View source for Real Learining in Virtual World - Selected Appendices

<div class="nonumtoc">
=Appendices=

==Appendix A:          Terminology==

{| width="15%"
|- 
|'''Term'''
|'''Description'''
|}
;Virtual World: 
:An artificial environment that a person projects themself within.  In the context this in which this term has been used mainly in this paper (unless otherwise stated) it is an environment that is technological built form software programs.   
;In World: 
:Artificial, where the person operates in the artificial virtual world. 
;Real Word
:Reality, where the person operates in their physical world.  
;Avatar:
:The digital representation of the person in the virtual world.
;Teleport
:A method of transport used in the virtual world that moves them from one location to another without having to walk to a location with their avatar.
;Presence: 
:A subjective measure.  The feeling of being in the virtual world that disconnects them from physical world around them. 
;Immersion: 
:An objective measure.  The interface between the virtual world and the user that places the person in the virtual world.
;MMORPG:
:Massively Multiplayer Online Role Playing Game.  The can used in various shortened abbreviations eg RPG, MMO
This term often is used to describe the latest generation of online virtual world technology.  Many other terms are used such as MUVE, CVE etc. 
;MUD: 
:Multi User Dungeon.  Early text based networked virtual worlds.  

 
 

<P align=left >'''''Table 14  Terminology'''''</p >



 

==Appendix B:          MMOG Analysis==

Bruce Woodcock (2008) is an independent writer and long time player of MMOGs that has dedicated his research to tracking subscriptions numbers of online MMOGs.  These figures are obtained from source and public available material e.g. company financial reports, company media releases, media publications and in some cases an educated guess.  These figures although not precise, allows us to do a comparison of MMOGs that would otherwise would not be available unless one was to undertaken the same type of analysis such as he has done over the years.  If anything these figures would be underreported as they only are based upon user subscriptions and therefore do not include in the numbers of user that have free-access to their environments (included within the ones listed).  These figures are current as at April 2008, for more information see http://www.mmogchart.com/.

Breakdown of MMOGs listed Chart.

 
{|border="1" width="40%" align=center
|-
|align=center |'''Name'''
|align=center |'''Current Active Subscriptions'''
|- 
|align="right"|World of Warcraft
|align="right"|10,000,000 
|- 
|align="right"|RuneScape
|align="right"|1,200,000 
|- 
|align="right"|Lineage
|align="right"|1,056,177 
|- 
|align="right" |Lineage II
|align="right" |1,006,556 
|- 
|align="right" |Final Fantasy XI
|align="right" |500,000 
|- 
|align="right" |Dofus
|align="right" |452,000 
|- 
|align="right" |EVE Online
|align="right" |236,510 
|- 
|align="right" |EverQuest II
|align="right" |200,000 
|- 
|align="right" |EverQuest
|align="right" |175,000 
|- 
|align="right" |The Lord of the Rings Online
|align="right" |150,000 
|- 
|align="right" |City of Heroes / Villains
|align="right" |136,250 
|- 
|align="right" |Tibia
|align="right" |104,338 
|- 
|align="right" |Star Wars Galaxies
|align="right" |100,000 
|- 
|align="right" |Toontown Online
|align="right" |100,000 
|- 
|align="right" |Second Life
|align="right" |-91,531 
|- 
|align="right" |Tabula Rasa
|align="right" |75,000 
|- 
|align="right" |Ultima Online
|align="right" |75,000 
|- 
|align="right" |Pirates of the Burning Sea
|align="right" |65,000 
|- 
|align="right" |Dark Age of Camelot
|align="right" |45,000 
|- 
|align="right" |Dungeons & Dragons Online
|align="right" |45,000 
|- 
|align="right" |Vanguard: Saga of Heroes
|align="right" |40,000 
|- 
|align="right" |Yohoho! Puzzle Pirates
|align="right" |34,000 
|- 
|align="right" |EverQuest Online Adventures
|align="right" |30,000 
|- 
|align="right" |The Matrix Online
|align="right" |30,000 
|- 
|align="right" |Era of Eidolon
|align="right" |27,000 
|- 
|align="right" |PlanetSide
|align="right" |20,000 
|- 
|align="right" |Asheron's Call
|align="right" |15,000 
|- 
|align="right" |Sphere
|align="right" |15,000 
|- 
|align="right" |Anarchy Online
|align="right" |12,000 
|- 
|align="right" |The Realm Online
|align="right" |12,000 
|- 
|align="right" |World War II Online
|align="right" |12,000 
|- 
|align="right" |Pirates of the Caribbean Online
|align="right" |10,000 
|- 
|align="right" |Neocron 2
|align="right" |6,000 
|- 
|align="right" |Horizons
|align="right" |5,000 
|- 
|align="right" |Mankind
|align="right" |5,000 
|- 
|align="right" |A Tale in the Desert
|align="right" |1,054 
|} 



==Appendix I:            Second Life Demographics==



{| align="center" width="50%" style="background-color:#ffffcc; "
|-
|align="left" colspan="3" |'''Second Life Virtual Economy<br />
Demographic Summary Information<br />
Through November 2008'''
|-bgcolor="lightblue" 
|align="center" colspan="3"  |'''Top 20 Countries by Active User Hours'''
|-bgcolor="wheat"  
|align=center |'''Country'''
|align=center |'''Total Hours'''
|align=center |'''% of Total Hrs'''
|- 
|align=right |United States
|align=right |14,451,180.28
|align=right |39.38%
|-
|align=right |Germany
|align=right | 3,505,103.93
|align=right | 9.55%
|-
|align=right | United Kingdom
|align=right | 2,424,987.88
|align=right | 6.61%
|-  
|align=right | Japan
|align=right | 2,014,299.45
|align=right | 5.49%
|-  
|align=right | France
|align=right | 1,972,875.00
|align=right | 5.38%
|-  
|align=right |Netherlands
|align=right | 1,406,652.90
|align=right | 3.83%
|-
|align=right |Italy
|align=right | 1,397,571.12
|align=right | 3.81%
|-
|align=right |Brazil
|align=right | 1,361,741.72
|align=right | 3.71%
|- 
|align=right |Canada
|align=right | 1,336,706.03
|align=right | 3.64%
|- 
|align=right |Spain
|align=right | 1,083,716.70
|align=right | 2.95%
|- 
|align=right |Australia
|align=right | 747,158.40
|align=right | 2.04%
|-  
|align=right |Belgium
|align=right | 349,070.48
|align=right | 0.95%
|-  
|align=right |Portugal
|align=right | 332,468.60
|align=right | 0.91%
|-
|align=right |Switzerland
|align=right | 277,448.60
|align=right | 0.76%
|- 
|align=right |Poland
|align=right | 234,785.58
|align=right | 0.64%
|-
|align=right |Argentina
|align=right | 196,719.35
|align=right | 0.54%
|-
|align=right |Denmark
|align=right | 193,975.72
|align=right | 0.53%
|-
|align=right |Sweden
|align=right | 191,424.80
|align=right | 0.52%
|-
|align=right |Mexico
|align=right | 177,130.73
|align=right | 0.48%
|-
|align=right |Turkey
|align=right | 176,759.05
|align=right | 0.48%
|-
|align=right |Others
|align=right | 2,866,931.23
|align=right | 7.81%
|-
|align=center |'''Total'''
|align=right | '''36,698,707.57'''
|
|}  
  
 
 
{| align="center" width="50%" style="background-color:#ffffcc; "
|-
|align="left" colspan="3" |'''Second Life Virtual Economy<br />
Demographic Summary Information<br />
Through November 2008'''
|-bgcolor="lightblue" 
|align="center" colspan="3"  |'''Usage hours by Age Band'''
|-bgcolor="wheat"  
|align=center |'''Age'''
|align=center |'''% of Total Hrs'''
|- 
|align=right |13-17 (Teen Grid)
|align=right |0.32%
|-
|align=right |18-24
|align=right | 15.07%
|-  
|align=right |25-34
|align=right | 34.51%
|-
|align=right |35-44
|align=right | 28.51%
|-
|align=right |45 plus
|align=right | 21.14%
|-
|align=right |Unknown
|align=right | 0.45%
|-bgcolor="lightblue" 
|align="center" colspan="3"  |'''Usage hours by Gender'''
|-
|align=right |Male
|align=right | 58.72
|-
|align=right |Female
|align=right | 41.28
|}  

<p align="center" >'''''Source: (Linden Lab, 2008b)'''''</p >

==Appendix J:           Pre-Quiz Score Results==

This section discusses the pre-quiz scores significance test results.  

 

===J.1 Remember Scores===

Figure 68 provides the pre-quiz results for Bloom’s ‘remember’ cognitive process. 



Figure 68. Results: Pre-Quiz Remember - Histogram & Bell Curve

 

The pre-quiz ‘remember’ scores were tested using the parametric individual t-test as results met the assumptions for parametric testing.  Both groups’ results were normally distributed (2D: ses = -0.417, sek = -1.105, K2 p = 0.26747 and 3D: ses = -0.595 and sek = -1.54, K2 p = 0.2675) and the variance between the groups was not significant (F = 0.668, 2 tailed p = 0.140, α = 0.05), therefore the parametric independent t-test of equal variance was used to test for significance.

 

The results of an independent t-test found no significant difference (t = 1.665, df = 109, two-tailed p = 0.0987, α = 0.05) between the results of the 2D (x1 = 2.44, s1 = 1.032) and 3D (x2 = 2.071, s2 = 1.263) pre-quiz ‘remember’ scores.  

 

When tested using a one-tail test where µ1 – µ2  > 0.5 the results show that there is a significant different (t = 1.665, df = 109, one-tailed p =  0.0494, α = 0.05), thus the 2D pre-quiz scores were significantly higher than the 3D scores for the Bloom’s cognitive process of ‘remember’.

 

 

 

===J.2 Understand Scores===

Figure 69 provides the pre-quiz results for Bloom’s understand cognitive process.



Figure 69. Results: Pre-Quiz Understand - Histogram & Bell Curve

 

The pre-quiz ‘understand’ scores were tested using the parametric individual t-test as results met the assumptions for parametric testing.  Both groups’ results were normally distributed (2D: ses = 0.790, sek = -0.227, K2 p = 0.63248 and 3D: ses = 1.072, sek = 0.0563, K2 p = 0.50798) and the variance between the groups was not significant (F = 0.799, 2 tailed p = 0.410, α = 0.05), therefore the parametric independent t-test of equal variance was used to test for significance.

 

The results of an independent t-test found a significant difference (t = -2.257, df = 109, two-tailed p = 0.0260, α = 0.05) between the results of the 2D (x1 = 1.254, s1 = 0.775) and 3D (x2 = 1.607, s2 = 0.867) pre-quiz ‘understand’ scores.  The 3D pre-quiz scores were significantly greater than the 2D pre-quiz scores for the Bloom’s cognitive process of ‘understand’ (µ1 – µ2 < 0.5; t = -3.03167, df = 109, one-tailed p = 0.00138, α = 0.05). 



 

===J.3 Summary Pre-Quiz Remember and Understand===


Figure 70 provides an inverse cumulative normal distribution graph for Bloom’s cognitive process ‘remember’ and ‘understand’ for the post-quiz scores.  This graph displays what percentage of participants scored under a nominated score.



Figure 70. Results: Pre-Quiz Rem & Und - Inverse Cumulative Normal Distribution Graph

 

===J.4 Total Scores===

A graph of the results for the total score was provided in the main document in the Chapter, 4 Results, Pre- Quiz Results.  

 

The pre-quiz total scores were tested using the parametric individual t-test as results met the assumptions for parametric testing.  Both groups’ results were normally distributed (2D, ses = 0.0218, sek = -1.087, K2 p = 0.49248 and 3D, ses = -0.574, sek = -0.425, K2 p = 0.671739) and the variance between the groups was not significant (F = 0.862, 2 tailed p = 0.586, α = 0.05), therefore the parametric independent t-test of equal variance was used to test for significance.

 

The results of an independent t-test found a no significant difference (t = 0.0455, df = 109, two-tailed p = 0.964, α = 0.05) between the results of the 2D (x1 = 3.690, s1 = 1.372) and 3D (x2 = 3.679, s2 = 1.479) pre-quiz total scores.



 

==Appendix K:         Post-Quiz Score Results==


A graph of the results for the post-quiz score was provided in the main document in the Chapter, 4 Results; Post Quiz Results, Hypothesis One and Two sections.  

 

===K.1 Remember Scores===

The post-quiz ‘remember’ scores (H01) were tested using the non-parametric Mann-Whitney U Test as the results for the post-quiz ‘remember’ scores did not meet the assumptions for parametric testing which requires the scores to be normality distributed (2D: ses = -1.94259, sek = -1.10294, K2 p = 0.06976 and 3D: ses = -2.87371, sek = 1.02617, K2 p = 0.01161).  The 3D scores failed the D’Agostino-Pearson (K2) normal distribution test (p = 0.01161 ie < 0.05) therefore the scores from this group deviate significantly from normal distribution.  

 

The results of Mann-Whitney U Test when applied found that there was no significant difference between the 2D and 3D post-quiz ‘remember’ scores where the average ranked scores were 2D = 53.9364 and 3D = 58.0268 resulted in U = 1653.5, W = 113.5, 2 tailed p = 0.493107, α = 0.05.

 

===K.2 Understand Scores===


The post-quiz ‘understand’ scores (H02) were tested using the parametric independent t-test as results met the assumptions for parametric testing.  Both groups’ results were normally distributed (2D: ses = 0.204408, sek = - 0.8453, K2 p =  and 3D: ses = 1.016, sek = 0.016, K2 p = ) and the variance between the groups was not significant (F = 1.028, 2 tailed p = 0.920, α = 0.05), therefore the parametric independent t-test of equal variance was used to test for significance.

 

===K.3 Total Scores===

The post-quiz total scores were tested using the parametric individual t-test as results met the assumptions for parametric testing.  Both groups’ results were normally distributed (2D: ses = 0.158427, sek = -0.230644, K2 p = 0.8865884 and 3D: ses = -0.700083, sek = 0.404913, K2 p = 0.62133) and the variance between the groups was not significant (F = 1.10638, 2 tailed p = 0.70972, α = 0.05), therefore the parametric independent t-test of equal variance was used to test for significance.

 

The results of an independent t-test found a no significant difference (t = -0.8212, df = 119, two-tailed p = 0.4133, α = 0.05) between the results of the 2D (x1 = 10.9818, s1 = 2.46825) and 3D (x2 = 11.3571, s2 = 2.34659) post-quiz total scores.

 



 

==Appendix L:          Instrument Reliability Results==


Table 15 provides the results of the instrument reliability tests performed on the achievement quiz results.  For the pre-quiz there were 4 questions each for the Bloom’s cognitive process of ‘remember’ (rem) and ‘understand’ (und) for a combined total of 8 and in the post-quiz 10 questions for a combined total of 20.  The 2D group consisted of 55 participants and the 3D group 56.  

 

{| align="center" width="60%" style="background-color:#ffffcc; "
|-
|colspan="5" align="center" |'''Post-Quiz Remember'''
|- 
|align=center|
|align=center bgcolor="#DDADAF" colspan=2 |'''2D'''
|align=center bgcolor="lightblue" colspan=2 |'''3D'''
|-bgcolor="lightgrey" 
|align=center|
|align=center bgcolor="lightgrey" |'''Rem'''
|align=center bgcolor="lightgrey" |'''Und'''
|align=center bgcolor="lightgrey" |'''Rem'''
|align=center bgcolor="lightgrey" |'''Und'''
|- 
|align=right |'''Pre-Quiz KR20'''
|align=right | 0.14
|align=right | -0.46
|align=right | 0.48
|align=right | -0.01
|- bgcolor="lightgrey"
|align=right |'''Post-Quiz KR20'''
|align=right | 0.53
|align=right | -0.01
|align=right | 0.54
|align=right | 0.10
|}

<p align=center >'''''Table 15. Instrument Reiability: Acheivement Quiz'''''</p>


 

Table 16 provides the results of the instrument reliability tests performed on the post survey Likert scale results for questions 23, 24, 28 and 29.  

 

 
{| align="center" width="60%" style="background-color:#ffffcc; "
|-
|colspan="3" align="center" |'''Post-Quiz Remember'''
|- 
|align=center|
|align=center bgcolor="#DDADAF" |'''2D'''
|align=center bgcolor="lightblue" |'''3D'''
|-bgcolor="lightgrey" 
|align=right |'''Cronbach's Alpha:'''
|align=right |0.73
|align=right |0.72
|}

<p align="center" >'''''Table 16. Instrument Reiability: Survey Likert Scales'''''</p>

 

Frary (2008) provides the following definitions for the measure of these reliability (r) results:

*r = .90 or higher - High reliability.  Suitable for making a decision about an examinee based on a single test score. 
*r = .80 to .89 - Good reliability.  Suitable for use in evaluating individual examinees if averaged with a small number of other scores of similar reliability. 
*r = .60 to .79 - Low to moderate reliability.  Suitable for evaluating individuals only if averaged with several other scores of similar reliability. 
*r = .40 to .59 - Doubtful reliability.  Should be used only with caution in the evaluation of individual examinees. May be satisfactory for determination of average score differences between groups.  
 

 

'''Discussion'''

Instrument reliability tests the correlation of answers within a data set.  The assumptions for the KR-20 test is that test items are of equal, or near equal, difficulty and intercorrelation (Lenke, Wellens, & Oswald, 1977).  Consistent with these assumptions, the tests performed were split into the Bloom’s cognitive processes of ‘remember’ and ‘understand’.  Furthermore as we were measuring the difference between the achievement results of two groups that had distinctly different treatment methods the reliability tests were divided into 2D and 3D participant groups.  These repeated divisions caused a problem for the application of the instrument reliability test as in each division the total number tested items is 10 or below.  If the number of questions (or subjects) are too low within each group then the results of the test as put by Frary ‘should be taken with a grain of salt’.  Frary (2008) provides further insight as to why: 

 

“All reliability estimates are subject to considerable error when there are small numbers of examinees or test items. If there are fewer than, say, 25 examinees or 10 items, the reliability estimate must be "taken with a grain of salt." This phenomenon is especially noticeable when there are several scrambled forms of the test, each administered to a relatively small number of examinees. Then the KR20 coefficients may fluctuate considerably from one form to another.” 

 

As we can see from the above results there was considerable fluctuation in the reliability test results between the two groups.  With exception to the post-quiz ‘remember’ results the other figures varied considerably.  These results seem to correlate to the results that are discussed in Chapter 5 Discussion and Conclusion chapter.  Participants for both groups performed well for ‘remember’ but did not for Bloom’s ‘understand’.  

 

Although, as Frary asserts, the test reliability measures under this research’s circumstances are inconclusive indicators.

==Appendix M:        Qualitative Analysis: A Sample of Participants Comments==

===Virtual World Learning Experience===

*I found learning in world is a great way to find out about things you don’t normally think about finding out about 
*You’re more likely to learn things in world than go to places to find out about things 
*Things I usually don't take time to learn about, I can learn about them here
*I really felt as if I was sitting in a Room of Such listening to a lecturer
*It kind of felt personal.
*Kind of soothing but not putting me to sleep kind
*The lack of pressure that comes from a more traditional classroom atmosphere
*You can see if others are in the class with you
*Feel this way is better experience then the normal online way of taking classes
*I prefer learning alone and I would definitely prefer this type of learning to going to a classroom with other students.
*Seemed better than the typical classroom experience
*This is a fantastic experiment and I believe the potential to reach people with anything that will help them become better educated is a wonderful thing.
*Top idea to get people to learn about several topics
*I liked the idea; please invite me for more lessons
*By being part of this Survey Study, I have opened a door to seeking out further Studies, as well as Classes with SL
 

===Campus Experience===

*It was very easy to use
*It was very well laid out
*Easier to navigate through
*I liked the way different stages
*The environment was well set out  
*Very user friendly



===Format===

*2D:  Like liked the layout... it showed you a picture of the different types of bridges as well as giving you plenty of information on the subject then had a summary of all of it at the end
*2D: I wish that the pictures had been interactive so I could've clicked on the different sections of the bridges and gotten an individual description
*2D: Easy to follow slides
*2D: The presentation was actually enjoyable, however I believe that for this to be a truly effective learning tool the presentation speed must be made adjustable as people may find certain topics boring and just skip through them but may wish to spend longer periods of time on other material and wish to slow down to be more attentive.
*2D:  the possibility to go back or control the slideshow
*3D: The mix of the audio and the bulleted points made it easier to follow for visual 
*3D: Wonderfully laid out. The visuals were great! They conveyed the most important points very well.
*3D:  lots of examples
*3D: Wish there was a way I could stop the presentation or lecture and go back to review what was just said.

 

===Information content===

*2D: Very informative and interesting 
*2D: very easy to comprehend
*2D: It was not too technical
*2D: I never gave it much thought at to the Construction of Bridges, one droves on them, over them etc, and you certainly hear in recent years of the collapse of bridges etc, I found the topic informative although a lot to digest.
*3D:  It was informative.
*3D: Need more infor need more infor need more infor
*3D: I have never stopped to think about bridges before. Now how am I going to drive over a bridge without thinking about what it is?
*3D: The theory of the subject was well thought out, even though to my knowledge the subject was well informative, it could have been explained in more of laymen terms for those who really don't understand the makeup of bridges.
*3D: I found myself getting lost a bit here and there with the terminology
*3D:  Overall a bit too complicated for someone with no previous knowledge coming into the presentation, but still worthwhile.
*3D:  I might have liked a little better explanation of how compression and tension work at the beginning so as I could understand the physics of it a little better.     

 

===Learning===

*2D: I liked learning something new
*2D:  I got to learn something I did not know.  
*2D: Learned more about bridges  
*2D: It was good to learn about the understanding of bridges
*3D:  learn something about a subject I never knew something about
*3D:  Suddenly, unforeseeably, I was studying the physics of bridges! I could never have guessed when I woke up today that I would learn this.    
*3D:  What a well thought out presentation, Now that I know something about bridges. I have something new to take to Real life with me
*3D:  Combined my hobby with learning

 

===Facets of 3D Learning===

*3D: The way the bridges could actually be seen materialized and color coded was great.     
*3D: It was visually appealing versus reading a book or listening to a live lecture.  
*3D: It's a great learning key.
*3D: I liked the ability to see a 3D diagram of the topic.  
*3D: The examples floating in space allowed for a better view of the material
*3D: The use of "real" object as opposed to drawings helped with any problems in understanding
*3D:  The images were 3D making it a little easier to get an idea of what each bridge was.  
*3D: The 3D rendered models illustrating the different types of bridges & how loads were carried were a great tool.  
*3D: With the help of bridge models I was able to get a better understanding about what the lecture was talking about.
*3D:  Just the fact that the examples where suspended in space, allowed me a better understanding from all angles.
*3D: While it may not quite stick on the first pass, I feel as if this method DEFINITELY provided a clear, direct delivery of the subject matter. I could see this type of presentation doing much more for someone with at least a rudimentary knowledge of the subject matter.

 

===Instruction===

*2D:  It would have been fun to have an "instructor" to ask questions of. :)
*2D: lack of contact or clarification of issues
*3D: There was no place to pause the instructor, or ask further questions about the subject matter  
*3D:  A live guide would've been very helpful to clear up any confusion along the way, though it isn't necessary.
*3D: The inability to ask for clarification or further explanation.  
*3D: No interactive question-answer

 

===Focus===

====In world distractions====

*2D:  Distracting avatars  
*2D: my club shine glitzier owners tag got in the way
*2D:  I was distracted by my own curiosity of the technology  
*3D: Disruptions from others in chat
*3D: Noise or excessive gestures of certain people.
*3D: Some others in the room were very disruptive
*3D: Interruptions from people who don't take the education seriously.  
*3D: It would be idea to separate people in the education process as some people make noises during the presentation that distracts from the education.

 

===Outside world distractions===

*2D:  Just the fact it’s the weekend and so many distractions in the house
*2D: Thought it was interesting I may watch it again later, if it’s alright, my daughter kept talking to me during it and I kept getting distracted but I did try and pay attention. 
*2D:  I could do other things at my desk and could answer the phone!
*2D: I guess it’s not good to be able to talk to others during a class where you're supposed to learn something [yahoo messaging]
*2D: Could do things at my desk  
*2D: "real life" interruptions the telephone ringing
*3D: Interruptions from real life  

 

===Time===

*2D: Being new, it held my attention for the whole time
*2D: It went a bit slow.  
*2D: Speed of the presentation was a little slow
*2D: The narrator was a bit monotone which caused me to get bored a couple of times.  
*2D: I lost focus for a little.
*2D: found myself zoning out a little bit.
*2D: voice got monotonous
*3D: It actually held my attention! Quite the accomplishment if I do say so myself!
*3D: It was fast.  
*3D: The soothing voice of the narrator kept me engaged.     
*3D: Easy to stay concentrated  
*3D:  The images kept mind from wondering.
*3D: It was exceptionally quick
*3D:  Just a little fast for me a time or two
*3D:  There were a few times it went a little fast

 

===Navigation===

*2D:  I didn't see the words the best way cause of the chair.  
*2D:  Seating made vision difference which had to be adjusted more than once  
*3D: Hard to put screen right
*3D:  Models that were rotating sometimes blocked the text   
*3D: I had to situate my view to read the board
*3D: Display was blocked many times.
*3D: Had to peek round the 3D bridges to read the text



</div>

[[Category:Learning In Virtual Worlds]]
[[Category:Book - Real Learning in Virtual Worlds]]


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