Multi-User Virtual Environments - Teaching through Multi-User Virtual Environments - page 289

It is beyond the scope of this chapter to review
each of these characteristics; however, a detailed
look at the most relevant characteristics is war-
ranted and helpful in our understanding of the
current work being done related to MUVEs and
language learning.
The first major trend found in the MUVE
research focused on language learning is a heavy
emphasis placed on the value of different task
types and task-based learning. One of the chief
affordances of MUVEs is the potential for a variety
of complex task types and the inherent need for
negotiation within the virtual space. Task-based
learning and goal-oriented activity are commonly
praised as productive activities for language learn-
ing (Ellis 2003). Learners focus on meaning to
arrive at an end goal through a series of micro-
tasks. Purushotma, Thorne, and Wheatley (2008)
highlight the ways in which tasks in video games
are especially suited for language learning within
a task-based model. They suggest that gaming
environments emphasize goal-directed activity
and establish language as a resource critical to suc-
cessful gameplay. Sykes, Reinhardt, and Thorne
(in press) further emphasize the importance that
must be placed on task type and task development
in online virtual spaces. 6 In MUVEs, designers
and instructors have the capability to shape and
scaffold tasks in ways relevant to their students'
learning context. Furthermore, learners them-
selves have the capability to modify and adapt
the way they interact with various tasks, and,
as a result, are involved in co-constructing their
learning experience. For example, in an analysis
of the establishment of the cybercultures related
to Star Wars Galaxies , Squires and Steinkuehler
(2006) examine the developmental stages of how
communities of practice related to the MMOG
emerged. They conclude: “because MMOGs
[MUVEs] are living, breathing, cultures, player
practices do not always align with the intentions
of designers as one might anticipate” (p.195). As
researchers and educators, we can make informed
predictions about how learners will interact with

various spaces based on existing cultural practices;
however, we should not be surprised if the learners
themselves deviate from the intended activities.
This deviation and experimentation is what moves
learners beyond schooling and practice to mean-
ingful learning and engagement. Surpassing the
reproduction of traditional task types and taking
advantage of the unique aspects of MUVEs is
a critical step in realizing the potential of these
virtual environments.
Another especially notable characteristic of
MUVEs for language learning is the potential
for effective, multilevel, feedback built-in to
the digital space. Feedback and assessment of
outcomes is critical for language learning. At the
same time, it is often difficult to assess and give
feedback on metalinguisitc and pragmatic features
of language (Roever, 2004; Salaberry & Cohen,
2006). As noted by Gee (2003):

The secret of a videogame as a teaching machine
isn't its immersive 3-D graphics, but its underlying
architecture. Each level dances around the outer
limits of the player's abilities, seeking at every
point to be hard enough to be just doable (p. 1)

In doing so, the feedback given and the expecta-
tions are suited to the level of the learner. Content
can be manipulated to add or subtract additional
features and, as a result, allows for feedback on
complex language features such as pragmatics.
For example, in lower-level learners, dialect dif-
ferences might be mentioned on a global level,
where for advanced learners, recognition of dialect
differences in requests can become a required piece
of knowledge needed to succeed. Furthermore,
through simulated worlds and games, learners
can create and test their own hypotheses without
fear of real-life repercussions (Squire and Jenkins,
2003). Additional reflection tools, such as discus-
sion boards or blogs, can also be incorporated into
the culture of the game to encourage peer feedback
and social interaction (de Freitas, 2006). Finally,
all interactions can be archived for future review