Web-based Learning Solutions for Communities of Practice
Web-based Learning Solutions for Communities of Practice
Web-based Learning Solutions for Communities of Practice
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spectrum in order to specifically determine the<br />
effectiveness <strong>of</strong> different technologies and new<br />
learning methods. (Alberts, B. 2009, 15).<br />
Ilomäki (2008, 33-37) has been mapping a<br />
list <strong>of</strong> teachers’ problems when implementing<br />
ICT scenarios into educational practices. The author’s<br />
focus was limited to a teacher’s individual<br />
characteristic such as individual pedagogical<br />
conceptions and problems they experience while<br />
preparing the lessons as well. Very <strong>of</strong>ten, teachers<br />
with coherent ICT skills use more ICT solutions<br />
in their teaching and they do it in a more multifaceted<br />
and student-oriented way (Moseley &<br />
al. 1999; Hakkarainen 2001; Kankaanranta &<br />
Puhakka 2008). Even more, meta-studies related<br />
to immersive learning environments seem to<br />
provide a clear evidence <strong>for</strong> a specific efficiency<br />
<strong>of</strong> this type <strong>of</strong> educational technology: “The<br />
more a virtual immersive experience is <strong>based</strong> on<br />
design strategies that combine actional, symbolic,<br />
and sensory factors, the greater the participant’s<br />
suspension <strong>of</strong> disbelief that she or he is “inside” a<br />
digitally enhanced setting” (Dede 2009, 66). The<br />
immersive interfaces utilising the visual reasoning<br />
ability gives an opportunity to transfer educational<br />
experience from classroom to (other) real-world,<br />
open learning environments.<br />
COMBINING REAL HANDS-<br />
ON LEARNING INTO VISUAL<br />
AND AUGMENTED REALITY<br />
Hot Air Balloon is a classical science centre<br />
exhibit example provided in several institutes<br />
around the world, too. That was one <strong>of</strong> the reasons<br />
why it was chosen as a case within the described<br />
CONNECT/EXPLOAR learning scenario. The<br />
basic approach was to gain more educational value<br />
from the exhibit by using Augmented Reality –technology<br />
added to this classical exhibit. The main<br />
pedagogical goal was to teach the skills <strong>of</strong> doing<br />
observations. This was possible because by the ARsolutions<br />
certain invisible phenomenon could be<br />
198<br />
Visualising the Invisible in Science Centres and Science Museums<br />
done visible by animations and demonstrations. In<br />
this case the main phenomenon was temperature and<br />
molecule movement, i.e. Bolzmann constant.<br />
Testing<br />
Very <strong>of</strong>ten in the field, just paper-and-pencil tests<br />
are applied to monitor cognitive knowledge and<br />
achievement. However, science and technology<br />
has become more and more visual, and many<br />
<strong>of</strong> the skills trained and taught are not textual.<br />
There<strong>for</strong>e, “there may be a mismatch between the<br />
structure <strong>of</strong> the knowledge and the structure <strong>of</strong> the<br />
print and oral language media traditionally used<br />
both impart and test that knowledge (Greenfield<br />
2009, 71)”. Consequently, testing in this study<br />
contained also non-text <strong>based</strong> tests.<br />
Tests <strong>for</strong> the Students<br />
First <strong>of</strong> all, we applied a visual reasoning ability<br />
-test, in detail, the VRA-Visual Reasoning Ability<br />
test published by Raven (2000). With regard<br />
to the virtual and visual nature <strong>of</strong> the topic, three<br />
major issues supported our choice: 1. the test is<br />
standardised, approved and used in many countries<br />
and cultures; 2. no translations are needed; and<br />
last but not least; 3. young people tend to like to<br />
administrate this type <strong>of</strong> test which they don’t<br />
perceive as <strong>for</strong>mal education type <strong>of</strong> task.<br />
Secondly, <strong>for</strong> measuring the motivation (intrinsic,<br />
instrumental, and situation motivation)<br />
we administered two measures, the one <strong>of</strong> Deci<br />
& Ryan (1993) called IMI (Intrinsic Motivation<br />
Inventory) and the one <strong>of</strong> Salmi (1993; 2003)<br />
on our pre-test schedule. Thirdly, the cognitive<br />
knowledge <strong>based</strong> on 13 items was monitored<br />
on two different schedules, be<strong>for</strong>e and after the<br />
AR-intervention and science centre visit. Forth,<br />
we classified our participants with regard to their<br />
school grades given by their teachers in science,<br />
mathematics, and native language into three categories:<br />
A+ = Above average (25%), A = Average<br />
(50%); A- = Below average (25%).Finally, we