Discovering usage behaviors and engagement in an Educational Virtual World
Introduction
User perception and engagement with technology is a key aspect of a successful technological system, regardless of application. Information about user perception and engagement can be used by system developers, administrators, designers or managers to adapt, enhance or modify the technology to improve user acceptability, interest, feedback or performance. This type of research and analysis has a major presence in the field of eLearning. Within this field of online learning, behavioral and engagement analysis could be used to propose, implement and correct various types of platforms that enable education and skills acquisition via the use of Internet-based technologies. Many authors (Beer et al., 2010, Krause, 2005, Zhao and Kuh, 2004) have explored the field of behavior analysis and engagement related to online learning environments as a tool to determine how users feel and use technology to obtain insights into the acceptance and adaptation of these eLearning ecosystems in the Learning Process and increase success.
Tracing behavior patterns and measuring engagement on these platforms enables the determination of user interest in certain features or content and whether these features are exploited properly. These measurements enable platform managers to make decisions, correct unexpected uses, promote specific content, perform actions to avoid dropouts, improve system adoption, and adapt the structures or content of eLearning platforms to users.
An educational environment appropriate for this type of study is an Educational Virtual World. This type of environment provides an interesting field of study of user behavior and engagement because it is based on user interaction with a 3D environment and with other users. This feature, combined with the representation of the user via a virtual alter ego and features such as text-based chats, voice-based chats or movement between different islands or lands, allows users to express themselves very differently compared to other educational environments (De Freitas, 2006, De Freitas and Neumann, 2009). Thus, user preferences and desires in the field of Learning are often reflected more accurately than in other eLearning ecosystems.
The goals of this research were to measure engagement indicators specific to the Educational Virtual World, identify user behavior patterns (e.g., the correct use of resources and dropout patterns), determine the relationship between engagement factors and the behavior patterns identified in the proposed case study, and relate the observed rules and patterns to possible actions and decisions by Educational Virtual World managers (in case of usage error patterns, dropouts, etc.).
To achieve these goals, this research aims to conduct an exploratory analysis of a dataset retrieved from an Educational Virtual World to identify usage patterns, engagement factors and user behaviors to provide insights into the perceptions and motivations of users about a technology such as an Educational Virtual World.
The paper is divided into the following sections. Section 1 introduces the problem and concepts that will be discussed in the paper. Section 2 presents the data that will be analyzed and describes the retrieval process. Section 3 provides deeper insight into the variables used in the analysis and the challenges that this analysis attempts to address. The Section 4 describes the behaviors and patterns detected in the exploratory data analysis, while Section 5 discusses these behaviors and patterns, validating or rejecting the results as appropriate. Finally, Section 6 presents several conclusions regarding the research and potential future extensions.
Section snippets
Facilities
To develop this research work, we used an Educational Virtual World developed by the University of Salamanca. This Virtual World, called USALSIM (Lucas, Cruz-Benito, & Gonzalo, 2013), is designed to provide virtual practices and immersive learning experiences through a 3D environment. In 2012, a series of 3D environments permitting the development of professional practices and learning in the following areas of knowledge were incorporated into USALSIM: Pharmacy, Biology and Biotechnology, Law,
Theory
This section describes some key aspects used in the article to inform the reader of the concepts used for exploratory analysis. These concepts are about engagement and behavior patterns, their relationship with the learning ecosystems, and their relevance in Educational Virtual Worlds. The second part of this section describes the mechanisms used by the authors to perform the analysis and achieve the results.
As explained previously, engagement is a key factor in the successful adoption of a
Results
The exploratory analysis revealed many usage and behavior patterns. As explained in Section 3.2, the primary patterns were then linked with related patterns (secondary patterns involving the same clusters of users). Additional patterns and characteristics that were identified in the data analysis but were not sufficiently representative or were only residually present were not included in this study.
After identifying the patterns, the authors consulted through personal interviews the expert
Discussion
Is this type of study useful? Does this study differ from similar studies of other systems used for learning? As many authors agree, among the community that engages in the formal use of Educational Virtual Worlds and retrieves information from these systems, many researchers and early adopters of this type of environment for education have recognized a gap between the events inside the virtual world and the teachers’ knowledge of these events (Atkinson, 2008, García-Peñalvo et al., 2014,
Conclusions
Usage behaviors and engagement indicators represent an appropriate approach with which managers of the Educational Virtual Worlds can determine how users use the online features available, which tools have greater acceptance, and which tools are more useful for users. This knowledge allows managers to make decisions and plan actions about the eLearning system; these decisions and actions could cover several aspects, such as preventing dropout from learning activities, promoting interesting
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