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A New Framework for Entertainment Computing: From Passive to Active Experience

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In this paper a new framework for entertainment computing is intro- duced and discussed. Based on already existing models and concepts the differ- ent links and relationships between enjoyment, flow, presence, and different forms of experiences are shown and their contributions to the new framework reviewed. To address the more fundamental and theoretical issues regarding en- tertainment, we have to utilize existing theories in information processing, en- joyment and flow theory. Some already possible and probably important con- clusions for the design of new entertainment system are drawn.
Content may be subject to copyright.
F. Kishino et al. (Eds.): ICEC 2005, LNCS 3711, pp. 1
12, 2005.
© IFIP International Federation for Information Processing 2005
A New Framework for Entertainment Computing:
From Passive to Active Experience
Ryohei Nakatsu
1
, Matthias Rauterberg
2
, and Peter Vorderer
3
1
School of Science and Technology, Kwansei Gakuin University,
Kobe-Sanda Campus 2-1, Gakuen, Sanda Hyogo, Japan
nakatsu@ksc.kwansei.ac.jp
http://ist.ksc.kwansei.ac.jp/~nakatsu/
2
Department of Industrial Design, Technical University Eindhoven,
Den Dolech 2, 5612AZ Eindhoven, The Netherlands
g.w.m.rauterberg@tue.nl
http://www.idemployee.id.tue.nl/g.w.m.rauterberg/
3
Annenberg School for Communication, University of Southern California,
3502 Watt Way, Los Angeles, CA 90089-0281, USA
vorderer@usc.edu
http://ascweb.usc.edu/
http://www.ijk.hmt-hannover.de/
Abstract. In this paper a new framework for entertainment computing is intro-
duced and discussed. Based on already existing models and concepts the differ-
ent links and relationships between enjoyment, flow, presence, and different
forms of experiences are shown and their contributions to the new framework
reviewed. To address the more fundamental and theoretical issues regarding en-
tertainment, we have to utilize existing theories in information processing, en-
joyment and flow theory. Some already possible and probably important con-
clusions for the design of new entertainment system are drawn.
Keywords: Adaptivity, active experience, complexity, enjoyment, entertain-
ment, flow, incongruity, information, integrated presence, learning, play.
1 Introduction
The application and research domain of entertainment technology can be separated in
different fields: (1) game, (2) sport, (3) novel and movie, and (4) art (see Altman and
Nakatsu, 1997). With upcoming developments of advanced technology (Nakatsu,
1998), new media applications can be realized (e.g. Nakatsu, Tosa and Ochi, 1998;
Cavazza, 2003). The characteristics of new media are:
New types of experiences (e.g. Ono, Imai and Nakatsu, 2000)
[Inter-]active experiences, compared to passive experiences
Integration of spatial, social, mental and physical presence
Although a variety of theories has been advanced in communication and media
psychology that describe and explain specific experiential states commonly under-
stood as ‘entertainment’ or ‘enjoyment’, it seems to be very challenging to achieve a
2 R. Nakatsu, M. Rauterberg, and P. Vorderer
coherent, integrative view on entertainment. The main reasons for these difficulties
are the huge variety of experiences called ‘entertainment’ (e.g., curiosity, exhilaration,
tenderness, pride, melancholy, sexual arousal, perception of being in control or hold-
ing power) and the procedural dynamics of entertainment, that is, the strong variabil-
ity of cognitive and affective dimensions of entertainment over time within the course
of media use (Vorderer, Klimmt and Ritterfeld, 2004).
Looking back, various types of considerations on play are already published: Groos
(1901/1899), Huizinga (1980/1939), Caillois (1961/1958), Piaget (1969/1947), Csik-
szentmihalyi (1975), Kauke (1992), Scheuerl (1997), and Raessens and Goldstein
(2005). While Groos (1901) argued that children’s play is a preparation for life, this
was later often credited with the idea that children need to run off their surplus en-
ergy. The classification of play by Caillois (1961) is given as follows: (1) Competi-
tion (Greek: Agon): Boxing, Soccer, Chess, etc.; (2) Chance (Latin: Alea): Dice,
Roulette, etc.; (3) Mimicry (Greek: Mimicry): Actor, Theatrical play, etc.; and (4)
Ecstasy (Greek: Ilinx): Swing, Thrill ride, etc. What is missing in Caillois’ classifica-
tion? Ecstatic immersion (Ilinx) is an essential factor in all plays, and Csikszentmiha-
lyi (1975, 1990) has noticed this. Caillios confuses physical presence and mental
presence. Does it really make sense to classify soccer and chess into the same group?
According to the flow concept by Csikszentmihalyi (1990), flow is an essential factor
of play in the following sense: (1) flow is same as immersion based on engagement
(Douglas and Hargadon, 2000), and (2) the strict border between work and play is
eliminated (Rauterberg and Paul, 1990; Rauterberg, 2004a).
1.1 Curiosity, Arousal and Pleasingness
Curiosity is defined as a need, ‘thirst’ or desire for knowledge. The concept of curios-
ity is central to motivation in relation to mental presence. The term can be used as
both a description of a specific behavior as well as a hypothetical construct to explain
the same behavior to achieve mental presence. Berlyne (1960) believes that curiosity
is a motivational prerequisite for exploratory behavior. Exploratory behavior refers to
all activities concerned with gathering information about the environment and/or
changing the environment. This leads to the conflict and question of whether explora-
tory behavior should be defined (1) in terms of the movements that a human performs
while exploring, or (2) in terms of the goal or purpose of the observable behavior. A
clear distinction between these two seems to be not always possible (Fjeld, Lauche,
Bichsel, Voorhorst, Krueger and Rauterberg, 2002).
According to Berlyne (1960) arousal is a function of collative stimulus properties
such as complexity, novelty, incongruity (incompatible, discrepant), and surprising-
ness (unexpected). Environments with medium level of uncertainty (and a positive
hedonic tone) produce the most positive aesthetic judgments. Sufficient empirical
support exists for Berlyne's curvilinear, inverted U-shape relationship that has been
obtained at least for the complexity dimension that determines the arousal level (see
Figure 1; based on former work of Wundt, 1874). Similar relationships have been
obtained for other dimensions: more novel, more surprising, and less incongruous
environments are preferred. Although Berlyne’s research was pioneering, he did not
sufficiently investigate the relationship to individual skills and preferences. This was
addressed by Csikszentmihalyi's research (1975, 1990) about ‘flow’.
A New Framework for Entertainment Computing 3
Fig. 1. The Wundt Curve (1874, left) shows the hedonic function used to calculate interest; the
hedonic function is shown as a solid line, the reward and punishment sigmoidal curves summed
to form the hedonic function are shown dashed. Relationship between cortical arousal level and
pleasingness (right, adapted from Berlyne, 1960, p. 201).
1.2 Conceptual Models of Flow
All flow component segmentation models are based upon Csikszentmihalyi's defini-
tion of flow in terms of skills and challenges (Csikszentmihalyi, 1990, p. 74). How-
ever, the segmentation models attempt to account for all possible combinations (com-
ponents) of high/low skills and challenges. Underlying all of the flow component
segmentation models is the central role of skill and challenge as predictors of flow.
Novak and Hoffman (1997) compare two flow component segmentation models. The
original three component model from Csikszentmihalyi (1990; shown in Figure 2 left)
identifies flow as congruent skills and challenges, both high and low; anxiety is iden-
tified as the combination of high challenges and low skills, and boredom as high skills
and low challenges.
Fig. 2. Three component flow model (left; adapted from Csikszentmihalyi, 1990, p. 74); four
component flow model (right; adapted from Novak and Hoffman, 1997)
4 R. Nakatsu, M. Rauterberg, and P. Vorderer
In the four component model from Novak and Hoffman (1997; shown in Figure 2
right) identifies flow only in the combination of high skills and high challenges. They
separate apathy from flow in the combination of low skills and low challenges. Suffi-
cient empirical support has been found for the reformulated four component model
shown in Figure 2 (right). An extension of this four component model is an extended
eight component model (Massimini and Massimo, 1988; Ellis, Voelkl and Morris,
1994), which also allows for intermediate (moderate) levels of skills and challenges,
and identifies four additional components: arousal, control, relaxation, and worry. As
the arousal-relaxation distinction is collinear with challenge, and the control-worry
distinction is collinear with skill, the eight component model does not provide any
additional information that allows one to predict flow only based upon skill and chal-
lenge, over and above the four component model from Novak and Hoffman (1997).
All these different multi-component models rely on a non-learning human with an
almost fixed level of skills. But humans can and do learn and therefore change their
skills and capabilities based on their actions taken.
We are compelled to learn and to make experiences our whole life. Human infor-
mation processing can not be independent of this life-long learning process. In this
sense, humans are open systems. In his law of requisite variety Ashby (1958) pointed
out, that for a given state of the environment, an open system has to be able to re-
spond adaptively, otherwise the adaptability and the ability of the system to survive is
reduced. A learning system, without input or with constant input, either decays or (in
the best case) remains fixed. Learning and the need for variety implies, that with con-
stant input variety from context the requisite variety of the system tends to be not
satisfied over time. This is a strong argument against 'one best way' solutions in sys-
tem design to achieve a sufficient level of enjoyment (Csikszentmihalyi and
Hunter, 2003).
1.3 Information Processing Framework
Based on the work of Streufert and Streufert (1978), Rauterberg (1995) extended their
concepts into a general information processing framework by including learning of
adaptive systems. Information and information processing are one of the most impor-
tant aspects of dynamic systems. The term 'information', that is used in various con-
texts, might better be replaced with one that incorporates novelty, activity and learn-
ing. Hunt (1963) designated the ‘arousal potential’ of Berlyne (1960) as 'incongruity'.
Rauterberg (1995) shifts the semantic and theoretic problems from incongruity to
complexity. Incongruity is now defined as the difference in complexity between the
learning system (internal complexity of the memory) and the context (external com-
plexity) (see Figure 3).
Humans have a fundamental need for variety: they can't permanently perceive the
same context, they can't do always the same things. The fundamental need for variety
leads to a different interpretation of human behavior that is often classified as ‘ex-
ploratory behavior’ (Berlyne, 1960) or even ‘errors’ (Rauterberg and Felix, 1996).
Variety is the basis to measure complexity. Rauterberg (1993) could demonstrate a
promising approach of measuring behavioral and cognitive complexity in a fully
automated way (see also recently Fromm, 2004). We can distinguish two different
situations: (1) positive incongruity, and (2) negative incongruity (see Figure 3). If the
context complexity of the environment is fixed then the learning process will
A New Framework for Entertainment Computing 5
automatically decrease the amount of incongruity, and at the end will turn positive
incongruity into negative incongruity. If the actual amount of positive incongruity
is below an individual specific threshold then this individual system can either start to
actively increase the context complexity or looking for another context with
sufficient complexity.
Fig. 3. The difference between the complexity of the system’s mental model and the complexity
of the situational context is called incongruity (adapted from Rauterberg 1995, p. 59)
Ulich (1987) differentiates between ‘boredom’ and ‘monotony’. Boredom emerges
from the feeling of not having enough possibilities to be active (fixed context com-
plexity; see Figure 3). Monotony emerges from the feeling of doing always the same
things (‘fixed’ system complexity; see Figure 3). If the context does not provide suffi-
cient action affordances and opportunities (e.g. context complexity), we are con-
demned to boredom; if we are not allowed for sufficient variety and learning, we are
condemned to monotony, and this monotony effect seems to be independent from the
complexity of the system’s knowledge structure (memory). Monotony can exists on
any level of memory complexity and is mainly caused by insufficient learning and/or
action opportunities.
Traditional concepts of information processing are models of homeostasis on a basic
level without learning (e.g., Shannon, 1949). Human activity and the irreversible learn-
ing process are the main driving forces that cause permanently in-homeostasis in the
relationship between a learning system and its context. A suitable model for information
processing for learning systems must be conceptualized on a higher level: a homeostatic
model of 'in-homeostasis'. The concept to information processing from Rauterberg
(1995) includes action and learning and shows an inverted U-shaped function between
positive incongruity and strength of particular behavior to keep the positive incongruity
level optimized (see Figure 4).
First we have to accept that actual amount of incongruity is individual, context and
situation specific; further is this situation specific incongruity permanently drifting
based to learning. To keep the incongruity in an optimal range, the learning system has
to be provided with a context in which the complexity should permanently increasing as
well to provide a sufficient amount of positive incongruity (Csikszentmihalyi and
Hunter, 2003). This contextual adaptation rate should be similar or close to the
6 R. Nakatsu, M. Rauterberg, and P. Vorderer
individual learning rate
1
. If any of these conditions are not given, then each individual
will enter the range of negative emotions and will start actions to re-establish a situation
within the range of positive emotions (see Figure 4). If the incongruity increases
(e.g., too fast increase of context complexity), the human starts actions to increase
confirmation and therefore to decrease external complexity. If the incongruity decreases,
the human would react with exploratory or other actions to increase novelty and
external complexity.
Fig. 4. The coherence between positive incongruity, emotions and strength of observable be-
havior (taken from Rauterberg 1995, p. 66)
Future research will show how this model will be able to provide important design
recommendations for entertainment systems with dynamic and adaptive behavior,
beyond game levels with different complexity (see also Fabricatore, Nussbaum and
Rosas, 2002). The work of Spronk (2005) looks very promising.
1.4 Conceptual Model of Flow
A conceptual model of flow in relation to skill, challenge and presence is described in
detail by Hoffman and Novak (1996) and Novak, Hoffman and Yung (2000). Key fea-
tures of this model are that flow is determined by skills, challenges and presence. Chal-
lenges and presence are prerequisites for flow and exploratory behavior. The latest re-
vised version of Hoffman and Novak's structural model is shown in Figure 5. Novak,
Hoffman and Yung (2000) indicate the construct of exploratory behavior parallel to
flow. Control in Figure 5 refers to Ajzen’s (1988) construct of perceived behavioral
control, and is indicated as an antecedent, rather than a consequence, of flow. Challenge
determines flow directly, and via attention and presence indirectly (see Figure 5). This
model of Novak, Hoffman and Yung (2000) is one of the first concepts in which (1)
individual skill level (including learning), (2) external challenges, and (3) presence is
related to exploratory behavior and flow.
1
This is the central concept and challenge of any kind of didactic (Heiman, 1962).
A New Framework for Entertainment Computing 7
Fig. 5. Structural model of presence and flow in relation to other dimensions (adapted from
Hoffman, Novak and Yung, 2000, p. 34)
In the model of Novak, Hoffman and Yung (2000, p. 34; see Figure 5) the direct
paths to flow from skill, challenge, and presence are positive and statistically signifi-
cant. However, there was no support for the hypothesis that greater focused attention
corresponds directly to greater flow, although focused attention was found to corre-
spond to greater presence and time distortion. Interactive speed exerts a direct positive
influence on flow, but greater speed did not correspond to greater focused attention or
presence and time distortion. Greater importance was positively associated with
greater focused attention, and the longer the usage was, the greater the users’ skill and
control in the virtual environment.
Fig. 6. Enjoyment as the central concept for entertainment experience (adapted from Vorderer,
Klimmt and Ritterfeld, 2004, p. 393)
8 R. Nakatsu, M. Rauterberg, and P. Vorderer
Additionally Vorderer, Klimmt and Ritterfeld (2004) propose an integrated view of
media entertainment that is capable of covering more of the dimensional complexity
and dynamics of entertainment experiences than existing theories can do. Based on a
description of what is meant by complexity and dynamics, the authors outline a con-
ceptual model that is centered around enjoyment as the core of entertainment, and that
addresses prerequisites of enjoyment which have to be met by the individual user and
by the given media product. The theoretical foundation is used to explain why people
display strong preferences for being entertained (motivational perspective; see Vor-
derer and Bryant, 2005) and what kind of consequences entertaining media consump-
tion may have (effects perspective, e.g., facilitation of learning processes; Figure 6).
2 A New Framework for Entertainment Computing
Human activities in the context of entertainment experiences can be related to two
major classes:
Passive Experiences: Reading novels, watching movies; people watch ex-
periences of others, etc.; sometimes called ‘lean back’ entertainment.
Active Experiences: Doing sports, creating art; people are active partici-
pants in the dynamic situation (e.g. Nakatsu, Tosa and Ochi, 1998) ; some-
times called ‘lean forward’ entertainment.
Passive and active experiences are the two poles of the ‘activity’ dimension. Active
experience is mainly correlated with ‘physical’ presence, and passive experience
mainly with ‘mental’ presence. Nakatsu (2004) combines ‘physical’ and ‘mental’
presence into ‘integrated’ presence.
Physical Presence: hear sound, look at image, utter speech, move body, ex-
ercise, etc.
Mental Presence: use language, read a book, listen to music, watch picture
or movie, etc.
Integrated Presence: Karaoke, theatrical play, musical performance, sculp-
ture, professional sport, etc.
Integrated presence is based on a proper combination of a certain amount of physical
activity and mental imaginations. Mind and body come together in a more enjoyable
form of experiences and presence than each separately could achieve. Nakatsu (2004)
proposed a new classification of entertainment applications in which the dimension of
‘passive versus active experience’ is related to the dimension of presence which is
separated into ‘physical’, ‘mental’ and ‘integrated’ forms. In this new framework all
existing and upcoming entertainment applications can be classified and categorized in
a comprehensive new way (see Figure 7).
Virtual environments and new entertainment have added even more challenges to
entertainment theory. Clearly, the amount and state of presence that virtual environ-
ments can elicit is closely connected to new entertainment (Klimmt and Vorderer,
2003). However, since presence itself is a multi-dimensional concept, a very large
number of connections between (dimensions and precursors of) presence and (dimen-
sions / manifestations of) entertainment is conceivable. For example, interactivity,
which is a key element of virtual environments and an important determinant of inte-
A New Framework for Entertainment Computing 9
grated presence, holds fundamental implications for the quality and intensity of new
entertainment, primarily for individuals who can cope with the additional learning
challenges of interactive media (Vorderer, Knobloch and Schramm, 2001).
Fig. 7. Classification framework for entertainment applications (adapted from Nakatsu, 2004)
Klimmt (2003) and Klimmt and Hartmann (2005) has linked interactivity to such
diverse dimensions of enjoyment as effectance, suspense, curiosity, pride, and simu-
lated experience of attractive action roles. Vorderer, Hartmann and Klimmt (2003)
have discussed the implications of interactivity for competitive forms of entertain-
ment. On the other side based on an intensive literature search (Rauterberg, 2004b),
Rauterberg could find that collaborative forms of entertainment have significant posi-
tive effects on human growth and development. Other key characteristics such as sen-
suous richness (Turner, Turner and Caroll, 2005), audio-visual realism (Shirabe and
Baba, 1997), digital narratives (Cavazza, 2003), aesthetics (Overbeeke and Wens-
veen, 2004; Wensveen and Overbeeke, 2004), and intercultural differences (Rauter-
berg, 2004a) have not yet been systematically connected to entertainment theory.
Another important link between presence and new entertainment refers to the as-
sumption that enjoyment only occurs in situations when users perceive themselves as
being in control (Früh and Stiehler, 2003). However, very immersive new entertain-
ment applications could induce very captive and overwhelming feelings of presence,
which in turn might lead to a reduction of perceived control and thus diminish enjoy-
ment. From this perspective, entertainment experiences can only unfold if users
achieve a balance between inner distance to and ‘being captivated’ by a virtual
environment, which preserves a required minimum of perceived control over the
situation (Kiili, 2005). The relationship between ‘overwhelming’ presence, perceived
control and entertainment is thus another key objective of future theoretical and
empirical investigations.
10 R. Nakatsu, M. Rauterberg, and P. Vorderer
3 Conclusions
In this paper we have several theoretical concepts presented and discussed which can
contribute to a new framework for entertainment computing. One major optimization
criteria for the design of future entertainment applications (e.g. interactive movie,
new type of video games, entertainment robots, etc) is enjoyment (Tosa and Nakatsu,
1998; Vorderer, Klimmt and Ritterfeld, 2004). To reach enjoyment integrated pres-
ence has to be combined with active experience. Active experience is mainly based on
sufficient motor behavior involved in user actions: the cognitively and emotionally
enhanced body! If the user is in a flow state, then active experience can lead to inte-
grated presence. One of the remaining questions is how to get the user into the flow?
Let us assume, we have a sufficient interactive environment which involves physical
and mental presence (to achieve integrated presence), how should we link the
challenges from this action space to the actual skill level of the user? One possible
and promising answer is a sufficient adaptive system behavior to the user’s
learning progress. Enabling the user to keep his or her optimal incongruity (= proper
match of challenges to skills), is probably the best design to reach enjoyable
integrated presence.
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Worldwide the pros and cons of games and social behaviour are discussed. In Western countries the discussion is focussing on violent game and media content; in Japan on intensive game usage and the impact on the intellectual development of children. A lot is already discussed on the harmful and negative effects of entertainment technology on human behaviour, therefore we decided to focus primarily on the positive effects. Based on an online document search we could find and select 393 online available publications according the following categories: meta review (N=34), meta analysis (N=13), literature review (N=38), literature survey (N=36), empirical study (N=91), survey study (N=44), design study (N=91), any other document (N=46). In this paper a first preliminary overview over positive effects of entertainment technology on human behaviour is presented and discussed. The drawn recommendations can support developers and designers in entertainment industry.