Students’ expectations of the learning process in virtual
reality and simulation-based learning environments
Tuulikki Keskitalo
University of Lapland
Expectations for simulations in healthcare education are high;
however, little is known
about healthcare students’ expectations of the learning process in
virtual reality (VR)
and simulation-based learning environments (SBLEs). This research
aims to describe
first-year healthcare students’ (N=97) expectations regarding
teaching, studying, and
learning in such environments. In addition, it measures students’
expectations of
instructors, their academic self-perception, and atmosphere, as
well as whether there
are differences between the expectations of adult and young
students. Data was
collected through a questionnaire from two different universities
of applied sciences in
Finland in spring 2009, and analysed using statistical and
qualitative methods.
Overall, students have quite high expectations of the activities
that take place in VR
and SBLEs. Adult learners in particular seem to have high
expectations compared to younger students.
Introduction
Healthcare educators have long used simulations to enhance patient
safety. These
simulations vary from a simulated operating theatre with a
sophisticated, high-fidelity
human patient simulator, to a human who acts as a simulated patient
(Bradley, 2006).
These days, advances in technology have made it possible to create
simulations that
fully engage learners in the environment and the learning process
(Bradley, 2006; Cobb
& Fraser, 2005). Thus, the utilisation of virtual realities
(VRs) in healthcare education is
also growing rapidly (Kneebone, 2003; Rosen, 2008).
In recent years, interest has grown in examining students’
expectations and
perceptions of the educational environment in medical schools since
learning
environments are in many ways related to students’ behaviour,
academic
achievements, satisfaction, and aspiration (Miles & Leinster,
2007). However, research
related to expectations about the learning process in VR and
simulation-based learning
environments (SBLEs) remains absent. Expectations for simulations
are high in
healthcare education; their use is expected to improve patient care
and enhance patient
safety. In healthcare education, simulations are expected to
improve learning and
provide students with experiential learning opportunities
(Cleave-Hogg & Morgan,
2002; Gaba, 2004; Loke, Blyth & Swan, 2012; Rall &
Dieckmann, 2005). Simulations
potentially provide a safe and realistic learning environment in
which repeated
practice is possible. Additionally, some expect simulations to
enable the integration of
theory into practice (Issenberg, McGaghie, Petrusa, Gordon &
Scalese, 2005; Rall &
Dieckmann, 2005).
842 Australasian Journal of Educational Technology, 2012,
28(5)
This research aims to describe healthcare students’ (N=97)
expectations regarding
teaching, studying, and learning in VR and SBLEs prior to
experiencing them. It also
examines the kind of expectations students have of their
instructors, atmosphere, and
themselves as learners. Here, studying and learning are used
separately because the
purpose is to emphasise students’ active role in the learning
process. That is, teaching
does not always lead to learning; rather students’ own activities
are also necessary
(Kansanen et al., 2000; Uljens, 1997). The data was collected from
two different
universities of applied sciences in Finland in spring 2009, using
mixed methods. The
questionnaires’ open answers were analysed qualitatively and used
to support the
quantitative analysis. This article is part of a larger study whose
overall aim is to
develop a pedagogical model for VR and SBLEs using design-based
research methods
(Brown, 1992; Design-based Research Collective, 2003; see also
Keskitalo, Ruokamo &
Väisänen, 2010). The first phase consisted of thematic interviews
with teachers. The
goal was to determine the kinds of pedagogical approaches and
educational tools
teachers have adopted when teaching in VR and SBLE (Keskitalo,
2011). In this second
phase, the aim is to learn about students’ expectations of the
learning process in VR
and SBLEs (see also Keskitalo, 2009). This should enable the design
of a user-friendly
pedagogical model and ensure its integration into healthcare
education practice.
The overall aim of this research is to change pedagogical practices
in VR and SBLEs by
embedding learning theoretical views into teaching practice,
because previous research
has shown that healthcare education remains somewhat intuition and
opinion-based
(Ramani, 2006). In other words, teachers are using their opinions
or intuition to
determine their pedagogical methods. What follows is an
introduction to the literature,
research questions, and methods. The last section presents and
discusses the research
results.
Literature review
Previous studies of students’ expectations
In this study, the term “expectations” refers to students’
expectations regarding the
learning process in VR and SBLEs. Many definitions are used to
describe expectations
within the service delivery sectors (Higgs, Polonsky & Hollick,
2005; Shewchuk et al.,
2007). Expectations could be expected or predictive, which, in this
study, could be
students’ predictions of or beliefs about teaching and studying in
VR and SBLEs. In
other words, what will occur in these learning environments?
Normative expectations
are expectations about what should occur in VR and SBLEs (Higgs et
al., 2005;
Shewchuk et al., 2007). There are also experience-based
expectations, which are
expectations that follow prior experience, in this case, healthcare
education or practice
(Parasuraman, Zeithaml & Berry, 1988).
In medical and healthcare education, the existing research
literature related to
students’ expectations of teaching and learning in VR and SBLEs is
limited. So far, the
research that has been done relates to medical students’
perceptions of their
educational environment (Amin, Tani, Eng, Samarasekara & Huak,
2009; Miles &
Leinster, 2007) and their expectations for their future medical
practice (Draper &
Louw, 2007; O’Connell & Gupta, 2006). One study tried to
develop a standardised
approach to assessing physicians’ expectations and perceptions
about continuing
medical education (Shewchuk et al., 2007). Miles and Leinster
(2007) studied first-year
medical students’ expectations about the learning environment and
compared those
Keskitalo 843
results to the students’ actual perceptions. Their results revealed
that students initially
encounter their learning environment with high expectations,
although they do not
expect the learning environment to be perfect. Overall, students’
expectations for
learning and teachers, and their academic self-perception and
social self-perception
were higher than their actual perceptions. In particular, the study
found that teachers
were worse at providing feedback than students expected and did not
provide the
constructive criticism that students expected. The learning
objectives were also unclear
to students, the school schedule was not scheduled as well as they
expected, and the
support system for stressed students was poorer than they had
expected. In their
study, Miles and Leinster (2007) used the revised Dundee Ready
Education Environment
Measure (DREEM) (Roff et al., 1997) to measure medical students’
expectations about
their educational environment.
In Draper and Louw's (2007) study, most medical students found the
curriculum’s
content contrary to their expectations. They expected their medical
degree to be mostly
biomedical and scientific in content, and did not expect the
curriculum’s psychosocial
component to be a feature of studying medicine. These students
viewed the medical
profession as significant and influential. Also, O’Connell and
Gupta (2006) found that
despite the challenges of practising medicine, students have
realistic perceptions of the
current medical practice environment.
Teaching and learning in virtual reality and simulation-based
learning
environments
The apprenticeship model has long been used in medical and
healthcare education to
teach basic principles and skills to novice learners (Kneebone,
2003; Kneebone, Scott,
Darzi & Horrocks, 2004). In the traditional apprenticeship
model, an apprentice views
the master executing a task, and then the apprentice tries to
execute the task with the
master’s guidance and help (Rogoff, 1990). The main problem with
this model has
been the issue of patient safety because students were practising
with real patients.
Nowadays, problem-based learning (PBL) has become a popular
approach to teaching
in medical and healthcare education (e.g., Barrows & Tamblyn,
1980). PBL sees
learning as a problem-solving process in which students deal with
authentic and illstructured
problems that originate in real-life work. During the learning
process,
teachers work mostly as tutors or facilitators and support
students’ learning, whereas
students work in groups and engage in self-directed learning
(Hmelo-Silver, 2004;
Hmelo-Silver & Barrows, 2006). These approaches are based
mainly upon experiential
learning approaches (Hmelo-Silver, 2004), for example, Kolb’s
(1984) experiential
learning model that views learning as a continuous process grounded
in experience. In
addition, PBL utilises the ideas of social-constructivism and
socio-cultural theory (Lave
& Wenger, 1991; Tynjälä, 1999; Vygotsky, 1978).
Simulators and simulations have been introduced to healthcare
education because of
their ability to provide students with experiential learning
opportunities and a safe
practice environment (Cleave-Hogg & Morgan, 2002). In
simulation settings, a typical
course structure consists of an introduction, simulator briefing,
scenarios, debriefing,
and course ending (Dieckmann, Gaba & Rall, 2007; Joyce, Calhoun
& Hopkins, 2002).
According to Joyce and associates’ (2002) Learning through
simulations model, in the
introductory phase, the teacher presents the course topic and the
most important
concepts, and explains the simulation concept to students. This
phase also includes
explanations of how the course is organised, and the kinds of
pedagogical models and
844 Australasian Journal of Educational Technology, 2012,
28(5)
methods it uses. During the simulator briefing, the participants
begin to get into the
simulation. This is the phase in which the teacher introduces the
scenario. As a
learning trigger, the teacher uses either problems or real-world
examples. The second
phase includes the introduction of the simulation’s goals, the
participants’ roles, the
rules and procedures they have to follow, and the decisions they
have to be able to
make during the scenario. At the end of the second phase, the
teacher ensures that
everybody has understood the instructions. In phase three, students
participate in the
simulation. During this phase, students are active while the
teacher functions as a
facilitator or instructor by giving feedback, correcting
misunderstandings, and
evaluating students’ performance and decisions. However,
comprehensive evaluations
and reflections occur during the debriefing phase when the teacher
encourages
students to analyse the whole process, including how the scenario
went, what
problems they encountered, and what they learned. In this phase, it
is important for
students to compare the simulation to the real world.
Research questions
With these theories and the cited literature as background, this
study focuses on
students’ expectations related to teaching, studying, and learning
processes in VR and
SBLEs. The following research questions were set:
• What kinds of expectations do students have about teaching,
studying, learning,
and instructors in VR and simulation-based learning
environments?
• What kinds of expectations do students have of their academic
self-perception and
atmosphere in VR and simulation-based learning environments?
• Are there differences between the expectations of adults and
those of young
students?
Methods
Data collection
This research collected data using a questionnaire given to the
students (N=97). This
questionnaire was partially based on the DREEM (Roff et al., 1997)
as well as other
questionnaires that have been developed to measure meaningful
learning (Nevgi &
Löfström, 2005; Hakkarainen, 2007). The original DREEM was a
50-statement
questionnaire which was developed to measure the educational
environment of health
professions. DREEM's statements were divided into five subscales,
namely students`
perception of teaching, teachers, academic self-perception,
atmosphere, and social selfperception.
However, for the purpose of this research, some questions from
the
original DREEM were eliminated and questions regarding the
expectations of studying
and learning were added, since the original DREEM examines mainly
the perceptions
of teaching. The additional questions were used to measure the
expectations of the
meaningfulness of learning (Nevgi & Löfström, 2005;
Hakkarainen, 2007), which
provided essential information for the design of the pedagogical
model (Keskitalo et
al., 2010). Some statements from the DREEM were also revised for
this research, for
example, “I am confident about passing this year” was changed to “I
am confident
about passing this course,” or “The atmosphere is relaxed during
the ward teaching”
was changed to “During the debriefing, the atmosphere will be
relaxed.” The original
DREEM questions that were eliminated were considered unsuitable for
the purpose of
Keskitalo 845
this research, e.g., the questions “Cheating is a problem in this
school” or “The teachers
get angry in class” were considered irrelevant for our purpose. The
sub-scale,
“Students' social self-perception,” was almost completely omitted
since it was
considered irrelevant. However, one statement was reworded from
“There is a good
support system for students who get stressed” to “Embattled
students will get help,”
and removed to the sub-scale in our questionnaire that measures
atmosphere.
Finally, to check the meaningfulness of the questionnaire, 10
students from the
Rovaniemi University of Applied Sciences completed the
questionnaire and gave us
feedback. Thereafter, a tentative analysis and final revisions were
made. These test
questionnaires were not included in this research. The final
questionnaire asked
students for background information and questions related to their
expectations of
teaching, studying, and learning processes in VR and SBLEs. In
addition, it measured
students’ expectations regarding their instructor, academic
self-perception, and
atmosphere. Each of the 65 statements was scored on a continuum, in
which 1 = “the
statement does not describe my expectations at all,” 2 = “the
statement describes my
expectations some,” 3 = “the statement describes my expectation
neither poorly nor
well,” 4 = “the statement describes my expectations quite well,”
and 5 = “the statement
describes my expectations well.” Also, one open question gave the
students
opportunity to write about any other expectations they had. In this
research, all the
activities were conducted in Finnish, and the translations into
English were made by
the author and checked by a native-speaking transcription
service.
The data was collected at Rovaniemi University of Applied Sciences
(Rovaniemi,
Finland) and Arcada University of Applied Sciences (Helsinki,
Finland,
http://apslc.arcada.fi/) in
January and February 2009. Both schools have simulation
centres consisting of separate rooms where students can practise
specific skills or go
through entire scenarios related to the content areas. When
studying, one room is
usually decorated for the students’ rehearsal, and contains a
patient simulator and a
monitor displaying the vital signs of the patient simulator. Next
to this room is a space
for the facilitator, where he or she can control the simulator and
guide the students’
learning process via audio devices. One room is dedicated to
debriefing and contains
appropriate technology, such as video and audio recording devices,
which can be used
in debriefing sessions to complement the students’ reflection. The
simulation centre
situated at the Rovaniemi University of Applied Sciences (known as
ENVI, see
http://www.envi.fi/) also
includes an immersive full-scale 3-D (three-dimensional)
incident environment simulation projection, in which users can
view, navigate, and
interact with a handheld device (for detailed description, see
Keskitalo, 2011).
Therefore, ENVI is kind of a mixed-reality learning environment as
it combines
physical environment and simulation manikins with 3-D simulation
projection (see
Haukkamaa, Yliräisänen-Seppänen & Timonen, 2010). The idea of
ENVI is that
healthcare students or professionals can practice cooperation
during the entire
healthcare process, from the scene of an accident, to a hospital,
and finally, to
rehabilitation. However, this research did not analyse the
influences of the type of
simulation centre; it focused instead on the students’ expectations
of the learning
process in these environments.
The participants were first-year healthcare students who were
chosen because they
had little experience with training in VR and SBLEs, though they
were expecting to
train in this type of learning environment in the future. The
purpose of choosing them
on this basis was to guarantee that their experiences did not
affect their expectations.
The participants volunteered to take part and had an opportunity to
refuse or
846 Australasian Journal of Educational Technology, 2012,
28(5)
withdraw from the study at any time. The participants received no
compensation for
taking part in the study.
Data analysis
The quantitative data was analysed using SPSS 15.0 for Windows.
Altogether, 97
students volunteered to take part in the study, 82 of whom (84.5%)
were female and 15
(15.5%) male. The respondents’ mean age was 27 years. The youngest
respondent was
19 and the oldest was 53 years old. Sixty-one of the respondents
(62.9%) were nursing
students. In addition, some of the students were studying
paramedics (n=2; 2.1%),
physiotherapy (n=17; 17.5%), occupational therapy (n=5; 5.2%), and
healthcare (n=9;
9.3%). The data was analysed using factor analysis and reliability
analysis (Cronbach’s
alpha). For the factor analysis, the statements were selected based
on previous studies.
However, as a result of the analysis, some statements that belonged
to the original
DREEM or the questionnaires that measured meaningful learning were
discarded.
Based on the results of factor analysis and reliability analysis,
the sum variables were
computed using a mean of the items within the sub-scale. For the
analysis, the sum
variable was also categorised into five categories (1 = no
expectations, 2 = a little
expectations, 3 = neither little nor a lot expectations, 4 = quite
a lot of expectations, 5 =
a lot of expectations) to get a better understanding of the level
of the participants’
expectations. Kolmogorov-Smirnov tests, instead of t-tests, were
used to determine
whether there were differences in expectations between adult and
young students,
because the distribution of the test variables was skewed. The
individual items’ means
and standard deviations were also reported. The qualitative data
was analysed and
used to support the quantitative analysis.
Results
Students’ expectations of the learning process in VR and
SBLEs
The first research question was concerned with the kinds of
expectations students have
regarding teaching, studying, learning, and instructors in VR and
SBLEs. Table 1
presents the factors and the statements with the means and standard
deviations that
belong to each factor (with the loadings of 0.517 to 0.890).
Cronbach’s alpha for each
factor is included in the table along with the means and standard
deviations of the sum
variables, which are the empirical counterparts of the
factors.
The results showed that Cronbach's alpha values were all above 0.7
(0.861 to 0.897),
which indicates both an acceptable internal consistency and that
the variables can be
used to describe students’ expectations (Nunnally, 1978). As the
results indicate,
students’ expectations of teaching (M=3.65; SD=0.54) in VR and
SBLEs were quite high;
49.5% of the respondents had quite high expectations of teaching in
these
environments, and 5.2% expected a lot. Most often, students
expected that teaching
would help to develop their competence (M=4.16; SD=0.83), would be
stimulating
(M=3.99; SD=0.92), and that students’ needs were the starting point
for teaching
(M=3.86; SD=0.97). Therefore, the variable was named “Inspiring and
individuallytailored
teaching”. This result was expected because many previous
researchers have
indicated that students enjoy simulation exercises and the
opportunities provided to
practise skills before encountering the real situations
(Cleave-Hogg & Morgan, 2002;
Holzman et al., 1995; Moule, Wilford, Sales, & Lockyer, 2008),
which the following
excerpts also confirm:
Keskitalo 847
Table 1: Statements, Cronbach's alpha, means and standard
deviations for each factor
Factor Statements in the questionnaire
Cronbach's
alpha for
each factor
Means (M)
and SD of the
sum variable
1 I will be encouraged by the teaching (M=3.66;
SD=0.92)
2 The teaching will be stimulating (M=3.99; SD=0.92)
3 Students’ needs are the starting point for teaching
(M=3.86; SD=0.97)
4 The teaching will help to develop my competence
(M=4.16; SD=0.83)
5 The teaching will help to develop my confidence
(M=3.56; SD=1.03)
6 The teaching takes students’ individuality into
account (M=3.17; SD=1.02)
Inspiring
and
individually
-tailored
teaching
7 The teaching encourages me to be an active learner
(M=3.67; SD=0.98)
0.897 M=3.65;
SD=0.54
1 In lessons, students have the opportunity to actively
acquire, evaluate, and apply information (M=3.67;
SD=0.98)
2 While studying in a simulation-based learning
environment, I have the ability to utilise my prior
knowledge (M=4.03; SD=0.86)
3 I have the opportunity to set my own goals for
studying (M=4.02; SD=0.86)
4 With the instructor’s guidance, I have the
opportunity to practise my skills (M=3.76; SD=1.05)
5 When studying, I have the opportunity to take
advantage of my prior experiences (M=3.93;
SD=0.80)
6 During the course, I have the opportunity to
familiarise myself and practise with the equipment I
will need in my future work (M=4.16; SD=1.13)
7 During the lessons I have the possibility to
repeatedly practise my skills (M=3.66; SD=0.90)
8 While studying in a simulation-based learning
environment, I can feel safe (M=3.98; SD=0.83)
Individual
and competence-
based
studying
9 During the lessons, I have the opportunity to
critically evaluate my own learning (M=3.92;
SD=0.90)
0.862 M=3.91;
SD=0.64
1 I can apply the things that I have learned during the
course (M=4.23; SD=0.85)
2 The things that I learn in a simulation-based
learning environment help me to understand things
better than I did before (M=4.23; SD=0.80)
3 I believe that using the equipment I need in my
work will be easier after this course than it was
before (M=4.13; SD=0.91)
4 My problem-solving skills will develop during this
course (M=3.66; SD=1.06)
Transferable
learning
outcomes
5 Studying in a simulation-based learning
environment will develop my skills (M=4.18;
SD=0.91)
0.861 M=4.09;
SD=0.73
848 Australasian Journal of Educational Technology, 2012,
28(5)
1 Instructors are knowledgeable (M=4.29; SD=0.83)
2 Teachers can provide proper and constructive
criticism (M=3.69; SD=0.97)
3 The teachers will have good communication skills
with patients (M=3.71; SD=0.94)
4 The teachers will give clear examples (M=4.00;
SD=0.85)
Competent
and wellprepared
instructors
5 The teachers will be well prepared for teaching
(M=4.01; SD=0.94)
0.878 M=3.94;
SD=0.75
I expect enthusiastically to get into an ENVI environment; we have
not yet been in the
ENVI. I expect that I will test and practise different kinds of
situations and tricks.
(Student, number 6)
It is nice that we can practise in a simulated situation before
being with real patients. I
am sure that I am not as nervous as I would be if there was no
simulated training.
(Student, number 40)
Students had quite high expectations of studying (M=3.91; SD=0.64)
too; 67% of the
respondents expected quite a lot or a lot. As the sum variable’s
name (“Individual and
competence-based studying”) indicates, students particularly
expected to be able to utilise
their prior knowledge (M=4.03; SD=0.86) and set their own goals for
studying (M=4.02;
SD=0.86). Students also expected to have the opportunity to
familiarise themselves and
practise with the equipment they would need in their future work
(M=4.16; SD=1.13),
although, on this question, the standard deviation was quite high.
This indicates that
some of the students expected that they could familiarise
themselves and practise with
the equipment, but others had lower expectations in this regard. As
these results
indicate, students expected their studying to be constructivist and
self-directed in
nature. Constructivist learning means that learners build
meaningful knowledge upon
their previous knowledge (e.g., Jonassen, 1995; Tynjälä, 1999);
self-directed learning
assumes that learners can set their own goals for learning and be
responsible for
achieving them (e.g., Knowles, 1975).
“Transferable learning outcomes” was used to describe the
expectations for learning
(M=4.09; SD= 0.73) in these environments. Individual items indicate
that most often
students expected to learn things that were applicable (M=4.23;
SD=0.85), and that
learning in VR and SBLEs would help them to understand things
(M=4.23; SD=0.80).
In addition, students expected the use of equipment to be easy
(M=4.13; SD=0.91) and
that they would become highly skilled (M=4.18; SD=0.91) after the
course. These
expectations might come true; previous studies have shown that
students benefit from
simulation-based training. For example, in Moule and associates’
(2008) study,
students learned skills, but they also felt that training in a
simulation-based
environment increased their knowledge and understanding of the
subject matter.
Overall, 41.2% of the respondents expected quite a lot and 32%
expected a lot from
learning in these environments.
Students expected quite a lot from instructors (M=3.94; SD=0.75) as
well; 33.0% of the
students expected quite a lot from their instructors, and 26.8%
expected a lot. Students
especially expected their instructors to be competent (M=4.29;
SD=0.83) and well
prepared for teaching (M=4.01; SD=0.94), and to give clear examples
(M=4.00;
SD=0.85). Therefore, the sum variable was titled “Competent and
well-prepared
instructors.” Amin et al. (2009) also found similar results when
they measured the
characteristics of university teachers in medical school. The
characteristics that
Keskitalo 849
students valued most were being knowledgeable about the subject
matter, being
friendly and approachable, and having well-organised teaching
materials.
These results place high demands on the instructors. The
instructor’s role in
simulation-based training is quite different from that of
traditional lecture-based
instruction. Research has indicated that instructors need
development, especially
regarding different kinds of pedagogical methods (Keskitalo, 2011)
and in how to
facilitate debriefing (Østergaard, Østergaard & Lippert,
2004).
Students’ expectations of their academic self-perception and
atmosphere
The second research question concerned the kinds of expectations
and perceptions
students have of their academic self-perception and atmosphere in
VR and SBLEs.
Table 2 presents the factors and the statements with the means and
standard
deviations that belong to each factor (with the loadings of 0.825
to 0.835). Cronbach’s
alphas for each factor and the means and standard deviations of the
sum variables are
also included in the table.
Table 2: Statements, Cronbach's alpha, means and standard
deviations for each factor
Factor Statements in the questionnaire
Cronbach's
alpha value
for each
factor
Means (M)
and SD of
the sum
variable
1 I am confident about passing this course (M=3.73;
SD=0.84)
2 I believe that I will be well prepared to practise my
profession (M=3.46; SD=1.01)
3 I believe that I can manage different kinds of
exercises (M=3.86; SD=0.85)
4 I will be able to memorise all I need from this course
(M=3.12; SD=0.92)
Confident and
competent
students
(academic selfperception)
5 Learning strategies that have worked for me before
will continue to work for me now (M=3.41; SD=0.91)
0.835 M=3.51;
SD=0.70
1 I will feel comfortable during the lessons (M=3.76;
SD=0.77)
2 During the debriefings, the atmosphere will be
relaxed (M=3.64; SD=0.77)
3 Embattled students will get help (M=3.70; SD=0.92)
4 I believe that the atmosphere will be relaxed during
the lessons (M=3.99; SD=0.77)
Relaxed and
comfortable
atmosphere
5 The atmosphere will motivate me to learn (M=3.66;
SD=0.95)
0.825 M=3.77;
SD=0.64
The results show that students’ expectations concerning their
academic self-perception
(M=3.51; SD=0.70) were moderately high. As the sum variable’s name
(“Confident and
competent students”) indicates, students were especially certain
that they could manage
different kinds of exercises (M=3.86; SD=0.85) and that they would
pass the course
(M=3.73; SD=0.84). “Relaxed and comfortable atmosphere” was used to
describe the
students’ expectations of the atmosphere, which were quite high
(M=3.77; SD=0.64).
Individual items indicated that most often students expected that
the atmosphere
would be relaxed (M=3.99; SD=0.77) and comfortable (M=3.76;
SD=0.77) during the
lessons, and that embattled students would get help (M=3.70;
SD=0.92). Although
simulation exercises sometimes cause nervousness (Alinier, Hunt,
Gordon &
850 Australasian Journal of Educational Technology, 2012,
28(5)
Harwood, 2006; Cleave-Hogg & Morgan, 2002), students in this
study expected the
atmosphere to be relaxed during the lessons, which is a
prerequisite for good learning
(e.g., Cassaday, Bloomfield & Hayward, 2002). In
simulation-based training, it is
important that students be allowed to make mistakes without being
ridiculed or
humiliated. Especially in debriefing sessions, it is crucial that
students are able to freely
express their views and learn from their mistakes (Fanning &
Gaba, 2007).
Differences in expectations between adult and young students
The third research question was: Are there differences between the
expectations of
adult and young students? The respondents’ mean age was 27 years;
the youngest
respondent was 19 years old and the oldest was 53. Therefore,
before the analysis, the
participants were divided into two age groups based on the
distribution that is
popular in statistics and labour markets in Finland (Herranen &
Penttinen, 2008): 1)
Adult students (>25 years old; n=39; 40.2%); and 2) Young
students (≤25 years old;
n=58; 59.8%). To determine whether there were statistically
significant differences
between adult and young students’ expectations, the
Kolmogorov-Smirnov test was
used. For analysis, the sum variables were categorised into three
categories so that
values 1 and 2 described little expectations, and the values four
and five described
great expectations. Value three was a neutral value. Percentile
distributions of the
adult and young students with little or a lot of expectations
regarding teaching,
studying, learning, instructors, their academic self-perception,
and atmosphere are
presented in Figure 1.
Figure 1: Percentages of adult and young students’ expectations
regarding teaching,
studying, learning, instructor, academic self-perception, and
atmosphere
Keskitalo 851
As Figure 1 indicates, adult students seemed to have higher
expectations than young
students. The most significant differences were found in
expectations regarding
teaching (K-S test = .0469, p = .000, pn
toimeentulo ja opiskelu. [Student research 2010. Higher education
students living and studying.]
Opetus- ja kulttuuriministeriön julkaisuja 2010:18.
Shewchuk, R. M., Schmidt, H. J., Benarous, A., Bennett, N. L.,
Abdolrasulnia, M. & Casebeer, L.
L. (2007). A standardized approach to assessing physician
expectations and perception of
continuing medical education. Journal of Continuing Education in
the Health Professions, 27(3),
173-182. http://dx.doi.org/10.1002/chp.121
Stringer, R. W. & Heath, N. (2008). Academic self-perception
and its relationship to academic
performance. Canadian Journal of Education, 31(2), 327-345.
http://www.jstor.org/stable/20466704
Tynjälä, P. (1999). Towards expert knowledge? A comparison between
a constructivist and a
traditional learning environment in the university. International
Journal of Educational
Research, 31(5), 357-442. http://dx.doi.org/10.1016/S0883-0355(99)00012-9
Uljens, M. (1997). School didactics and learning. Hove, East
Sussex: Psychology Press.
Valentine, J. C., DuBois, D. L. & Cooper, H. (2004). The
relation between self-beliefs and
academic achievement: A meta-analytic review. Educational
Psychologist, 39(2), 111-133.
http://dx.doi.org/10.1207/s15326985ep3902_3
Vygotsky, L. (1978). Mind in society: The development of higher
psychological processes. Cambridge:
Harvard University Press.
Østergaard, H. T., Østergaard, D. & Lippert, A. (2004).
Implementation of team training in
medical education in Denmark. Quality and Safety in Health Care,
13(1), i91-i95.
http://dx.doi.org/10.1136/qshc.2004.009985
Author: Tuulikki Keskitalo MEd. PhD student, Researcher
Centre for Media Pedagogy, Faculty of Education
University of Lapland, PO Box 122, FI-96101 Rovaniemi,
Finland
Email: tuulikki.keskitalo@ulapland.fi
Web: http://tuulikkikeskitalo.wordpress.com/
Please cite as: Keskitalo, T. (2012). Students’ expectations of the
learning process in
virtual reality and simulation-based learning environments.
Australasian Journal of
Educational Technology, 28(5), 841-856.
http://www.ascilite.org.au/ajet/ajet28/keskitalo.html
在虚拟现实和基于仿真学习环境的学习过程中学生的期望[/B]
[/B]
在医学教育方面仿真的期望值很高。但是，人们对在虚拟现实和基于仿真学习环境的学习过程中医学学生的期望却知之甚少。这个调查旨在描述一年级医学学生（97人）关于教，学以及在这些环境中学习的期望值。另外，它还测量了学生对教师的期望，以及学术上的自我认知和学术氛围，还测量了是否成年人和年轻学生的期望存在差异。数据来源于一份2009年春天在芬兰两所不同的应用科学类大学的调查问卷，此问卷采用了统计法和定性法分析。总的来说，学生在虚拟现实和基于仿真学习环境中的活动有着相当高的期望。较年轻学生而言，成年学习者往往有更高的期望。
引言[/B]
医学教育家曾用仿真来增强病患的安全感。这些仿真在带有复杂高保真病患模拟器的仿真手术室和一个假装成病人的人之间变化。这些天，技术上的改进使得在学习环境和过程中充分参与的学习者创建仿真成为可能。因此，虚拟现实在医学教育方面的应用迅速发展起来。
近几年，自从学习环境与学生的行为、学术成就、满意度和渴望度等许多方面相关联后，人们对测试医学学生的期望和他们在教育环境中的认知越来越感兴趣。但是，对虚拟现实和基于仿真学习环境的学习过程中学生的期望的调查研究仍是空白。在医学教育方面仿真的期望值很高，人们希望它们能用来改善对病患的照顾和增强病患的安全感。在医学教育方面，人们希望通过仿真来提高学习效率，以及给学生提供从实践中学习的机会。在重复练习可能的前提下，仿真潜在的提供了一个相对安全和现实的学习环境。此外，一些仿真已能逐步将理论与实践相结合。
这个调查旨在医学学生实践之前描述他们在教、学以及在虚拟现实和基于仿真学习环境中学习的期望值。同时也测量了学生对教师、学术氛围以及作为学习者本身的期望的性质。在这里，研究和学习分开来用是为了强调学生在学习环境中扮演的角色。换言之，教学不总是引导学生学习，学生自己的活动性也非常重要。数据来源于在2009年春天对芬兰两所不同的应用科学类大学的调查，采用了混合研究方法。问卷的公开答案被定性的分析，并用于支持定量分析法。这个课题是一个庞大研究的一部分，这个研究的目的是用基于设计的研究方法来开发虚拟现实和基于仿真学习环境中的教学模型。第一阶段包含对教师的主题研究。目的是为了确定教学方法的类型，以及教师在虚拟现实和基于仿真学习环境中教学采用的教学工具。第二阶段的目的是学习学生关于在虚拟现实和基于仿真学习环境的学习过程中的期望。这样做能使设计的教学模型更容易使用，同时也确保最终能应用到医学教育实践中去。
这个调查的主要目标是通过将学习中的理论观点植入到实践教学，从而改变在虚拟现实和基于仿真学习环境中的教学实践。这是因为先前的调查研究已经表明医学教育留有一些直觉和自我想法。换句话说，老师们正在用自己的想法和直觉来决定教学方法。下列所述是文献的介绍，调查的问题和方法。最后一部分显示并讨论了调查结果。
文献综述[/B]
关于学生期望的先前研究
在这个研究中，术语“期望”指的是在虚拟现实和基于仿真学习环境的学习过程中学生的期望。许多术语过去常常用于描述服务部门的期望。期望可能是预料的或有预测性的，在这个研究中，指的是学生对在虚拟现实和基于仿真学习环境中教和学的预测或信心。也就是说，在这些环境中将会发生些什么。标准的期望就是关于在虚拟现实和基于仿真学习环境中将会发生什么的期望。另外还有那些遵循先前经验的基于经验的期望，在这个情况下，就是指医学教育或实践。
在医学教育中，现存的关于在虚拟现实和基于仿真学习环境的学习过程中学生期望的文献资料是有限的。到目前为止，有关医学学生对教育环境的认知和未来医学实践的期望的调查研究已经结束。研究试着去开发一个标准化的方法来评价内科医生对于持续医学教育的期望和认知。2007年，Miles和Leinster研究了一年级医学学生对于学习环境的期望，并将研究结果与学生真实的认知相对比。结果表明学生对最初接触到的学习环境有很大的期望， 尽管他们并不期望学习环境有多么完美。总的来说，学生们对学习、教师、学术自我认知和社会自我认知的期望远远高于自己实际的认知。尤其，这个研究还发现老师在提供反馈的方面比学生预想的要糟糕，并且没有给学生提供任何他们期望的建设性的评论。给学生的学习目标也没有那么明确，学校的日程安排表也没有像预想那样安排好，缓解学生压力的保障系统也没有预期的那么好。在这个研究中，Miles和Leinster采用了改进的Dundee教育环境测量（DREEM）来测量医学学生在教育环境中的期望。
在Draper和 Louw的研究中，大多数的医学学生发现课程内容与他们的期望相悖。学生们希望自己的医学学位主要是生物医学和科学的范畴，并不期望课程中社会心理学的成分成为医学学习的特征。这些学生把医药职业看作重要的和有影响力的。另外，O’Connell 和Gupta发现不管医学实践的挑战有多大，学生们仍对突发的医学实践环境抱有现实主义的看法。
在虚拟现实和基于仿真学习环境中的教与学
师徒模式被长期用于教授初学者基本原理和技能的医学和医疗保健教育中。在传统的师徒模式中，徒弟看着师傅执行任务，然后徒弟在老师的引导和帮助下完成任务。这个模式主要的问题是病患安全的问题，因为学生是在真实的病人身上进行实践。如今，基于问题的学习(PBL)成为在医学和医疗保健教育中一种比较普及的方法。PBL（基于问题的学习）将学习视为一种问题解决的过程，在这个过程中学生们处理源于实际生活中的的真实的问题。在这个学习过程中，教师的主要工作是辅导、促进和支持学生的学习，学生们主要是分组工作和自主的学习。这些方法主要源于经验学习方法，例如，Kolb的经验教学模式中将学习视作在实践中的连续的过程。另外，PBL（基于问题的学习）利用了社会建构和社会文化的理论。
仿真器和仿真之所以被介绍到医疗保健教育中，是因为他们能够提供给学生从实践中学习的机会和一个安全的实践环境。在仿真的设定中，一个典型的课程结构包括引导，模拟器简介，情景，任务报告和课程总结。根据Joyce的“通过仿真模式学习”，在引导阶段，老师提出课程的题目，最重要的部分，以及给学生介绍仿真的概念。这个阶段包括对课程构成的解释，教学模型的种类和所采用的方法。在模拟器简介过程中，参与者开始接触仿真。这是一个教师介绍情景的阶段。作为学习的引导，老师采用了要么问题要么现实生活中的例子。第二阶段包括方针目标的介绍，参与者的任务，他们需要遵循的规则和程序，和他们在情境中要做的决定。在第二阶段最后，老师要确保每个人明白整个说明。第三阶段，学生们开始参与仿真。在这个阶段中，当老师的功能成为给予反馈、更正错误和评估学生结果和决定的促进者和指导者后，学生们开始发挥自我主动性。然而，综合评价和反馈发生在当教师鼓励学生分析整个过程（包括情景分析，他们遇到的问题和所学到的东西）的简介阶段。在这个阶段，最重要的是学生能将仿真和现实世界做对比。
调查问题[/B]
用上述理论和引用文献作为背景，这个调查集中于在虚拟现实和基于仿真学习环境中学生对教、学及学习过程的期望。设定了下述几个研究问题：
• 在虚拟现实和基于仿真学习环境中，学生对教、学及学习过程有着何种类型的期望？
•
在虚拟现实和基于仿真学习环境中，学生对自我学术认知和学术氛围有着何种类型的期望？
•
在成年人和年轻学生的期望间有没有一些不同？
方法[/B]
数据收集
这个调查通过发放学生（97人）调查问卷来收集数据。这份问卷部分来源于DREEM（教育环境测量），还有其他的问卷是用于测量有意义的学习。最初的DREEM（教育环境测量）是一个50句的问卷，这份问卷用来衡量卫生行业的教育环境。DREEM（教育环境测量）被分为五个部分，也就是学生对教学的认知，教师，学术自我认知，学术氛围和社会自我认知。但是，这份调查为的是，从最初的DREEM（教育环境测量）主要衡量教学认知后，淘汰许多来源于最初的DREEM（教育环境测量）的问题，同时增加关于教与学的期望的问题。附加的问题被用来衡量有意义学习的期望，这个期望提供了教学模型设计的基本信息。DREEM（教育环境测量）的一些部分同样也作为这个调查的修正，例如，“我有信心今年能通过”被改为“我有信心这门课能通过”，或者是“在教学过程中氛围变得轻松”被改为“在任务报告期间，氛围将会变得轻松”。最初的DREEM（教育环境测量）问题因被认为与调查目标不相符而被淘汰。例如，“作弊在学校中是个很严重的问题”“教师在课上发火了”等问题被认为和我们的研究目标不相关。“学生的社会自我认知”这个部分也在被认为与目标不想关之后几乎全部省略了。但是，其中一句“这是一个针对有压力学生的很好的支持系统”被改写成“心烦意乱的学生将会得到帮助”，然后这句话被移动到问卷下方用来衡量学术氛围。
最后，为了检测这个问卷的意义性，来自Rovaniemi大学应用科学系的十名同学完成了问卷，并给了我们回馈。从那以后，一个试探性的分析和最后的修订完成了。这些测试问卷并没有包含在调查之中。最终的调查问卷向学生们索要背景信息，以及关于他们对在虚拟现实和基于仿真学习环境中教、学及学习过程的期望的有关问题。另外，问卷还衡量了学生
关于老师，学术自我认知和学术氛围的期望。每65句在同一连续时间上被计分，分数1 =“这句话一点也没描述我的期望”，分数2=“这句话描述了我的一部分期望”，分数3 =“这句话描述我的期望不算太好也不算太糟”，分数4=“这句话描述我的期望相当好”，分数5=“这句话正好描述了我的期望”。另外，还给了学生一个开放式问题来写他们有的其他期望。在这个调查中，所有的活动都用芬兰语分析，然后作者将其翻译成英文，并有一个本土翻译者复核。
数据在2009年一二月 Rovaniemi大学和Arcada大学应用科学系收集得到。这两个学校都有单独房间组成的仿真中心，在那儿学生可以锻炼特殊技能，还可以浏览目录中的整个情节。当学习时，一个房间经常会因学生的学习需求来装饰，还包括一个假装病人的人，和一个观察者观察病人的生命体征。紧挨着这个房间的是引导者的空间，他们在那儿可以控制假装病人的人，以及引导学生通过音频设备学习。一个房间被供于说明和容纳使用的技术，比如视频和音频设备，用来补充学生们的反馈。位于Rovaniem大学应用科学系的仿真中心也包含一个身临其境的3D仿真放映室，使用者可以观看，操纵，和手持设备互动等等。因此，ENVI（遥感图像处理系统））是一种混淆现实的学习环境，它用3D仿真放映结合了虚拟环境和仿真模型。ENVI（遥感图像处理系统）的想法使医疗学生和专业人员能在整个医疗过程中实践合作，从意外事故的现场，到医院，再到最后复原。但是，这个调查没有分析仿真中心类型的影响；它只关注在学生在这些环境的学习过程中的期望。
被选中的参与者是大一的医学学生，之所以选他们是因为他们在在虚拟现实和基于仿真学习环境中有很少的实践经验，尽管他们期望将来在这种类型的学习环境中得到锻炼。选择他们的目的是基于保障他们的实践经验不会影响到期望。志愿者自愿参加，任何时候都有机会拒绝和退出这项研究。参与这项研究的研究者没有任何报酬。
数据分析[/B]
数据用WINDOWS系统的SPSS 15.0分析。总共有97名学生参与了研究，82(84.5%)名女性，15(15.5%)名男性。调查对象平均年龄是27岁。其中最小的19岁，最大的53岁。其中61(62.9%)人是护理学生。另外，这些学生中的一些正在学习护理学(n=2; 2.1%)，物理疗法(n=17; 17.5%),职业疗法(n=5; 5.2%),医疗保健(n=9;9.3%)。数据用了因子分析和信度分析。在因子分析中，基于先前研究的说明语句被挑选出来。但是，作为研究的结果，一些属于最初的DREEM（教育环境测量）语句或用来衡量有意义学习的问卷被丢弃。基于因子分析和信度分析结果，求和变量用项目的平均值来计算。在分析中，求和变量依旧被分为五类（1没有期望2一点期望3不多也不少的期望4相当多的期望5很多的期望），是为了更好地理解参与者期望的水平。柯尔莫哥罗夫-斯米尔诺夫检验代替了t检验，被用来决定是否成年人和年轻学生的期望存在差异，主要因为测试变量的分布是偏态分布。个别项目的均值和标准差也被报告出。定性数据被分析出，并用于支持定量分析。
结果[/B]
在虚拟现实和基于仿真学习环境的学习过程中学生的期望
第一个调查问题涉及到在虚拟现实和基于仿真学习环境中学生对教、学及学习过程期望的种类。表格1显示了因子和属于每个因子的均值和标准差。每个因子的克隆巴赫系数（是检视信度的一种方法，由李·克隆巴赫在1951年提出。它克服了部分折半法的缺点，是目前社会科学研究最常使用的信度分析方法。）连同求和变量的均值和标准差都被包含在表格之中，这些都是因子的实证对应物。
结果显示克隆巴赫系数的值都在0.7 (0.861
到0.897)以上，这表明可接受的内部相容性和变量能被用于描述学生期望。有分析结果发现，在虚拟现实和基于仿真学习环境中学生对教学的期望(M=3.65; SD=0.54)相当高，49.5%的调查对象在这些环境中教学有相当高的期望，5.2%的调查对象非常期望。很多时候，学生希望教学对提升他们能力有所帮助(M=4.16; SD=0.83),
会有促进作用(M=3.99; SD=0.92), 学生的需求是教学的首要问题(M=3.86; SD=0.97)。因此，变量被命名为“激励和量身定做的教学”。结果与预期一样，是因为许多早先的研究者已经指出学生们喜欢仿真练习，并在他们遇到真实情况之前给其提供实践锻炼的机会。下面的摘录也证实了这一点：
表格一：每个因子的语句，克隆巴赫系数，平均值和标准差
[tr]
| [td]
|
| 因子
| [/TD]
| [td]
|
| 问卷语句
| [/TD]
| [td]
| 每个因子的克隆巴赫系数
| [/TD]
| [td]
| 求和变量的均值和标准差
| [/TD]
| [/TR]
| [tr]
| [td]
|
|
|
| 激励和量身定做的教学
| [/TD]
| [td]
| 1
| [/TD]
| [td]
| 这次教学将会鼓励我(M=3.66;SD=0.92)
| [/TD]
| [td]
| 0.897
| [/TD]
| [td]
| M=3.65;
| SD=0.54
| [/TD]
| [/TR]
| [tr]
| [td]
| 2
| [/TD]
| [td]
| 这次教学将会很有促进作用(M=3.99; SD=0.92)
| [/TD]
| [/TR]
| [tr]
| [td]
| 3
| [/TD]
| [td]
| 学生的需求是教学的首要重点(M=3.86; SD=0.97)
| [/TD]
| [/TR]
| [tr]
| [td]
| 4
| [/TD]
| [td]
| 这次教学对开发我的能力很有帮助(M=4.16; SD=0.83)
| [/TD]
| [/TR]
| [tr]
| [td]
| 5
| [/TD]
| [td]
| 这次教学对增强我的自信心很有帮助(M=3.56; SD=1.03)
| [/TD]
| [/TR]
| [tr]
| [td]
| 6
| [/TD]
| [td]
| 这次教学考虑到了每个人的个性(M=3.17; SD=1.02)
| [/TD]
| [/TR]
| [tr]
| [td]
| 7
| [/TD]
| [td]
| 这次教学鼓励我成为一个积极的学习者(M=3.67; SD=0.98)
| [/TD]
| [/TR]
| [tr]
| [td]
|
|
|
|
|
| 独立的和基于能力的学习
| [/TD]
| [td]
| 1
| [/TD]
| [td]
| 在课程中，学生们有机会积极地获取、评价和应用信息。(M=3.67;SD=0.98)
| [/TD]
| [td]
| 0.862
| [/TD]
| [td]
| M=3.91;
| SD=0.64
| [/TD]
| [/TR]
| [tr]
| [td]
| 2
| [/TD]
| [td]
| 在基于仿真的学习环境里学习，我有能力运用先前学到的知识(M=4.03; SD=0.86)
| [/TD]
| [/TR]
| [tr]
| [td]
| 3
| [/TD]
| [td]
| 我有机会设定自己的学习目标(M=4.02; SD=0.86)
| [/TD]
| [/TR]
| [tr]
| [td]
| 4
| [/TD]
| [td]
| 在老师的指导下，我有机会实践自己的技能(M=3.76; SD=1.05)
| [/TD]
| [/TR]
| [tr]
| [td]
| 5
| [/TD]
| [td]
| 在学习时，我有机会利用自己先前的经验(M=3.93;SD=0.80)
| [/TD]
| [/TR]
| [tr]
| [td]
| 6
| [/TD]
| [td]
| 在课程中，我有机会熟悉自己并利用未来工作中可能会用到的仪器进行实践(M=4.16; SD=1.13)
| [/TD]
| [/TR]
| [tr]
| [td]
| 7
| [/TD]
| [td]
| 在课程中我能够重复锻炼自己的技能(M=3.66; SD=0.90)
| [/TD]
| [/TR]
| [tr]
| [td]
| 8
| [/TD]
| [td]
| 在基于仿真的学习环境中学习，我感到很安全(M=3.98; SD=0.83)
| [/TD]
| [/TR]
| [tr]
| [td]
| 9
| [/TD]
| [td]
| 在课程中，我有机会精密的评价自己的学习(M=3.92; SD=0.90)
| [/TD]
| | [/TR] |
[tr]
| [td]
|
|
|
|
|
| 可转移的学习成果
| [/TD]
| [td]
| 1
| [/TD]
| [td]
| 在课程中我能很好的应用学到的知识(M=4.23; SD=0.85)
| [/TD]
| [td]
| 0.861
| [/TD]
| [td]
| M=4.09;
| SD=0.73
| [/TD]
| [/TR]
| [tr]
| [td]
| 2
| [/TD]
| [td]
| 在基于仿真学习环境中学到的知识有助于我比以前更加的理解(M=4.23; SD=0.80)
| [/TD]
| [/TR]
| [tr]
| [td]
| 3
| [/TD]
| [td]
| 在课程之后，我相信以后工作中用到的仪器使用起来会比以前更加简单(M=4.13; SD=0.91)
| [/TD]
| [/TR]
| [tr]
| [td]
| 4
| [/TD]
| [td]
| 在课程学习中我的问题解决能力有了提高(M=3.66; SD=1.06)
| [/TD]
| [/TR]
| [tr]
| [td]
| 5
| [/TD]
| [td]
| 在基于仿真的学习环境中学习会增强我的技能(M=4.18;SD=0.91)
| [/TD]
| [/TR]
| [tr]
| [td]
|
|
|
|
|
| 有能力的和准备充分的老师
| [/TD]
| [td]
| 1
| [/TD]
| [td]
| 教师是知识渊博的(M=4.29; SD=0.83)
| [/TD]
| [td]
| 0.878
| [/TD]
| [td]
| M=3.94;
| SD=0.75
| [/TD]
| [/TR]
| [tr]
| [td]
| 2
| [/TD]
| [td]
| 教师能提供适当的和有建设性的评论(M=3.69; SD=0.97)
| [/TD]
| [/TR]
| [tr]
| [td]
| 3
| [/TD]
| [td]
| 教师能很好地与病人沟通(M=3.71; SD=0.94)
| [/TD]
| [/TR]
| [tr]
| [td]
| 4
| [/TD]
| [td]
| 教师能给出清晰的例子(M=4.00;SD=0.85)
| [/TD]
| [/TR]
| [tr]
| [td]
| 5
| [/TD]
| [td]
| 教师为教学做了很好的准备(M=4.01; SD=0.94)
| [/TD]
| [/TR]
| [tr]
| [td]
|
|
|
| 我热切期待能进入一个ENVI（遥感图像处理系统）环境；我们还没有用过ENVI（遥感图像处理系统）。我期待我能试验和练习不同种类的情景和技巧。（学生，NO6）
| 在我们接触真是病患之前能在仿真环境中练习是一件很好的事。我相信如果没有仿真环境中的练习我将会很紧张。（学生，NO40）
|
| 学生在学习中有相当高的期望(M=3.91; SD=0.64)，67%的调查对象有相当高的期望或很高的期望。像求和变量的名字显示的那样，学生特别期望能用到先前学到的知识(M=4.03; SD=0.86)，以及设定自己的学习目标(M=4.02;SD=0.86)。学生们也期望有机会更加了解自己，还有机会用未来工作中需要的仪器来练习(M=4.16;
| SD=1.13),但是，在这个问题上，标准差也很高。这显示一些学生期待能熟悉自己和用仪器练习，但是其他人就这一点而言有很低的期望。这些结果显示，学生们实际上期望自己的研究是建构主义和自我引导的。建构主义学习是指学习者在他们先前的知识之上建立有意义的知识，自我引导学习假定学习者能设定自己的学习目标，然后自己实现他们。
| “可转移的学习成果”被用于描述在这些环境中学习的期望(M=4.09; SD=
| 0.73)。个别项目显示很多时候学生期望学到可应用的东西(M=4.23;
| SD=0.85),在虚拟现实和基于仿真学习环境中学习能帮助他们懂得知识(M=4.23;
| SD=0.80)。另外，学生们期望仪器的使用能够简单(M=4.13; SD=0.91)，他们还希望在课程之后技能能得到很大的提高(M=4.18;
| SD=0.91)。这些期望将会变成现实，先前的研究显示学生从基于仿真的训练中获益。例如，在Moule和他同伴的的研究中，学生们学习技能，但是他们也觉得在基于仿真的环境中训练能提升他们的知识和对主题的理解。总的来说，在这些环境中学习，41.2%的调查者期望相当高，32%期望非常高。
| 学生们对教师的期望也相当高(M=3.94; SD=0.75)，33.0%的学生对教师期望相当高，26.8%的学生期望很高。学生们特别期望他们的教师有能力(M=4.29;
| SD=0.83)，为教学做好准备(M=4.01;
| SD=0.94),以及给出清晰的例子(M=4.00;SD=0.85)。因此，求和变量被命名为“有能力的和准备充分的老师”。Amin以及其他人在测量医学学校大学老师的特征时也发现了相似的结果。学生们最喜欢的特征是知识渊博，友好容易接近，以及能够很好的组织教学资料。
| 这些结果强加给教师很高的需求。教师在基于仿真训练中的角色不同于传统的讲授类教学。调查显示教师需要发展，尤其是关于不同种类的教学方法，和怎样促进任务报告。
| 学生对自己学术自我认知和学术氛围的期望
|
| 第二个调查问题关于不同期望和认知的种类。学生在虚拟现实和基于仿真学习环境中有自己的学术自我认知和学术氛围。表格2显示了因子和属于每个因子的均值和标准差。每个因子的克隆巴赫系数连同求和变量的均值和标准差都被包含在表格之中。
|
|
|
|
|
|
|
|
|
|
| | [tr]
| [td]
|
| 因子
|
|
| [/TD]
| [td]
|
| 问卷语句
|
|
| [/TD]
| [td]
|
| 每个因子的克隆巴赫系数
|
| [/TD]
| [td]
|
| 求和变量的均值和标准差
|
| [/TD]
| [/TR]
| [tr]
| [td]
|
|
|
|
| 自信和有能力的学生（学术自我认知）
|
|
| [/TD]
| [td]
| 1
|
|
| [/TD]
| [td]
| 我有信心通过这个课程(M=3.73;SD=0.84)
|
| [/TD]
| [td]
| 0.835
|
|
|
| [/TD]
| [td]
| M=3.51;
| SD=0.70
|
|
|
| [/TD]
| [/TR]
| [tr]
| [td]
| 2
| [/TD]
| [td]
| 我相信我已准备充分去实践自己的职业(M=3.46; SD=1.01)
| [/TD]
| [/TR]
| [tr]
| [td]
| 3
| [/TD]
| [td]
| 我相信我能应付不同种类的练习(M=3.86; SD=0.85)
| [/TD]
| [/TR]
| [tr]
| [td]
| 4
| [/TD]
| [td]
| 我能记住这个课程中所有我需要的知识(M=3.12; SD=0.92)
| [/TD]
| [/TR]
| [tr]
| [td]
| 5
| [/TD]
| [td]
| 我之前使用的学习策略现在将会继续被使用(M=3.41; SD=0.91)
| [/TD]
| [/TR]
| [tr]
| [td]
|
|
|
|
|
| 轻松舒服的氛围
| [/TD]
| [td]
| 1
| [/TD]
| [td]
| 在课程过程中我感觉很舒服(M=3.76;SD=0.77)
| [/TD]
| [td]
| 0.825
| [/TD]
| [td]
| M=3.77;
| SD=0.64
| [/TD]
| [/TR]
| [tr]
| [td]
| 2
| [/TD]
| [td]
| 在课程中，氛围非常的轻松(M=3.64; SD=0.77)
| [/TD]
| [/TR]
| [tr]
| [td]
| 3
| [/TD]
| [td]
| 心烦意乱的学生将会得到帮助(M=3.70; SD=0.92)
| [/TD]
| [/TR]
| [tr]
| [td]
| 4
| [/TD]
| [td]
| 我相信在课程中氛围将会变得很轻松(M=3.99; SD=0.77)
| [/TD]
| [/TR]
| [tr]
| [td]
| 5
| [/TD]
| [td]
| 学习氛围激励我学习(M=3.66;SD=0.95)
| [/TD]
| | [/TR] |
|
| [/TD]
| | [/TR] |
结果显示学生们关于自己学术自我认知的期望(M=3.51;
SD=0.70)是适中的。像求和变量名字显示的那样，学生们尤其关心他们能应付不同种类的练习(M=3.86;
SD=0.85)，以及会通过这个课程(M=3.73;
SD=0.84).“轻松舒服的氛围”用于描述学生对学习氛围的期望，结果相当高(M=3.77;
SD=0.64).个别项目显示很多时候学生期望学习氛围是轻松的(M=3.99; SD=0.77)，舒适的(M=3.76; SD=0.77)，以及心烦意乱的学生将会得到帮助(M=3.70;
SD=0.92)。尽管有时仿真练习会引起紧张不安，学生们在学习中仍期望氛围是轻松的，这是好好学习的先决条件。在基于仿真的练习中，学生能够在没有嘲笑和羞辱下犯错。尤其在任务报告会话中，学生们能够自由表达自己的观点以及从错误中学习是很重要的。
成年人和年轻学生间期望的差异
第三个研究问题是：是否成年人和年轻学生间期望存在差异？参与者的平均年龄是27岁；最小的19最大的53.因此，在分析之前，参与者以统计学分布和芬兰劳动力市场为基础，被分成两个年龄组。成年学生(>25 岁 n=39; 40.2%);年轻学生(≤25
岁;n=58;
59.8%)。为了确定是否成年人和年轻学生间期望存在统计上的差异，用到了柯尔莫哥罗夫-斯米尔诺夫检验。分析中，求和变量被分成三类以至于评价1和2描述了很少的期望，评价4和5描述了很高的期望。评价3是个中立的评价。成年和年轻学生关于教、研究、学习、教师、自己的学术自我认知和学术氛围的期望的百分比被展示在图表一中：
1激励和量身定做的教学
成年学生
年轻学生
2独立的和基于能力的学习
成年学生
年轻学生
3可转移的学习成果
成年学生
年轻学生
4有能力的和准备充分的老师
成年学生
年轻学生
5自信和有能力的学生（学术自我认知）
成年学生
年轻学生
6轻松舒服的氛围
成年学生
年轻学生
如图表一显示：成年学生似乎比年轻学生有更高的期望。最显著的差异在于教学(K-S test = .0469, p = .000,
p和教师(K-S test =
.0452, p = .000,p。但是，成年学生也对研究(K-S test =.0321, p = .023,
p、学习(K-S test =
.357, p = .008, p、学术自我认知(K-S test = .343, p = .012,
p和氛围(K-S test =
.314, p =
.025,p有较高的期望。这可能是因为年轻学生并不如年长学生有经验。换句话说，他们没有那么多基于经验的期望。因而，他们可能对虚拟现实、基于仿真的环境中训练、和自己作为学习者的期望有不确定性。
就像年轻学生自己解释的：
因为我是为数不多的没有经验的人之一，我希望更多经验丰富的学生不会以此欺人，但是他们理解我的水平并支持我。我相信，在这个群体中，这是可能的。（学生，NO18）
讨论和结论[/B]
调查旨在研究一年级医学学生在虚拟现实和基于仿真学习环境中对教学、研究及学习过程的期望。另外，它还测量了学生关于教师、学术自我认知和学术氛围的期望。为了这些目的，选择了DREEM（教育环境测量）问卷和用于测量有意义学习的问卷；但是，在这次研究中为了鉴定学生们的期望而修正了这些问卷。另外，还给学生们提供了一个用来回答开放式问题的小空间，用在这儿可以有助于定量分析。65个项目被转化为6个分量表。每个分量表的克隆巴赫系数都相当高，描述了一个可接受的内部一致性，以及这些变量能被用于描述学生的期望。男人(n=15; 15.5%)和女人(n=82;
84.5%)代表了教育的不同领域；因此目标群体有相当的一致性。尽管性别分布是不均匀的，它遵循了芬兰医学教育正常的分布。但是，性别的不均匀分布也是调查没有试图确定不同性别间期望的差异的原因。
人们也承认，这项研究是不深刻的。例如，学术自我认知是一个很广泛的调查领域。因而对这个概念理解的深刻度还没有达到调查自己的高度。除问卷之外，访谈也提供了额外的信息，例如，学生们并不是很期望自己学术自我认知的原因。但是，这个研究也提供给了我们关于在虚拟现实和基于仿真学习环境中学习的学生期望，这可以用于开发一个更以使用者为中心的教学模型，以及用于在这些环境中的教育。
作为分析的结果，求和变量表达的学生在虚拟现实和基于仿真学习环境的期望的名字如下所述：
1激励和量身定做的教学
2独立的和基于能力的学习
3可转移的学习成果
4有能力的和准备充分的老师
5自信和有能力的学生（学术自我认知）
6轻松舒服的氛围
总的来说，学生们对涉及到虚拟现实和基于仿真学习环境的活动有很高的期望。在所有
例子中,超过一半的学生认为相当多或大量的学习过程发生在虚拟现实和基于仿真学习环境。而只有少数学生没有期望或期望很少。成年的学习者较年轻学生而言尤其拥有很高的期望。先前关于学生期望的研究也显示学生们在自己的学习环境中有很高的期望。调查结果显示学生们关于学习和教师的期望平均最高，尽管求和变量的均值和标准差的差异很小。学生们尤其期望他们学到的东西是可转移的，以便他们在学习环境中训练后变得更有能力。学生们同样也相当期望他们的教师。有能力的和准备充分的老师对学生而言很重要。结果显示在教育和教育者身上有很高的需求。因此，我们应该考虑将这些期望当做建议，并在组织方法研究和学习时考虑到他们。另外，未满足的期望将会导致不满。学习也是固有的个人的，在学习中学生期望学习为他们量身定做。因而，这个研究建议应该给予学生的个性以特别的关注。
学生的学术自我认知的期望是所有变量中最低的，尽管它依旧是积极的。一种解释可能是,学生们意识到,他们所要去到新学校,他们要在一个新环境的锻炼,这可能会意外的揭示他们的能力水平。因此,与此同时,他们有点担心自己的技能和知识，不过他们对自己能够应付这些锻炼有积极的看法，并对自己的职业准备充分。在另一方面，84.5%的参与者是女性，女性通常有低估自己表现的趋向。这也是学术自我认知的期望是所有变量中最低的原因之一。但是，似乎学生们作为学习者有一些现实的看法，这是一个很好的学习的先决条件。比起妨碍学习的那些太过积极地或消极的观点，这当然是更好的。
然而，在教学和学习过程中强调反射能够增强学生对自己能力水平的意识，也能保护他们的情绪。像Barrows 和 Tamblyn所提出的，学生们要学着识别他们的只是缺口—知道什么和不知道什么。在研究中学生们对学习氛围的期望是中等的。这些期望可能会相当容易达到,因为之前的研究人员表示,学生喜欢在这些环境中学习。
这篇文章是一个更广泛的研究的一部分，其目的是用基于设计的调查方法来开发一个在虚拟现实和基于仿真学习环境中的教学模型，它是基于设计、实施、分析和重新设计的循环周期。第一阶段包括主题上的采访老师,目的在于揭示ENVI（遥感图像处理系统）老师使用的学习概念、学习方法和教学工具。第二阶段是为了找出虚拟现实和基于仿真学习环境中学生期望的种类。第三阶段，目的是为了根据理论和以往的研究结果设计教学模型，以及制定和重新设计模型。在实现阶段，目的也是为了收集关于学生期望的数据，以及关于学生经验的数据。这会使我们能够在这个领域中检测学生的期望有没有被满足。最后，一个有效的教学模型能使教师意识到适合教学的不同选择和方法，也能够对在虚拟现实和基于仿真学习环境中计划、实现和评价有所帮助。
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