Presence Is the Key to Understanding Immersive Learning

Abstract

Presence as the subjective feeling of ‘being there’ is one of the main psychological components in immersive virtual environments. Research shows that presence can have an effect on learning outcomes in educational virtual environments. As presence can be considered as an individual psychological variable, its crucial role in the process of immersive learning is influenced by numerous subjective and objective factors. On the basis of the Educational Framework for Immersive Learning (EFiL), we developed a research model including the factors presence, immersion, cognitive abilities, motivation, and emotion. The hypotheses of the research model have been examined in a study with 23 students testing three different immersive educational virtual environments for learning computer science. The results of 67 presence questionnaires could confirm the hypotheses of the research model deriving from the EFiL partly. The factors immersion, emotion, and cognitive abilities were predictors for presence. An assumed, predictive effect of intrinsic motivation towards learning computer science on presence could not be verified.

Full text

Presence Is the Key to Understanding Immersive
Learning
Andreas Dengel1and Jutta Mägdefrau2
1University of Passau, Innstr. 33, Faculty of Computer Science and Mathematics
andreas.dengel@uni-passau.de
2University of Passau, Innstr. 41, Faculty of Arts and Humanities
jutta.maegdefrau@uni-passau.de
Abstract. Presence as the subjective feeling of ‘being there’ is one of
the main psychological components in immersive virtual environments.
Research shows that presence can have an effect on learning outcomes in
educational virtual environments. As presence can be considered as an in-
dividual psychological variable, its crucial role in the process of immersive
learning is influenced by numerous subjective and objective factors. On
the basis of the Educational Framework for Immersive Learning (EFiL),
we developed a research model including the factors presence, immer-
sion, cognitive abilities, motivation, and emotion. The hypotheses of the
research model have been examined in a study with 23 students testing
three different immersive educational virtual environments for learning
computer science. The results of 67 presence questionnaires could confirm
the hypotheses of the research model deriving from the EFiL partly. The
factors immersion, emotion, and cognitive abilities were predictors for
presence. An assumed, predictive effect of intrinsic motivation towards
learning computer science on presence could not be verified.
Keywords: Immersive Learning, Presence, Educational Virtual Envi-
ronments, Virtual Reality, Immersion
1 Introduction
Immersive Learning in virtual and mixed environments can be considered as
a new approach to learning in an active and engaging way. We can think of
Dewey’s popular approach of learning-by-doing as learning by being there, in an
immersive and engaging environment, perceiving it as an actual reality with the
possibility of interaction, uncertainty, and choice: “We hang on the lips of the
storyteller because of the element of mental suspense. [...] When an individual is
engaged in doing or making something (the activity not being of such a mechan-
ical and habitual character that its outcome is assured), there is an analogous
situation. Something is going to come of what is present to the sense, but just
what is doubtful. The plot is unfolding toward success or failure, but just when
or how is uncertain” [6]. Therefore, the feeling of being present somewhere or of
something being present in combination with engagement is crucial for an active
learning process.

2 Andreas Dengel, Jutta Mägdefrau
2 Presence Is Being There
When speaking about the feeling of ‘being there’, research in virtual and mixed
reality usually refers to the term presence. There are ongoing discussions about
terminology, especially concerning the distinction of terms presence and immer-
sion. According to similar approaches suggested by Biocca [3] and Lee [11], the
feeling of presence contains the subjective elements of physical, social, and self-
presence, referring to different domains of human experience. Presence can be
seen as “a psychological state in which virtual objects are experienced as actual
objects in either sensory or nonsensory ways” [11]. The framework from Witmer
and Singer describes immersion as a psychological state referring to the feeling of
being enveloped by the environment, as well as being included in and interacting
with it [26]. Jennett et al. widen this definition by describing immersion as the
degree of involvement with a game, distinguishing its three levels engagement,
engrossment, and total immersion (including presence) [9]. On the other side,
Slater suggests that immersion should be understood simply as a quantifiable
description of technology from an objective point of view which is independent
of the user’s perception [21].
By following Slater’s definition, it is possible to separate the aspect of human
experience from the technological aspect. Steuer distinguishes the technologi-
cal variables influencing (tele-)presence in vividness and interactivity. Vividness
refers to “the representational richness of a mediated environment as defined
by its formal features” [23] in terms of how the technological setting presents
information of the environment to the senses. This technological variable con-
sists mainly of the characteristics breadth (number of sensory dimensions which
are presented simultaneously) and depth (resolution of the cues within the per-
ceptual channels). Interactivity is “the extent to which users can participate in
modifying the form and content of a mediated environment in real time” [23].
The factors speed of interaction (response time), range of interactivity (num-
ber of attributes which can be manipulated including their possible variations)
and mapping (connection between human actions and actions within the envi-
ronment) contribute to interactivity [23]. We follow these approaches by seeing
presence as the subjective feeling of ‘being there’ in regards to the virtual or
mixed environment in its entirety, including its surroundings (physical presence),
its social actors (social presence), and its representation of the user’s self (self-
presence). Immersion, therefore, refers to an objective description of the used
technology, including the stimulus-driven variables vividness and interactivity.
Immersion is one of the main factors influencing presence. Studies comparing
different immersive settings and their effects on presence show associations be-
tween differences in hard- and software and the feeling of self-reported presence:
Mikropoulos examined differences between the feeling of presence in egocentric
and exocentric perspectives [14]; Bailenson et al. investigated the effect of field of
view on presence in virtual environments [1]; Lee, Wong, and Fung investigated
how Virtual Reality (VR) features like presentational fidelity and immediacy of
control effect presence; they also emphasize the role of motivation for feeling
present in a virtual environment [10].

Presence Is the Key to Understanding Immersive Learning 3
Fig. 1. Objective and Subjective Factors Influencing Presence
Cognitive skills can also be regarded as a determinant for presence: Accord-
ing to Schubert, Friedmann, and Regenbrecht, the construction of a spatial-
functional mental model of a virtual environment induces a sense of presence
[20]. Constructing the representation of one’s own bodily actions as possible ac-
tions in the virtual world while suppressing incompatible sensory input are the
two cognitive processes involved for feeling present in the mediated world [23].
The idea of users willingly suppressing incompatible sensory inputs can be re-
ferred to as a “suspension of disbelief that they are in a world other than where
their real bodies are located” [22]. Such an understanding of cognitive activities
also corresponds with Biocca’s theory of presence being a labile psychological
construct oscillating between physical, imaginal, and virtual environments [3].
As the physiological measurement methods of presence show [15], emotional
variables that are connected to the purpose of the virtual experience, like anxiety
and fear for phobia treatments, also influence the user’s presence. Following this
idea, it can be assumed that positive emotions enhance presence in a pleasant
environment. On the other hand, presence can be regarded as a crucial factor
for triggering emotions in virtual and mixed realities [9, 17].
An adequate model for determining the effect of motivation on presence is
the self-determination theory of Deci and Ryan, distinguishing intrinsic moti-
vation, extrinsic motivation, and amotivation [4]. Yeonhee found that intrinsic
motivation and perceived interactivity as a core component of presence were
moderately correlated (r= .46, p< .01) [27]. Similar effects for other internal
motivational constructs (i.e. identification) are expectable. A negative associa-
tion between the least autonomous constructs of extrinsic motivation (external
regulation/introjection) and presence could be assumed as well.
For examining presence further, we extend Steuer’s model of objective techno-
logical variables influencing (tele-)presence with individual subjective variables
affecting presence. We can assume that the psychological feelings of physical,
social and self-presence are influenced by objective technological variables given

4 Andreas Dengel, Jutta Mägdefrau
through immersive hard- and software as well as interacting with subjective
variables like motivational, emotional, and cognitive factors (Fig. 1). The level
of immersion is determined through stimulus-driven characteristics of the used
immersive material like vividness and interactivity. The model is not extensive
and there certainly are more factors that influence presence and are influenced
by presence, but the named factors have been identified to be crucial variables
in terms of Immersive Learning [5] and are therefore focused on in this paper.
3 Presence influences Immersive Learning Activities
The most interesting effects of presence to investigate in terms of Immersive
Learning include the learning activities and learning outcomes. Mikropoulos
notes that presence, deriving from different immersive settings, is a unique char-
acteristic in educational virtual environments and influences learning outcomes
[14]. Research examining such relations show diverse results. Bailey et al. in-
vestigated the effect of presence on recall performance and found a negative
association between presence and cued recall performance on pro-environmental
principles (r= -.45; p< .05) and no significant correlation between presence
and a corresponding free recall performance [2]. Roy and Schlemminger mea-
sured language learning performance in an educational virtual environment dur-
ing two weeks with three times of measurement. The results show that presence
can enhance learning performance over time (r= .365; p< .05; last point of
measurement) [19]. By comparing different immersive settings (varying fields of
view between 60◦and 180◦), Lin et al. verified a positive effect of presence on
memory structures related to the shapes, colors, relative locations, relative sizes,
and event sequences of virtual environments (r= .48; p< .01) [12]. Lee et al.
conducted a study on how desktop VR enhances and influences learning in the
subject Biology; they found a positive correlation between presence and learn-
ing outcomes (r= .64; p< .001) and between presence and perceived learning
effectiveness (r= .55; p< .001) [10].
On the basis of Helmke’s supply-use-framework for scholastic learning [8],
Dengel and Mägdefrau introduced the Educational Framework for Immersive
Learning (EFiL). According to the EFiL, Immersive Learning can be seen as
“learning activities initiated by a mediated or medially enriched environment
that evokes a sense of presence” [5]. Learning in immersive educational virtual
environments, therefore, does not happen automatically but the supplied learn-
ing materials have to be used actively by the learner. The perception of the
didactical, immersive and content quality of the instructional materials at a cer-
tain level of presence and the interpretation of these materials may initiate learn-
ing activities. The student’s (immersive) learning potential, including cognitive,
emotional, and motivational factors, influences the immersive learning process
interacting with and in the learning environment (context variables like school
form, social composition, and cohesion of the class, etc.). Other factors affecting
the process of Immersive Learning are the family and the teacher of the learner.
Dengel and Mägdefrau note that the factors influencing immersive learning are

Presence Is the Key to Understanding Immersive Learning 5
Fig. 2. The Educational Framework for Immersive Learning by Dengel and
Mägdefrau on the Basis of Helmke’s Supply-Use-Framework
interrelated; many factors influence each other mutually [5]. Presence is seen as
the central factor of perceiving and interpreting the supplied immersive material:
“The immersive content itself does not invoke learning activities directly as it
has to perceived by the learner first. A higher feeling of presence in terms of ac-
tually being in the immersive EVE [Educational Virtual Environment] enhances
the learning activities” [5]. The learner’s feeling of presence can be influenced
through his or her subjective motivational, cognitive, and emotional factors, as
well as through the level of immersion regarding the instructional material.
The EFiL’s cognitive factors “summarize all intraindividual cognitive charac-
teristics and skills that influence learning activities, including intelligence, learn-
ing strategies, and the ability of reflective thinking” [5]. The didactical and me-
thodical design of the immersive learning content can induce the activation of
some of the cognitive factors.
We assume that the emotional factors of the learner contribute as well to
the immersive learning activities as to presence. The EFiL’s understanding of
emotional factors follows the approach of Pekrun et al. distinguishing academic
emotions into positive activating emotions (e.g. enjoyment, hope, pride), positive
deactivating emotions (e.g. relief), negative activating emotions (e.g. anger, anx-
iety, shame), and negative deactivating emotions (e.g. hopelessness, boredom)
[17]. As a situational characteristic, emotional factors could be influenced by the
content quality of the immersive material. As we want to determine the predic-
tors for presence in educational virtual environments rather than determining
the factors influencing learning activities in general, we follow the approach of
distinguishing positive emotions and negative emotions as possible influences for
presence while not differentiating activating and deactivating emotions.
The EFiL includes Deci and Ryan’s concept of amotivation, extrinsic moti-
vation (external regulation, introjection, identification) and intrinsic motivation

6 Andreas Dengel, Jutta Mägdefrau
[4] with their occurrences of global, contextual and situational motivation [25].
Global and contextual motivation (e.g. academic motivation towards learning
in general or in a specific subject) are considered as relatively stable individual
characteristics which can only be changed slowly and partly [25]. In contrast,
the situational motivation of a learner refers to current activity and can be influ-
enced e.g. through the supplied immersive hard- and software or through other
situational characteristics of the learner.
The EFiL gathers numerous studies investigating one or multiple effects of
and between these variables in terms of immersive learning. Presence, as a central
variable which is influenced by factors like immersion, emotion, cognition, and
motivation seems to play a crucial role in immersive learning activities. However,
studies which include multiple objective, situational, and stable psychological
variables are rare. In order to explore the assumptions of the EFiL further, an
examination on what seems to be the central key to understanding Immersive
Learning is needed. Therefore, this paper focuses on extracting the subjective
feeling of presence by investigating its predictors.
4 Research Model
For this study investigating the objective and subjective variables influencing
presence, we use hypotheses deriving from assumptions underlying the EFiL. For
investigating the effect of immersion (IMM) on presence (PRES), different edu-
cational virtual environments have to be compared (effect of different immersive
software on presence) in different immersive technologies for each environment
(effect of different immersive hardware on presence). In order to assess cognitive
abilities, we assume that scholastic performance (SP) can map the overall cogni-
tive skills reasonably. Therefore, the scholastic performances in the core subjects
Math (SP_MA), the students’ native language (German, SP_GER), as well as
in the subject of the learning content of the educational virtual environment
(Computer Science, SP_CS) are assessed. Also, a composite score of the three
subjects is calculated (SP_OVR) to display a simplified overall scholastic per-
formance. In terms of the emotional factors, we assess the academic emotions
suggested by the EFiL: the positive activating emotions (enjoyment, hope, and
pride) and the positive deactivating emotion relief are aggregated to the factor
positive emotions (EMO_PO); the negative activating emotions (shame, anger,
and anxiety) and the negative deactivating emotions (hopelessness and bore-
dom) are aggregated to the factor negative emotions (EMO_NE). Regarding
the motivational factors, we assess the external regulation (MOT_EX), as well
as introjected (MOT_IJ), identified (MOT_ID), and intrinsic (MOT_IN) aca-
demic motivations towards learning computer science. In this study, we focus on
the variables influencing presence. Therefore, the research model does not cover
all relations noted in the EFiL. In particular, we want to focus on physical pres-
ence as this manifestation of presence is relevant to all EVEs (some EVEs might
not include social actors or a representation of the user’s self). The hypotheses
below result in the research model shown in Fig. 3.

Presence Is the Key to Understanding Immersive Learning 7
Fig. 3. Research Model for the Presence Study
1. A higher level of immersion predicts a higher sense of presence.
2. Higher previous scholastic performance predicts a higher sense of presence
(a: German, b: Math, c: Computer Science, d: Composite Scholastic Perfor-
mance).
3. The student’s emotional state predicts his or her sense of presence (a: positive
emotions increase presence, b: negative emotions decrease presence).
4. The student’s motivation towards learning Computer Science predicts his or
her sense of presence (a: intrinsic motivation enhances presence, b: identified
motivation increases presence, c: introjected motivation decreases presence,
d: external regulation decreases presence)
5 Method
5.1 Sample
23 (seven female) eighth grade students from an Austrian school took part in
the experiment. Their Computer Science teacher did not cover the topics of the
virtual environments prior to the study.
5.2 Instruments
As we wanted to focus on the role of physical presence, we used the Slater-
Usoh-Steed (SUS) questionnaire [22]. The questionnaire consists of six questions
assessed on a 7-point Likert scale (α= .88). Three different methods for the
calculation of the presence value have been suggested: the original SUS Count
method [22] counting all items with a value of 6 or higher with a maximum
of 6 points, the adapted method by Peck, Fuchs, and Whitton [16] counting
all items with a value 5 or higher with a maximum of 6 points and the SUS
Mean value [22] with a possible maximum of 7. We assessed external regulation
(six items, α= .81), introjected motivation (four items, α= .52), identified

8 Andreas Dengel, Jutta Mägdefrau
Fig. 4. Educational Virtual Environments for Learning Computer Science (Com-
ponents of a Computer, Asymmetric Encryption, Finite State Machines)
motivation (four items, α= .79), and intrinsic motivation (five items, α= .84)
on a 5-point Likert scale with a questionnaire evaluated by Hanfstingl et al. [7].
While the original survey asked for motivation towards an unspecified subject,
the questionnaire used in the study was adapted so that it asked about the
students’ motivation towards the subject Computer Science. The questionnaire
for assessing the emotions shame, enjoyment, anger, hope, pride, hopelessness,
relief, anxiety, and boredom on a 6-point Likert scale was adapted from a survey
used by Titz [24]. The emotions were categorized into the scales positive emotions
(α= .83) and negative emotions (α= .35).
The educational virtual environments cover contents from computer science
education: Components of a Computer,Asymmetric Encryption, and Finite State
Machines. The environments have been developed with Unity and display a
game-like setting for learning about the subject contents. Information was pre-
sented using texts and images. The Components of a Computer environment
let the user enter a computer and learn about its different parts by repairing
it from the inside. The Asymmetric Encryption environment uses magic po-
tions as a metaphor for public and private key encryption processes. The Finite
State Machines environment uses a treasure hunt game on varying islands as
a metaphor for the states (islands) and the transition functions (boats) of an
automaton. The used immersive settings are a laptop, a mobile VR and an HTC
Vive. Due to their characteristics of interaction and vividness, the HTC Vive was
considered to be the most immersive setting; the laptop setting was considered
to be the least immersive setting.
5.3 Procedure
Three days prior to the study, the students completed the motivation ques-
tionnaire and learning objective examinations for the three learning topics. The
participants used an individual code for these pre-questionnaires which they
would also use again later for the questionnaires in the study. In order to secure
confidentiality, the students’ teacher noted their scholastic performance in the
subjects German, Math, and Computer Science on the pre-questionnaire without
noting down the individual code. For the study itself, the class was randomly

Presence Is the Key to Understanding Immersive Learning 9
divided into three groups (two groups with eight members, one group with seven
members). One student in a group of eight did not finish the study because of mo-
tion sickness after the mobile VR experience for the Components of a Computer
environment. The participants of each group experienced all three software pro-
totypes, but each group was provided a different technological setting for every
program (Tab. 1). Within each group, the participants were handed a sheet with
the task to collect stamps for all the technological settings (one stamp) and the
filling out of the related questionnaires for presence and learning outcome (an-
other stamp). The questionnaires had to be filled out immediately after the VR
experience. The six stamps could be collected for the completion of the laptop
experience, the mobile VR experience, the completion of the HTC Vive experi-
ence and, respectively, the related questionnaires. This resulted in 67 datasets
in total (one for each presence questionnaire). Doing so, it was possible to ran-
domly mix the order of the programs among the students as well as the benefit
that each student could take his or her own time in completing the VR expe-
riences and the questionnaires without being pressured by peers who may have
already finished. After the students were divided into groups and lead to their
rooms, they were asked to fill out the emotion questionnaire. After all students
finished their stamp cards, they took part in a short presentation explaining the
metaphors used in the different games as well as the desired learning objectives.
As this learning outcomes can not be considered as predictors of presence, their
relation to presence was not investigated in this paper.
Table 1
Technological settings for the groups
Groups
Group A Group B Group C
Components of a Computer Mobile VR HTC Vive Laptop
Asymmetric Encryption HTC Vive Laptop Mobile VR
Finite State Machines Laptop Mobile VR HTC Vive
6 Findings
The different methods of measurement showed high correlations among each
other. In order to map the students’ heterogenous manifestions of their feeling
of presence as good as possible, we used the SUS Mean value for the further
analyses (r= .95, p< .01 for counting method ‘5 and above’ with mean value; r
= .88, p< .01 for counting method ‘6 and above’ with mean value). Because of
the small sample of this pilot study, we decided in favor of analyzing the different
factors separately rather than using structural equation modeling.

10 Andreas Dengel, Jutta Mägdefrau
Table 2
ANOVA showing the Variation between Presence Means in the three different
Technologies
N mean sd Sum of Squares df F p
Laptop 23 3.22 1.17
4.759 2 15.27 .01Mobile VR 23 4.54 1.39
HTC Vive 21 5.29 1.20
An ANOVA measuring variation between the students’ presence means in the
three different immersive settings (Tab. 2) showed significant differences between
the settings laptop, mobile VR and HTC Vive [F(2, 64) = 15.27, p< .01, η2
p
= .32]. A higher level of immersion lead to a higher sense of presence.
Table 3
Correlations between Presence and Previous Scholastic Performance
1 2 3 4
1. German –
2. Math .57** –
3. Computer Science .63** .75** –
4. Composite Score .83** .90** .89** –
5. Presence .40** .15 .12 .25
Note. **p<.01
The previous scholastic performance in the subjects German, Math and Com-
puter Science showed significant correlations among the subjects (Tab. 3). The
subject German showed a significant correlation with the presence mean value
(r= .40, p< .01). A better scholastic performance in the subject German,
therefore, lead to a higher sense of presence.
We found a significant correlation between the positive emotions and presence
(r = .26, p< .05). Stronger positive emotions lead to higher presence. A possible
effect of negative emotions on presence could not be examined due to a poor scale
reliability value (see 5.2).
The motivational constructs intrinsic motivation and identified motivation
were strongly correlated (r= .68, p< .01). There were no significant correla-
tions found between the motivational constructs (intrinsic motivation, identified
motivation, external regulation) and presence. The relation between introjected
motivation and presence was not investigated further due to the poor scale reli-
ability value mentioned above.

Presence Is the Key to Understanding Immersive Learning 11
7 Discussion
The study was designed to explore the determinants of presence. The effects of
the level of immersion as well as of the learner’s scholastic performance, emo-
tional state, and motivation towards learning the subject associated with the
learning environments on presence were investigated. By following Slater’s defi-
nition of immersion as a quantifiable description of the used technology, it was
possible to separate the supply-side of the EFiL (a teacher can choose to supply
a certain immersive technology, including hardware and software) from the use-
side of the framework (the learner’s perception of the virtual world at a certain
level of presence, his or her emotions, cognitive abilities, and motivation).
H1 (a higher level of immersion predicts a higher sense of presence) can be
maintained: An ANOVA between the technologies showed significant differences
with the HTC Vive inducing the highest sense of presence and the laptop setting
inducing the lowest sense of presence. These results relate to the characteristics
of immersion postulated by Slater [21]: The mobile VR can be seen as more
immersive than the laptop setting deriving from a higher level of interactivity due
to the head tracking in the mobile VR; the head-mounted-display setting can be
regarded as the most immersive setting (increased speed of the interactivity and
better resolution/vividness in terms of the perceptual depth) compared to the
mobile VR. With regards to this hierarchy of immersive systems, the correlation
analysis shows that a higher level of immersion predicts higher presence.
As for the students’ previous scholastic performance, the performance in the
subject German was found to be predictive for presence. This could be explicated
by the high amount of German texts in the VR environments which may have
made feeling present dependent to a certain level of reading skills, represented
through the grade in the subject German. Another possible explanation is that
a higher interest in reading, especially fictional texts, could possibly lead to an
increased fantasy, accompanied by an increased cognitive ability to create mental
models. With the data collected, it is not possible to explore this idea further.
While we have to decline hypotheses H2b(Math), H2c(Computer Science), and
H2d(Composite Scholastic Performance), and therefore a generalization of H2
(higher previous scholastic performance predicts a higher sense of presence.),
maintaining hypothesis H2a(German), the predictive effect of scholastic per-
formance in the subject German on presence, indicates that cognitive abilities
which are related to the manner of how knowledge is acquired in the learning
environment may influence the feeling of presence. The absence of a connection
between Maths/Computer Science and presence could be related to the design
of the software: The game-based learning environment used metaphors and the
learning objectives were not really apparent to the user.
The positive emotions (combining positive activating emotions and positive
deactivating emotions) were found to be predictive for presence. As neither
the laboratory nor the programs were designed to induce or increase negative
emotions, the absence of significant associations between presence and negative
emotions, activating or deactivating, is not surprising. H3a(positive emotions
increase presence) can be maintained: The student’s sense of presence correlates

12 Andreas Dengel, Jutta Mägdefrau
with his or her emotional state regarding positive emotions. H3 (the student’s
emotional state predicts his or her sense of presence) cannot be generalized as an
investigation of H3b(negative emotions decrease presence) was not appropriate
due to poor scale reliability for the negative emotions. A possible explanation
for this could be that the negative emotions which are addressed by the virtual
environment might not necessarily be the same emotions associated with learn-
ing processes. Further research on what emotions influence presence in neutral
or pleasant virtual environments is needed.
To the surprise of the authors, none of the motivational constructs were
found to be significantly correlated to presence; H4 (the student’s motivation
towards learning Computer Science predicts his or her sense of presence) has to
be declined. This could possibly be explained by a lacking connection between
the motivation towards learning computer science and the students’ engagement
in the software as the programs were designed as games which did not require
any previous knowledge about the topics. Thus, the students possibly did not
connect the contents to the subject, encouraging them to impartially engage with
the environment. As the scale reliability for introjected motivation was low, we
could not test H4b. This may be an indicator that the questionnaire used for the
study was not fully applicable for the subject Computer Science and may have
to be revised for further investigations.
8 Implications for Immersive Learning in Educational
Virtual Environments
This study could contribute as well to presence research as to the research realm
of immersive learning clarifying the role of technological and person-specific vari-
ables for developing a sense of presence in EVEs. Not all assumptions of the EFiL
regarding presence could be verified. For some of the effects found, it is not yet
clear, why and how they influence presence. In order to explore these factors
further, larger studies would be needed. Also, while the EFiL hypothesizes mu-
tual relations between the subjective factors, we focused on predictive effects of
certain subjective and objective variables on presence. Long term studies with
broad use of immersive educational technology would be needed in order to de-
termine whether there are long term effects of presence on cognitive abilities,
emotional states, and motivational attitudes.
Even though Jennett et al. argue that presence is only a small part of a user’s
gaming experience [9], the current study could verify the localization of presence
as a central factor in the process of Immersive Learning: Objective variables like
the level of immersion, given through the design of software components and the
used technology, as well as subjective variables like cognitive abilities and emo-
tional capability, predict presence. As the person-specific variables also influence
learning processes in general, understanding the concept of presence, how pres-
ence is induced and how it influences learning is indispensable for understanding
learning processes involving immersive technology. After consolidating the cru-
cial role of presence in Immersive Learning, further research in terms of learning

Presence Is the Key to Understanding Immersive Learning 13
activities and learning outcomes is needed: While it was possible to resolve some
central questions on the determinants of presence, the results differing from the
theoretical framework raise even more interesting and yet unresolved questions
on the details of how presence interacts with the factors involved in the process
of Immersive Learning. In a next step, a design for a larger study will be devel-
oped to investigate the effects of immersion, presence, cognition, emotion, and
motivation among each other as well as on learning outcomes.
Presence as the subjective feeling of being physically in an environment,
actually interacting with the social actors of this environment, and connecting
one’s self with the avatar representation inside the environment seems to be
crucial for immersive learning. Together with influences from the supply side as
well as from the individual use-side of the learner, presence is connected to many
subjective constructs influencing learning processes in immersive educational
virtual environments; it might be the key to understanding Immersive Learning.
9 Acknowledgements
The SKILL project is part of the “Qualitätsoffensive Lehrerbildung”, a joint
initiative of the Federal Government and the Länder which aims to improve the
quality of teacher training. The programme is funded by the Federal Ministry
of Education and Research. The authors are responsible for the content of this
publication.
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