Implementing Learning Models in Virtual Worlds

From Theory to (Virtual) Reality

Athanasios Christopoulos, Marc Conrad and Mitul Shukla

School of Computer Science and Technology, University of Bedfordshire, University Square, Luton, U.K.

Keywords: Instructional Design, Hybrid Virtual Learning, Interaction, Engagement, OpenSimulator.

Abstract: The main advantage of Desktop Virtual Reality is that it enables learners to interact with each other both in

the physical classroom and in a 3D environment. Even though, no explicit theories or models have been

developed to contextualise Virtual Learning, instructional designers have successfully employed the

traditional approaches with positive results on learners’ motivation and engagement. However, there is very

little we know when the question comes to the importance of examining and taxonomising the impact of

interactions on motivation and engagement as a synergy of learners’ concurrent presence. To evaluate the

potential of interactions holistically and not just unilaterally, a series of experiments were conducted in the

context of our Hybrid Virtual Learning classes underpinned from the instructional designer’s decisions to

increase the incentives for interactions. Learners’ thoughts and preconceptions about the use of virtual

worlds as an educational tool were surveyed, whilst, their actions and interactions (in both environments)

were observed during their practical sessions. The take away is that the higher the levels of interactivity are,

the higher the chances to attract students’ attention and engagement with the process will be.

1 INTRODUCTION

Various terms are used to describe Virtual Reality

(VR) products. In this paper, the term ‘virtual-world

or virtual environment’ (VE) is translated into a

computer generated, 3-dimensional (3D) multiuser

environment, whose representations are designed

and shaped by individuals, through the use of

avatars, in real time. In this definition, VR

environments which presume the use of additional

hardware equipment––such as head-mounted, haptic

or kinetic devices––are excluded.

Virtual environments have been inherently

designed to mirror the real-world settings in a vivid

and realistic 3D environment (Loke, 2015).

Moreover, as such environments are highly

customisable, the development of scenarios that

cannot be (effortlessly or efficiently) staged or do

not even exist in the ‘real’ world becomes tangible

(Chen, 2009). Researchers agree that VR technology

has many capabilities and potential to offer in

education (Jarmon et al., 2009) whereas, educators,

highlight the value and benefits that 3D VEs offer on

learners’ motivation and engagement (Pellas and

Kazanidis, 2015).

The lack of literature related to learning

frameworks focused on VEs led educators to

integrate the existing learning theories, as an initial

stepping stone (Savin-Baden et al., 2010; Wang and

Burton, 2013). Consequently, whilst educators and

instructional designers were exploring the

applications of this alternative tool, strong debates

emerged leading to the development of conceptual

and empirical frameworks or taxonomies related to

learning in VEs (Duncan et al., 2012; Lee et al.,

2010). Bossard et al. (2008) examined how effective

VEs are for learning or training and investigated

how the knowledge and skills that have been

constructed in VEs are transferred to the real world’s

applications. Calleja (2014) explored the elements

that affect the levels of immersion that learners

reach whereas, Childs (2010), depicted how the

sense of presence affects their learning

achievements.

The extensive utilisation and positive results of

VEs in Distance Learning, led to their (partial)

incorporation in the traditional face-to-face

education so as to enrich and enhance learners’

experience (Omieno et al., 2012). A plethora of

definitions related to the Blended Learning model

exists. The most predominant definition describes

226

Christopoulos, A., Conrad, M. and Shukla, M.

Implementing Learning Models in Virtual Worlds.

DOI: 10.5220/0006689302260234

In Proceedings of the 10th International Conference on Computer Supported Education (CSEDU 2018), pages 226-234

ISBN: 978-989-758-291-2

Blended Learning as the combination of online and

face-to-face instruction and interaction both between

learners and educators (Graham, 2013). The

outcomes of the aforementioned studies are, indeed,

very substantial and useful to educators and

instructional designers who aim to develop

immersive learning activities for their learners.

Nevertheless, when it comes to Hybrid Virtual

Learning (HVL), the detailed examination does not

fully apply, especially from the view and perspective

of immersion. As HVL, we define the context where

the traditional classroom and the VE are

overlapping. In other words, in HVL, educators and

learners are simultaneously co-present, interacting

with each other in real-time, in the physical and the

virtual environment as well. According to

Konstantinidis et al. (2009), in such contexts,

learning becomes more student-oriented and co-

operative whilst, teaching is more interactive and

rewarding.

As reported by Lee et al. (2010), most of the

existing literature examines and reports how VR

influences learning but very few studies have been

performed to understand how VR enhances learning.

An example of this argument is the topic of

interaction and engagement. Fernández-Gallego et

al. (2013) stress the importance of interactions on

the learning activities whilst, Dillenbourg et al.

(2002), underline the lack of understanding on

developing interactions for different learning

objectives. Nevertheless, the attempts to introduce

taxonomies and frameworks that map and evaluate

them, especially in HVL scenarios, are absent.

Interestingly, even when interactions are under

researchers’ attention, the focus is almost

exclusively on the interactivity of the VE per se and

not on the interactions that need––or have––to be

developed in order to cover learners’ needs and aid

the learning process (Camilleri et al., 2013; Chodos

et al., 2012; Fardinpour and Reiners, 2014;

Grivokostopoulou et al., 2016).

On the antipode, the studies that discuss

interactions holistically (i.e. both in the physical

classroom and the VE), report findings that have

been derived from experiments which included the

use of external hardware devices (Klompmaker et

al., 2013; Kronqvist et al., 2016). However, such

devices are not readily available to (most)

institutions due to their prohibitive cost. Thereafter,

following the common practice route to integrate the

outcomes of studies which have been performed in

mixed/augmented reality contexts, in a strictly

desktop-based HVL model, is absurd.

Ultimately, disregarding partly or even

completely the network of interactions that is being

developed between the ‘real’ and the ‘virtual’

world––between the ‘real’ students and the

‘avatars’––simultaneously, diminishes or even

dismisses the essence of the HVL approach as well

as restricts educators and instructional designers

from reaching its maximum potential.

This brief overview related to the lack of a

common taxonomy for describing and classifying

the types of interactions that take place in HVL

contexts and their impact on learner engagement is a

limitation that needs to be systematically examined

and evaluated.

In this paper, we discuss some of the most

relevant and applicable, to VEs, learning theories

and models contextualised with examples related to

the instructional designer’s perspective.

Consequently, we present our perspective and

understanding in regard to the content and activities,

that educational VEs should include, with particular

emphasis on the importance of interactions. Before

reaching our conclusions, we make a brief

presentation (summary) of the core findings derived

from a four-year longitudinal study to examine this

content in a HVL scenario. The paper concludes

with suggestions and guidance to educators and

instructional designers who are particularly

interested in utilising VEs in HVL contexts.

2 LEARNING THEORIES

Most of the experiments that have been conducted in

VEs have been underpinned from the existing

learning theories (Twining, 2009). To authors’

knowledge, there are no learning theories

exclusively developed to contextualise Virtual

Learning. Furthermore, the majority of the existing

studies are empirical and usually report the learning

benefits of VEs in different educational fields. This

is eventually the under-theorisation of research

problem in VEs. Savin-Baden et al. (2010) underline

that the pedagogical basis for using VEs is under-

theorised whereas, Dalgarno and Lee (2010),

opposes to the aforementioned argument and suggest

that the design of VEs is more intuitive than theory-

based. Indeed, educators who use VEs have more

pragmatic or practical oriented targets than

theoretical focus (Wang and Burton, 2013).

However, understanding and theorising how learners

acquire knowledge in VEs will help educators to

determine what their students can learn and

consequently apply the most relevant mechanism to

achieve the best possible results (Loke, 2015). In

Implementing Learning Models in Virtual Worlds

227

this section, we discuss the most frequently used

learning theories that educators utilise to design

educational VEs.

2.1 Behaviorism

The ease of repeated transmitting information and

feedback to learners in VEs makes ‘operant

conditioning’ viable. Nonetheless, Nelson and

Erlandson (2012) warn instructional designers not to

develop complex activities, with large-scale goals,

as this deconstructs the essence of the behaviorist

idea. Instead, what needs to be developed is a set of

small tasks, which will build upon the feedback of

interactions, until the learning goals are reached.

2.2 Cognitivism

VEs lift many limitations that exist in the ‘real’

world and can facilitate the ‘deep learning process’

through their vivid and interactive content.

Nevertheless, instructional designers who consider

this theory shall keep in mind that, in order to help

learners organise and relate new information to their

existing cognitive schemas (especially when the

subject is highly interconnected and complex), many

different representations of content are required

(Bryceson, 2007).

2.3 (Social) Constructivism

VEs allows learners to develop, alter, and enhance

their content in relation to their personal learning

needs and therefore, construct their cognitive

schemes and engage with the phenomena they study.

Furthermore, the learning process becomes more

student-centered and self-directed, whilst the

educator gets the role of the designer, instructor, and

supporter. Therefore, the focus should be on

developing interactive tasks, with particular

emphasis on the social tools of VEs. In doing so, the

incentives for student collaboration are increase and

enable learners to develop their social presence as

part of the knowledge construction process

(Anderson and Dron, 2011).

2.4 Connectivism

Connectivism, as developed and introduced by

Siemens (2005), is a newly formed learning theory

which established after developing understanding on

how online learning environments can serve as

networks to facilitate learning. Driven by the

principle of ‘knowledge creation’ and

‘consumption’, learners are becoming part of a

wider information network which is generated in

accordance to individuals’ needs and

understandings. Nonetheless, as learners are exposed

to a continuous and changing information flow, their

ability to collect current and relevant information is

a critical factor (Kop and Hill, 2008). The

application of this theory in VEs relies much on the

available nodes (e.g. content and examples) that

instructional designers provide learners (e.g.

shareable example-artifacts from experts or past

students).

2.5 Summary

All and each one of the aforementioned theories

share many properties in common but also differ

greatly in points. Educators who want to offer their

learners engaging and interactive learning

experiences should aim to utilise most of them as

they offer unique benefits whilst, eliminating the

disadvantages and limitations of the others.

3 LEARNING MODELS

In this section, we present some of the most relevant

learning models which have been developed based

on the aforementioned theories and incorporated

successfully in VEs.

3.1 Collaborative Learning

The terms collaborative and cooperative learning are

often used interchangeably though they do not

represent the same idea. In cooperative learning, the

group members work individually and usually

asynchronously towards multiple subtasks which are

assembled to produce the final outcome (Hasler,

2011). On the other hand, collaborative learning

refers to the synchronous social interaction (e.g.

dialogue and discussion) that the group members

engage in, when working as a team, to develop

mutual understanding towards the solution of a

given problem or task (Jeong and Chi, 2007).

VR technology emerged with the concept of

(social) interactivity in mind. Utilising these features

under the principles of the (Social) Constructivism

theories, educators’ decision to use VEs to undertake

a wide range of educational activities, such as role

play, simulation, programming, is fully justifiable.

Indeed, most of the studies report positive results,

especially when it comes to learner embodiment,

engagement and motivation (Pirker, 2013).

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3.2 Experiential Learning

A generic agreement can be identified in educators’

views when it comes to the application and benefits

of this model in VEs (Loureiro and Bettencourt,

2014). Indeed, considering the technical

characteristics and features of VR, learners can

experience information in a real-world-like setting

and learn through experimentation (Chen, 2009).

Nevertheless, Loke (2015) argues that this model is,

by definition, inadequate in explaining how learners’

experience in VEs is transferred or translated as

knowledge and skills in the real-world context.

However, as the author further mentions,

experiential learning theory makes particular

emphasises on the importance of reflection to make

meaning of concrete experiences. Thereby, Loke’s

suggestion is to emphasise on the reflection process

in the exact same way as if the experience was

undertaken in the real world’s context.

3.3 Situated Learning

When the idea of Situated Learning proposed, VR

was not in authors’ list as one of the potential

extension or application. Thereafter, applying this

model in VEs raises the concern of how the acquired

knowledge or skills are transferred from the virtual

context to the real world? Indeed, for this approach

to be effective, various aspects have to be

concurrently considered. Loke (2015) suggests that

the context of the virtual world should be realistic or

‘authentic’ enough so as to enable learners perceive

it in the same way that real-world situations occur.

Moreover, van Rooij (2009) emphasises on the

importance of ‘scaffolding’ the situation so as to

meet the different needs and capabilities of learners.

3.4 Problem-based Learning

Considering the flexibility of applying this learning

model cross-disciplinary, employing the context of

VEs as the learning space to enact or visualise case-

based scenarios, promote social presence and enable

learners to practice their skills stress-free, is

considered to be highly beneficial to the students

(Beaumont et al., 2014).

3.5 Game-based Learning

As Deterding et al. (2011) argue, gamified activities

should be implemented with the same affordances

required to design and develop virtual games.

Nevertheless, as the psychological characteristics or

affordances that stem from games are not explicitly

identified, various instructional design approaches

are framed under the ‘gamification’ idea (Hamari et

al., 2014). A wide range of scientific fields have

utilised this approach reporting that the playfulness

of the activities made valuable contribution towards

learners’ experience and knowledge acquisition

(Kim and Ke, 2017; Young et al., 2012).

3.6 Agent-based Learning

Pedagogical Agents (PAs) in VEs are employed to

support the learning processes and provide

additional instructional support (Terzidou and

Tsiatsos, 2014; Grivokostopoulou et al., 2015).

Nevertheless, the opinion that a portion of educators

share regarding the usefulness of PAs to foster

learner motivation and learning outcomes (Baylor

and Kim, 2005) comes in opposition with the

concerns that others raise, arguing that PAs may

distract learners from the learning content and

objectives (Dehn and van Mulken, 2000). Therein,

instructional designers are advised to consider

various factors concurrently and carefully––such as

the learning environment and content, the target

group which determines the learning goals and the

interactivity spectrum of the agents––when

designing PAs.

3.7 Summary

Similarly to the learning theories, each one of these

models has unique characteristics that facilitate

learning and enhance learners’ experience.

Nevertheless, researchers do not fail to mention the

challenges, obstacles, and limitations that exist when

integrating VEs for educational practices. Students’

difficulty to adapt and familiarise with the interface

or the implemented tools, the 3D modeling

capabilities of this technology––which affect the

realism and authenticity of the activities––or the

elements that distract students’ attention and thus,

prevent them from focusing on their task, are only a

few examples that educators should take into

consideration prior to using virtual worlds.

In the following section, we present our

perspective towards the structure and elements that

instructional designers should consider offering their

students when designing educational activities.

4 INSTRUCTIONAL DESIGN

The existence of our HVL curriculum offered a great

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229

opportunity to examine a set of instructional design

decisions and also, their impact on interactions

engagement. A university hosted virtual world,

based on the OpenSimulator technology, was used to

allow Computer Science students explore and

familiarise themselves with the Linden Scripting

Language—an Event Driven Programming

Paradigm—and also, with the 3D modeling

concepts. Figure 1 illustrates the narrative and logic

which led to our decisions, while designing the in-

world content, following the suggestions from

researchers to combine multiple learning theories

and models with the instructional design techniques

and approaches (Pellas, 2014).

Figure 1: The correlations between the learning theories,

models and our instructional design approach.

4.1 Methodology

Our research methodology, included a combination

of both qualitative (observations) and quantitative

(surveys) methods. Prior to elaborating further on

that, an anecdotal observation, which became

apparent from the very early stages of our first

experiment, should be mentioned. Students’ attitude

and behaviour towards the VE as an educational tool

was overwhelmed from negative attitude and

emotions originating from their biases and

preconceptions that ‘VEs’ are equivalent to ‘Virtual

Games’. Indeed, the academics in charge received

manifold complaints suggesting that such medium

has ‘no place’ in the university classroom and

should be therefore discontinued from the teaching

curriculum. As it was unclear how such behaviour

could affect interactions and engagement, the

distribution of a brief survey a priori to the conduct

of the following experiments was considered critical.

The aim of this survey was to enable us develop a

clear idea of our sample’s beliefs and preconceptions

prior to using the VE so as to correlate them with the

findings deriving from the a posteriori survey and

the observations. As it concerns the observations,

students’ actions and interactions––both in the

physical classroom and in the VE––were observed

during their weekly practical sessions.

4.2 Exemplification

Exemplification is defined as “the ability to critically

assess the use of examples in scientific

communication” (Oliveira and Brown, 2016). The

importance and effectiveness of exemplification to

support conceptual understanding, provide

supportive details about abstract concepts and

engage learners with the phenomena they study has

been highlighted by the aforementioned authors.

Furthermore, as they consider exemplification as an

emotion-related process, they argue that the high

degree of vividness, when providing examples, is an

integral part of this process. Moreover, Zillman and

Brosius (2000) mention that by providing humans

with examples enables them to associate the new

features with past experiences and thus, help them

develop lasting cognitive and emotional experiences.

In this scenario, the most well developed student

work from a prior cohort was selected and utilised as

examples for the newcomers. By providing such

content, it was also expected that the incentives for

interaction, not only between the students and the

content of the world but also with each other, would

increase (e.g. discussion, criticism). As far as the

sample is concerned, 161 students participated in the

a posteriori survey and 33 were observed during

their laboratory work for 44 hours.

4.3 Conceptual Orienteering

Educators who have used VEs stress the importance

of providing students with enough time to

familiarise themselves with the world and its tools

(Jarmon et al., 2009; Savin-Baden et al., 2010).

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However, the strict university time frames make that

hard or even impossible. Considering that this is a

time-consuming process, it is questionable whether

or not instructional designers can facilitate, or even

speed it up.

To facilitate this process, a ‘school-like’ building

was developed, containing instructional information

and practical exercises related to: the navigation

tools, the avatars’ editing appearance process, the

use of the communication channels and the use and

development of avatar gestures/animations. In

addition, we offered students a sandbox area with

information related to the 3D modeling process, as

well as a park where they could socialise. In this

experiment, 196 students participated in the a priori

survey and 178 in the a posteriori. During the

observations, 43 students agreed to participate and

were observed for a total of 44 hours.

4.4 Edutainment and Gamification

The employment of leisure games aimed at evoking

strong childhood memories and further enhancing

the already playful nature of the world. Interacting

with the games would presumably increase the

opportunities for interaction, not only with the

content but also with other students.

For this scenario, the following content was

available to students: an amusement park, a small

lake, a café, a maze (question-based walls related to

the theoretical material and in-world rewards), and a

timed-run game. The sample of this experiment was

138 students who participated in the a priori survey

and 133 in the a posteriori. Amongst them, 51

students were observed for 32 hours.

4.5 Agent-based Instructional Tutoring

Baylor and Kim (2005) suggest that PAs can take

various forms such as ‘expert’, ‘motivator’ or

‘mentor’. In this scenario, 2 AI agents with

contradictory behaviours and characteristics and 1

non-AI NPC were utilised to attract students’ interest

and attention in different manners. At this point, it

should be noted that students were intentionally not

informed about the presence and roles of the NPCs

so as to allow them act naturally and discover their

features as part of the exploration process.

The first NPC had a human-like form,

resembling the role of the instructor or educator and

was a conversational agent (programmed chatbot)

with knowledge-intensive and domain-specific

question answering capabilities. Its role was to

facilitate the learning process and support students

by providing useful and meaningful answers to

technical-related queries. The second NPC was also

a chatbot, though with nonhuman type (‘monkey’),

as an example of the contradictory content that VEs

can accommodate. Its role was to disorientate

students by providing incorrect or ‘nonsense’

answers to their queries in a ‘ludicrous’ way. The

last NPC had a robot-like form, operating as vendor

(task-specific/domain-specific information giver).

Unlike the other NPCs who had also moving

capabilities, this agent was immobilised, becoming

interactive upon students’ call. Its role was to

provide students with informational notecards

(digital text-based notes), assign tasks and offer

‘freebies’ (premade 3D objects and code). In total,

160 students filled in the a priori and 165 the a

posteriori surveys. As to the observatory study,

almost one third of them (n=50) was observed for a

total of 30 hours.

4.6 Summary

The prime objective of the aforementioned scenarios

was to examine whether or not these processes could

help learners acquire all the required knowledge and

skills to cope with the learning activities. Moreover,

for the validation of our data, we repeated each

experiment three times, with different learning

objectives and student cohorts. At this point, it

should be noted that the context of each instructional

approach was examined in isolation from the others

so as to focus exclusively on one factor at a time.

5 DISCUSSION

One of the most important benefits of HVL is that

instructional designers are in the position to examine

the impact of their decisions, under the consideration

of interaction and engagement, holistically and not

just unilaterally. Through our study we had the

opportunity to develop a better understanding

towards our learners’ needs and adjust our future

plans based on their suggestions and

recommendations. In this section, we discuss the

core findings of each experiment.

Providing students with example content should

be an integral part of the world’s content. It enables

learners to have a comparison measurement against

their own aims and goals, turns the VE into a more

authentic environment––which in turn contributes

towards creating a wider community feeling––and

may even be considered as a source pool of ideas.

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Even though the new generations are considered

as ‘digital natives’, offering learners with some form

of guidance––especially at the starting point––can

be truly helpful for those who are not familiar or

comfortable with the idea of the 3D. Nonetheless,

VEs also represent the idea of ‘freedom’ and ‘safety’

when it comes to trial and error. Considering this,

along with the human nature to explore the

unknown, it becomes apparent that it is fairly hard to

patronise such procedures. Thereafter, chances are

that students will rather attempt to explore the world

and its tools by themselves, instead of going through

specific or framed procedures. Nevertheless, having

an information and instruction ‘fountain’ available at

any given point might come handy.

Leisure games have potentially higher chances,

as opposed to the educational ones, to attract

learners’ interest and attention and therefore, engage

them with the VE. Some of them may be inspired

from this content, whereas others may perceive it

purely as a way to break their routine and entertain

themselves. In either case, the existence of game-

like elements, in a relatively pure educational VE,

can help students familiarise themselves with the in-

world tools, or even make them perceive the

learning process in a more enjoyable way. However,

the impact of this content on the learning process is

rather minimal or even non-existent.

Finally, regarding the usefulness and impact of

the PAs on learner engagement, the results are very

controversial. First, unlike the previous experiments

where the instructional content was massive, the

minimalistic appearance of the NPCs made them

look and feel as part, or thereof not, of the system

responsible for controlling and ensuring the proper

operation of the VE. Nonetheless, the appearance of

the NPCs––especially the nonhuman creature––

attracted students’ attention as it was the ‘odd’ of the

ecosystem. This agent received intense criticism for

providing meaningless responses to ‘serious’ matters

and therein, was interpreted as the ‘fun element’ of

the world. The human-like agent was certainly more

useful to address student queries, though only a

small portion of them had intense interaction with

this agent, probably due to the biases and

preconceptions that have been developed from the

behaviour of the aforementioned agent. Last but not

least, the robot-like NPC was the one which truly

added value to the learning process. Indeed, most of

(if not all) the students would visit this agent fairly

often to get advices, instructions or even ‘gifts’ (as it

befalls in nearly all the workspaces).

6 CONCLUSIONS

Both types of interactions (in-world/in-class) play a

crucial role in learner engagement, as they

contribute to enhancing the benefits deriving from

using the VE alone. Unlike virtual games, where the

sense of in-world presence is a key factor, when it

comes to HVL, immersion does not have much

relevance or effect (if any). Furthermore, the in-

world student-to-student interactions have a slightly

lesser impact on learner engagement, compared to

the ones that students have with the VE per se.

Nevertheless, their impact on engagement and

learning should not be disregarded.

The role of instructional designers is that of a

‘game changer’ in the teaching and learning process.

Indeed, learners’ personal preferences, choices, or

preconceptions, might come in opposition with the

instructional design. However, it is of vital

importance that learners receive clear information

and instructions regarding the relevant content or

even encourage them to use it, as it has been

designed and developed in their favour.

Unarguably, not every learner will be attracted

by the same learning approach. However, the higher

the levels of interactivity are, the higher the chances

to attract students’ attention and engagement with

the process will be.

REFERENCES

Anderson, T., and Dron, J., 2011. Three generations of

distance education pedagogy. Int. Rev. of Research in

Open and Dist. Learn., 12(3), 80-97.

Baylor, A. L., and Kim, Y., 2005. Simulating instructional

roles through pedagogical agents. Artificial Int. in

Edu., 15(2), 95-115.

Beaumont, C., Savin-Baden, M., Conradi, E., and Poulton,

T., 2014. Evaluating a Second Life Problem-Based

Learning demonstrator project: What can we learn?.

Interactive Learning Environments, 22(1), 125-141.

Bossard, C., Kermarrec, G., Buche, C., and Tisseau, J.,

2008. Transfer of learning in virtual environments: A

new challenge?. Virtual Reality (Waltham Cross),

12(3), 151–161.

Bryceson, K., 2007. The online learning environment–A

new model using social constructivism and the

concept of ‘Ba’ as a theoretical framework. Learning

Environments Research, 10(3), 189-206.

Calleja, G., 2014. Immersion in virtual worlds. In M.

Grimshaw (Ed.) The Oxford Handbook of Virtuality,

222–236. NY: Oxford University Press.

Camilleri, V., de Freitas, S., Montebello, M., and

McDonagh-Smith, P., 2013. A case study inside

virtual worlds: use of analytics for immersive spaces.

CSEDU 2018 - 10th International Conference on Computer Supported Education

232

Proc. 3

Int. Conf. on Learning Analytics and

Knowledge, 230–234. Belgium: ACM.

Chen, C. J., 2009. Theoretical bases for using virtual

reality in education. Themes in Sci. Tech. Edu., 2(1-2),

71-90.

Childs, M., 2010. A conceptual framework for mediated

environments. Educational Research, 52(2), 197–213.

Chodos, D., Stroulia, E., King S., Carbonaro, M., 2012. A

framework for monitoring instructional environments

in a virtual world. BJoET, 45(1), 24-35.

Dalgarno, B., and Lee, M.J.W., 2010. What are the

learning affordances of 3-D virtual environments?.

BJoET., 41(1), 10–32.

Dehn, D.M., and van Mulken, S., 2000. The impact of

animated interface agents: A review of empirical

research. J. Hum–Compt. Stud. 52, 1–22.

Deterding, S., Dixon, D., Khaled, R., and Nacke, L., 2011.

From game design elements to gamefulness: defining

gamification. Proc. 15

Int. Academic MindTrek

Conf.: Envisioning Future Media Env., 9-15. Finland.

Dillenbourg, P., Schneider, D., Synteta, P., 2002. Virtual

Learning Environments. Proc. 3

Hellenic Conf. Info.

and Com. Tech. in Edu., 3-18. Rhodes:Greece.

Duncan, I. M. M., Miller, A. H. D., and Jiang, S. 2012. A

taxonomy of virtual worlds usage in education.

BJoET, 43(6), 949-964.

Fardinpour, A., Reiners, T., 2014. The Taxonomy of Goal-

oriented Actions in Virtual Training Environments.

Procedia Technology, 13, 38-46.

Fernández-Gallego, B., Lama, M., Vidal, J.C., Mucientes,

M., 2013. Learning Analytics Framework for

Educational Virtual Worlds. Procedia Comp. Sci. 25,

443-447.

Graham, C.R., 2013. Emerging practice and research in

blended learning. In M. J. Moore (Ed.), Handbook of

distance education, 333–350, 3

ed. NY: Routledge.

Grivokostopoulou, F., Perikos, I., Konstantinos, K., and

Hatzilygeroudis, I., 2015. Teaching Renewable Energy

Sources Using 3D Virtual World Technology. Proc.

IEEE Int. Conf. on Advanced Learn. Tech., 472-

474. Hualien: Taiwan.

Grivokostopoulou, F., Perikos, I., Kovas, K., and

Hatzilygeroudis, I., 2016. Learning Approaches in a

3D Virtual Environment for Learning Energy

Generation from Renewable Sources. Proc. 29

Int.

FLAIRS Conference, 497-500. Florida: USA.

Hamari, J., Koivisto, J., and Sarsa, H., 2014. Does

Gamification Work? A Literature Review of Empirical

Studies on gamification. Proc. 47

Hawaii Int. Conf.

on System Sciences, 3025-3034. Hawaii: USA.

Hasler, B.S., 2011. Intercultural collaborative learning in

virtual worlds. Cutting-Edge Tech. High. Educ., 4,

265–304.

Jarmon, L., Traphagan, T., Mayrath, M., and Trivedi, A.,

2009. Virtual world teaching, experiential learning,

and assessment: An interdisciplinary communication

course in Second Life. Comp. and Edu., 53(1), 169-

182.

Jeong, H., and Chi, M.T.H., 2007. Knowledge

convergence and collaborative learning. Instructional

Science, 35, 287-315.

Kim, H., and Ke, F., 2017. Effects of game-based learning

in an OpenSim-supported virtual environment on

mathematical performance. Interactive Learning

Environments, 25(4), 543-557.

Klompmaker F., Paelke V., Fischer H., 2013. A

Taxonomy-Based Approach towards NUI Interaction

Design. In Streitz N., Stephanidis C. (Eds.)

Distributed, Ambient, and Pervasive Interactions.

Lecture Notes in Computer Science, 8028. Springer.

Konstantinidis, A., Tsiatsos, Th., Pomportsis, A., 2009.

Collaborative Virtual Learning Environments: Design

and Evaluation. Multimedia Tools and Applications,

44(2), 279-304. Springer.

Kop, R., and Hill, A., 2008. Connectivism: Learning

theory of the future or vestige of the past?. Int. Review

of Research in Open and Distance Learning, 9(3).

Kronqvist, A., Jokinen, J., and Rousi, R., 2016. Evaluating

the Authenticity of Virtual Environments: Comparison

of Three Devices. Advances in Human-Comp. Int.,

2016, 14 pages.

Lee, E.A.L., Wong, K.W., and Fung, C.C., 2010. How

does desktop virtual reality enhance learning

outcomes? A structural equation modelling approach.

Comp. and Edu., 55(4), 1424-1442.

Loke, S.K., 2015. How do virtual world experiences bring

about learning? A critical review of theories.

Australasian J. of Edu. Tech., 31(1), 112-122. Ascilite.

Loureiro, A., Bettencourt, T., 2014. The use of virtual

environments as an extended classroom - a case study

with adult learners in tertiary education. Procedia

Technology, 13(2014), 97–106.

Nelson, B.C., and Erlandson, B.E., 2012. Design for

Learning in Virtual Worlds. NY: Routledge.

Oliveira, A.W., and Brown, A.O., 2016. Exemplification

in science instruction: Teaching and learning through

examples. Research in Sci. Teaching, 53(5), 737-767.

Omieno, K. K., Wanyembi, G., Mbugua, S., 2012.

Integrating Virtual Worlds and Virtual Learning

Environments in Schools in Developing Economies.

Int. J. of ICT Research, 2(1), 17-21.

Pellas, N., 2014. Bolstering the quality and integrity of

online collaborative courses at university level with

the conjunction of Sloodle and open simulator. Edu.

and Info. Tech, 21(5), 1007–1032.

Pellas, N., and Kazanidis, I., 2015. On the value of Second

Life for students’ engagement in blended and online

courses: A comparative study from the Higher

Education in Greece. Edu. and Info. Tech., 20(3), 445–

466.

Pirker, J., 2013. The Virtual TEAL World - An Interactive

and Collaborative Virtual World Environment for

Physics Education. Master's thesis, Graz University

of Technology.

Savin-Baden, M., Gourlay, L., Tombs, C., Steils, N.,

Tombs, G., and Mawer, M., 2010. Situating

pedagogies, positions and practices in immersive

virtual worlds. Educational Research, 52(2), 123–133.

Siemens, G., 2005. Connectivism: A learning theory for

Implementing Learning Models in Virtual Worlds

233

the digital age. Int. J. of Instruct. Tech. and Distance

Learn., 2(1), 3-10.

Terzidou, T., and Tsiatsos, Th., 2014. The impact of

pedagogical agents in 3D collaborative serious games.

Proc. IEEE Global Eng. Edu. Conf., 1–8. Istanbul:

Turkey.

Twining, P., 2009. Exploring the Educational potential of

Virtual Worlds – d Some Reflections From the SPP.

BJoET, 40(3), 496-514.

van Rooij, W.S. (2009). Scaffolding project-based

learning with the project management body of

knowledge (PMBOK). Comp. and Edu., 52(1), 210-

219.

Wang, F., and Burton, J. K., 2013. Second Life in

education: A review of publications from its launch to

2011. BJoET, 44(3), 357–371.

Young, W., Franklin, T., Cooper, T., Carroll, S., and Liu,

C., 2012. Game-based learning aids in Second Life. J.

of Interactive Learning Research, 23(1), 57–80.

Zillman, D., and Brosius, H.D., 2000. Exemplification in

communication: The influence of case reports on the

perception of issues. Mahwah, NJ: Lawrence Erlbaum

Associates.

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