfully, or how certain characteristics of media are related to effective learning, and how people
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