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Experiential Learning of Unifying Principles of Science through Physical Activities

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Abstract

Do cosmologists, cell biologists and sociologists understand each other when they explain the basic principles of their respective fields? Over the last three decades, considerable progress has been made in explaining different levels of organized matter through universal dynamical concepts. This has led to the growth of a common language domain in science. Two important consequences of this new scientific framework are a better mutual understanding between disciplines and the development of synthetic knowledge. Physical activities are a rich source of phenomena that are underpinned by universal dynamical concepts, and as such they can provide a perceptually grounded, i.e. experiential, basis on which to learn these concepts. This chapter has three main aims. First, to examine the changes occurring within the linguistic (i.e., conceptual) landscape profile of scientific fields in relation to the presence or absence of general explanatory principles derived from nonlinear dynamical systems theory and statistical physics; Second, to discuss recent empirical results that capture the growth of the domain from the context-dependent languages of separate disciplines towards unified general concepts forming an embedded explanatory framework which allows the creation of synthetic knowledge; Third, to show how the perceptual (proprioceptive, visual and introspective) experience of sports-related activities can enhance the comprehension of these unifying explanatory principles and promote the acquisition of synthetic knowledge.
Chapter 3
EXPERIENTIAL LEARNING OF THE UNIFYING
PRINCIPLES OF SCIENCE THROUGH PHYSICAL
ACTIVITIES
Robert Hristovski, Natàlia Balagué, Pablo Vázquez
Ss. Cyril and Methodius University, Skopje, Macedonia
INEFC University of Barcelona, Spain
ABSTRACT
Do cosmologists, cell biologists and sociologists understand each other when they
explain the basic principles of their respective fields? Over the last three decades,
considerable progress has been made in explaining different levels of organized matter
through universal dynamical concepts. This has led to the growth of a common language
domain in science. Two important consequences of this new scientific framework are a better
mutual understanding between disciplines and the development of synthetic knowledge.
Physical activities are a rich source of phenomena that are underpinned by universal
dynamical concepts, and as such they can provide a perceptually grounded, i.e. experiential,
basis on which to learn these concepts.
This chapter has three main aims. First, to examine the changes occurring within the
linguistic (i.e., conceptual) landscape profile of scientific fields in relation to the presence or
absence of general explanatory principles derived from nonlinear dynamical systems theory
and statistical physics; Second, to discuss recent empirical results that capture the growth of
the domain from the context-dependent languages of separate disciplines towards unified
general concepts forming an embedded explanatory framework which allows the creation of
synthetic knowledge; Third, to show how the perceptual (proprioceptive, visual and
introspective) experience of sports-related activities can enhance the comprehension of these
unifying explanatory principles and promote the acquisition of synthetic knowledge.
Keywords: science, science education, experiential learning, unifying principles, synthetic
knowledge, dynamical systems, sport-related activities
Hristovski, R., Balagué, N., & Vázquez, P.
2
INTRODUCTION
Science is a system, a language system arising from conceptual interactions from
which explanatory patterns emerge. The past two decades have witnessed a large-scale
diffusion of explanatory concepts coming from dynamical systems theory (DS) and statistical
physics (SP) (from now on, the DSSP explanatory complex), into the fields of exercise and
sports science. Sound theoretical and experimental work has corroborated the early ideas that
phenomena of exercise and sports are amenable to the explanatory framework of the DSSP
complex [1]. The nuclei of this growing trend can be traced back to the research into basic
human movement carried out in previous decades. In the late 1970s and early 1980s, novel
explanatory patterns regarding the nature of biological movement emerged which were
underpinned by DSSP ideas [2, 3, 4, 5]. The spread of explanatory concepts from the DSSP
complex into exercise and sports science is just the tip of the iceberg of a much more
widespread process in science which has gone on for centuries, driven by the tacit rationale of
the search for minimum principles able to explain a maximum number of phenomena [6, 7].
Science is also a cooperative social endeavor and a social exchange conducted via
language. Science communities explore and strive to explain the immense diversity of
processes at different levels and time scales of substance organization. The explanations
acquired are continuously shared within and between scientific communities through
language which enhances the diffusion process described above, and sports science is no
exception to this rule. On the other hand, the diversity of phenomena constrains the scientific
language of each discipline to form a specific vocabulary for naming and explaining natural
properties and processes as well as communicating knowledge among scientists. For example,
do a cosmologist, a cell biologist, a sports scientist and a sociologist understand each other
when they explain the basic processes within their fields? Not entirely, one might suppose.
Cosmologists speak about inflationary and electroweak epoch and space-time metrics, cell
biologists about cell membranes, enzymes and ribosomes, sports scientists about fatigue-
induced task disengagement, motor balance and attention focus, and sociologists about group
formation, cohesion and social attitudes.
Recently, the diversity of phenomena and properties of substance organization was
ascribed to the existence of “mesoscopic protectorates” [8], i.e., emergent levels of substance
organization whose key properties cannot be formally, i.e., mathematically, deduced from the
laws that govern the behavior of the more microscopic components (for a detailed explanation
of this issue in physics, see [9]). Therefore, each level is endowed with specific and novel
structures and properties which need a specific language to explain them. These languages,
thus, use context-dependent concepts to name and explain the processes under scrutiny.
Context dependence is viewed essentially as a major cause of the fragmentation between the
vocabularies of different scientific disciplines. That is, while within specific scientific fields
and subfields the communication of knowledge is made possible by a common vocabulary,
the more distant disciplines are, the more difficult communication becomes. As this language
fragmentation is also translated into science education, this inevitably leads to the formation
of a fragmented worldview in learners and limits the possibilities of a learning transfer
between different scientific subjects. However, the tension arising from the coexistence of
Experiential Learning of Unifying Principles of Science through Physical Activities
3
context-dependent vocabulary and unifying tendencies in science can be seen as an
opportunity rather than a problem: resolving it may result in explanatory patterns that are
characterized by both a coherent explanatory skeleton coming from unifying tendencies and
flexibility due to its context-dependent vocabulary [10]. The DSSP complex increasingly
shows the potential of assimilating the context-dependent vocabularies of different scientific
fields into its unifying corpus, manifesting the strength of the approach which can be
harnessed as a powerful educational tool.
2. The growing coherence of explanatory patterns in science but not in science
education textbooks
Recently, a preliminary research study examined the differences within the linguistic,
i.e., conceptual, profile of contemporary scientific fields and science education textbooks [10,
11]. Specifically, the research aimed to examine possible hallmarks of enhanced conceptual
coherence within the scientific language used in these areas, as represented by dimension
reduction and information compression [12] emphasizing the position of sports sciences
within it.
In the study, characteristic concepts of 10 widely separate scientific fields (according
to the classical paradigm) were treated as linguistic degrees of freedom. Scientific fields were:
elementary particle physics (EP), cosmology (CL), molecular physics (MP), chemical
reactions (CR), cell biology (CB), neurobiology (NB), psychological processes (PP), motor
behavior (MB), collective sports research (CS) and sociology of groups (SG). In the first
phase, 35 generic explanatory and empirical concepts taken from contemporary university
and high school textbooks were used for each scientific discipline. The concepts which
defined the chapters, headings and subheadings were extracted first and then the rest of the
most frequent generic concepts from different parts of the textbooks. The experimental
apparatus, data extraction concepts and purely mathematico-technical terms were not taken
into account. The following general explanatory concepts from the DSSP conceptual complex
were used: self-organization (self-assembly or soft-assembly), collective modes (order
parameter, collective coordinate or variable, reaction coordinate), control parameter or
variable, phase transition, bifurcation, symmetry-symmetry breaking, stability, instability
(loss of stability), metastability, criticality (critical point or manifold), gradients, scalar field,
vector field, attractor, repeller, entropy-information, and network.
The second phase of the data collection consisted of an Internet search for scientific
papers published in the fields mentioned above and archived in relevant databases, such as
Scopus (Science Direct), Web of Science, Google Scholar, ArXiv. The sample papers from
each of these fields were taken from pertinent impact factor journals. In total, 1276 papers
were collected over a period of one year (May 2011 April 2012). Since the research focused
on the qualitative aspects of diffusion of concepts within scientific fields (not the quantitative
ones, i.e., the degree of diffusion), a co-word analysis was performed: that is, we searched for
combined expressions consisting of previously extracted scientific concepts and concepts
from DSSP in each scientific discipline. Each paper was analyzed separately to minimize the
possibility of spurious conceptual links. Only papers in which a genuine link between DSSP
and fundamental processes researched in scientific fields was found were taken into further
consideration. Under this procedure the loss was negligible. In each of the scientific fields
analyzed more than 100 papers using DSSP explanatory principles of fundamental processes
Hristovski, R., Balagué, N., & Vázquez, P.
4
were found with the notable exception of collective sports research, in which fewer than 50
papers were found.
Each conceptual space of scientific fields was represented by a binary vector of
length n = 367 (10 scientific fields x 35 generic concepts + 17 DSSP concepts). A value of 1
was assigned to concepts that were found to exist in the scientific discipline and a value of 0
otherwise. Salton’s cosine similarities were first calculated for each pair of the 10 scientific
discipline binary vectors and for each of the two conditions separately (science education
textbooks vs scientific research papers). Dimension reduction of the initial cosine similarity
matrix under both conditions was conducted using tree clustering (single linkage) analysis
and hierarchical principal component analysis (HPCA). Distances d between scientific fields
were calculated as d = 1 - q; where q is Salton’s cosine similarity (the overlap order
parameter) between the vectors which defined the conceptual spaces of scientific fields. The
population entropy of each principal component (PC) was calculated as Ii = ln λi + 0.5 ln π +
0.5, where λi represents its eigenvalue.
The results of the tree clustering analysis revealed significant differences between the
conceptual content of the science education textbooks on the one hand and of contemporary
science research papers on the other. The left-hand panel in Figure 1 shows that the absence
of general explanatory concepts typical of secondary school and university textbooks
generates a growing fragmentation of scientific fields (looking from right to left). On the
other hand, the conceptual fragmentation has stabilized under the presence of general
explanatory concepts typical of current scientific research.
Figure1. Left-hand panel: A hierarchical structure showing conceptual fragmentation of scientific
fields in the absence of the general explanatory concepts typical of science education textbooks. Right-hand
panel: Reduced conceptual fragmentation between scientific fields as a consequence of the diffusion of
unifying explanatory concepts typical of current scientific research. EP - physics of elementary particles; CL
- cosmology; MP - molecular physics; CR - chemical reactions; CB - cell biology; NB - neurobiology; MB -
motor behavior; PP - psychological processes; CS - collective sports research; SG - sociology of groups. The
distance is calculated as d = 1 - q, where q is the cosine similarity between scientific areas.
Notice also that the change in the distance in physical sciences (EP, CL and MP)
between the right-hand and the left-hand panel is negligible. This is because most of the
general explanatory concepts are already present within the realm of these scientific fields in
high school and especially in university textbooks, and they also spread into the contemporary
scientific research literature in these fields. This is not so for the other scientific fields, in
Experiential Learning of Unifying Principles of Science through Physical Activities
5
which the conceptual dimensions of textbooks and contemporary scientific research differ
markedly.
For science education textbook data, HPCA led to a compression of the original 10
vectors to four PCs with eigenvalues λ1 = 3.8; λ2 = 2.46; λ3 = 1.4; and λ4 = 1.02 explaining
86% of the total variance. The entropy for this set of PCs was I = 6.88 nats. The correlation
matrix of the principal components given in Table 1 (upper row, left panel) showed the
fragmentation of scientific fields existing with respect to the conceptual similarity. Only PC1
and PC2 showed medium to low associations with PC3. The first principal component
comprised the scientific fields: physics of elementary particles (EP), cosmology (CL) and
molecular physics (MP) among the physical sciences. The second one comprised
neurobiology (NB), motor behavior (MB), collective sports (CS) and psychological processes
(PP) forming the area of psychobiology. The third principal component was saturated by
chemical reactions (CR) and cell biology (CB), but the principal component of this important
projection also contained neurobiology (NB). This group was predominantly saturated by the
scientific area of biochemistry, with neurobiology acting as a bridge between this area and
psychobiology. The fourth principal component comprised psychological processes (PP) and
sociology of groups (SG), forming the area of social psychology.
Table 1. Left-hand panels: Correlations between primary principal components (PCs). Right-hand
panels: PC structure by scientific fields and their projections on the secondary principal component PCII.
Upper row: science education textbooks. Lower row: Contemporary science research papers. EP - physics of
Hristovski, R., Balagué, N., & Vázquez, P.
6
elementary particles; CL - cosmology; MP - molecular physics; CR - chemical reactions; CB - cell biology;
NB - neurobiology; MB - motor behavior; PP - psychological processes; CS - collective sports research; SG -
sociology of groups.
Vectors that define scientific language areas showed heterogeneous projection values
on the secondary principal component PCII. While physical sciences and biochemistry
components projected relatively homogeneously onto it with medium values, scientific fields
forming the psychobiology and social psychology areas showed a significant decline. This is
consistent with the tree cluster analysis results discussed above. We conclude that in science
education textbooks, because of the absence of binding concepts and principles, explanatory
language becomes increasingly fragmented in the areas that study the higher forms of
organization of matter (MB-SG).
The HPCA of the contemporary scientific research papers in the principal
components given in Table 1 (lower row) showed a different picture. The dimension
reduction led to compression of the original 10 vectors to three PCs with eigenvalues λ1 =
5.76; λ2 = 1.62; and λ3 = 1.04; explaining 85% of the total variance. The entropy calculated
was I = 5.48 nats. This significant reduction of dimensionality and information suppression of
I = 1.4 nats or approximately 2 bits, compared with science education textbooks was a
consequence of language similarities not only between neighboring scientific fields, but also
because widely disparate sciences share common explanatory concepts from the DSSP
complex. The primary PCs were moderately correlated and resulted in one secondary PCII
which was also moderately saturated in equal measure by all the scientific disciplines. The
first principal component contained the following scientific fields: physics of elementary
particles (EP), cosmology (CL), molecular physics (MP), chemical reactions (CR) and cell
biology (CB) under natural sciences. The major projections on the second primary PC showed
cell biology (CB), neurobiology (NB) and motor behavior (MB) under life sciences. The third
primary principal component was saturated by motor behavior (MB), psychological processes
(PP), collective sports research (CS) and sociology of groups (SG) under the social
psychology clade. Cell biology (CB), motor behavior (MB), and psychological processes (PP)
acted as bridges between the three main components. It is important to notice that, due to the
medium-size correlations between primary PCs and the homogenous structure of the
projections of scientific fields on PCII, the flow of information within the conceptual space is
not restricted to the most closely related science fields, but may be much more diverse and
may be shared among vastly disparate areas such as EP, and PP and SG. This point to the
possibility of circumventing, albeit not eliminating, the emergentism-reductionism duality
an interesting topic in its own right, which will be discussed elsewhere.
Generally speaking, there is a clear difference between the conceptual spaces of
science education textbooks and contemporary scientific research papers. The latter have
larger conceptual coherence as a consequence of the use of unifying explanatory concepts
from the DSSP. Only three primary PCs were extracted in the analysis of the conceptual
space of contemporary scientific papers, compared with four in the case of science education
textbooks. This clearly shows the existence of a greater dimension reduction in the scientific
research papers, as well as information compression as revealed by the difference of
population entropies. Though separate scientific fields maintain their context-dependent
language (inter-scientific conceptual distances d do not go to zero see Fig. 1), the unifying
DSSP concepts form an embedded explanatory framework within which stabilizing synthetic
Experiential Learning of Unifying Principles of Science through Physical Activities
7
knowledge becomes a feasible perspective. Unifying explanatory concepts play the role of a
correspondence principle which forms a stable link between the models of organized matter at
different levels and time scales. In a sense, the recurent explanatory patterns if viewed
ontologically, point to an existence of a structure which metaphorically may be called
holographic. The change of the space-time scale resolution keeps some principles unchanged.
Interestingly, the scientific fields cell biology, motor behavior and psychological processes
act as bridges between wider science areas. This finding may have major science education
repercussions; some preliminary consequences and ideas will be discussed in the next section.
3. Towards an experientially-grounded learning of DSSP concepts
Though it has been suggested, and experimentally corroborated, that concepts from
the DSSP complex may have a major explanatory role in exercise and sports science, the
possibility that these sciences may provide an educational underpinning to the learning of
science through the DSSP conceptual system has not been proposed to date. In relation to
this, it was the mathematician Henry Poincaré [13, 14] who noticed the fundamental fact that
the concept of space in humans is built upon our basic capabilities to move. In his own words:
“To localize an object simply means to represent to oneself the movements that would be
necessary to reach it. I will explain myself. It is not a question of representing the movements
themselves in space, but solely of representing to oneself the muscular sensations which
accompany these movements and which do not presuppose the preexistence of the notion of
space”, and further on “I have shown in ‘Science and Hypothesis’ the preponderant role
played by the movements of our body in the genesis of the notion of space. For a being
completely immovable there would be neither space nor geometry.” [13, p. 47-48].
Psychology went on a long voyage through the phases of Piagetian developmental
stage theory [15] and classical cognitive science with it’s amodal symbol systems [16] before
returning to Poincaré’s ideas on the perceptual action-groundedness of abstract mathematical
constructs, this time in the form of the embodied and grounded cognition approach [17, 18].
The difference between these approaches is not of major importance here. Grounded
cognition is clear on the importance of perception-action and introspection in the acquisition
and further use of abstract concepts. In learning and education sciences, this approach has
gained momentum in the past twenty years in a form in which the perceptual groundedness of
the learning of science concepts has been realized through contemporary methods such as:
computer simulations and animations [19, 20, 21]. On the other hand, the power of the DSSP
conceptual complex for learning transfer between disparate science fields is becoming clear
from the results and discussion under the previous subheading [10]. In particular, we saw that
the conceptual space of psychological processes and motor behavior research already contains
explanatory patterns from the DSST complex which bridge the explanatory gap between
classically disparate scientific areas. Psychological processes and motor behavior are also
perfectly suited in the sense that they are directly accessible to learners and observers in a
form of introspection and/or perceptions of overt motor actions. Hence, the link between the
educational consequences of grounded cognition and the unifying role of the DSSP language
offers a unique opportunity to combine physical activities and general explanatory principles
into a specific integrated framework of experiential learning [22]. In the following section we
give a fuller example of how this integration can be applied and then briefly discuss a few
more examples and their links with more distant science fields.
Hristovski, R., Balagué, N., & Vázquez, P.
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4. Experientally-grounded learning of DSSP concepts through physical activities
Kolb’s system of experiential learning contains four phases linked in a circle. Inside
the brackets, we expand briefly on the meaning of these phases for the examples that follow.
1. concrete experience (a physical activity: perception-action and/or introspection)
2. reflective observation on the experience (paying attention to key perceived
phenomena and their phases)
3. abstract conceptualization based upon the reflective observation (conceptualization,
estimation and/or plotting of relations)
4. experimenting with the new concepts (context-specific and context-free (i.e.,
unifying) concepts, applying to other science fields).
4.1. Learning the concepts. Metastability, criticality (instability), search for
stability and qualitative change.
Balance task.
Teacher’s introduction: Keeping balance in the upright position is a basic motor
skill in humans. It needs a coordinated cooperation of the neuro-muscular system at many
levels to negotiate the major environmental constraint gravity. Gravity tends to collapse the
body, i.e., its center of mass, to the minimum gravitational potential energy. When lying on
our back or belly the center of mass reaches its gravitational potential minimum. For the
human body this state is the global energy minimum (i.e., the ground state) which is reflected,
for example, in the minimum metabolic rate under these constraints. All other positions and
activities are excited and are therefore metastable states that need active control in order to be
stabilized. The degree of stability can be tested by applying external perturbations to the body
and observing how it behaves. Rapid recovery of its previous state signifies stability, slow
recovery signifies approaching instability, and no recovery at all signifies instability, i.e., loss
of stability.
Concrete experience: The learner stands with the feet parallel facing a target within
reach/just out of reach. S/he is instructed to pay attention to a specific set of bodily sensations
that will occur under different conditions. The distance from the target is divided into 10
equidistant intervals. The scaled target distance D is calculated as a ratio between the physical
distance of the learner from the target to his/her arm length measured from the shoulder to the
finger tips. The physical distance is measured from the tips of the toes to the vertical
projection of the front part of the target on the floor. Starting from the closest scaled distance,
the learner tries to reach and touch the target. Also, at each scaled distance, a partner applies a
relatively constant mechanical perturbation to the learner’s trunk in the direction of the target.
As the scaled distance increases, typically close to D = 1.4, the learner loses balance and takes
a step forward, i.e. transits to a more stable diagonal stance [23].
Reflective observation on the experience: The learner is asked to provide a number
of self-reports on the sensations of stability perceived at different scaled distances D,
Experiential Learning of Unifying Principles of Science through Physical Activities
9
especially with respect to the perturbations applied by the partner and the behavioral
variability of the lower limbs and the center of mass.
Abstract conceptualization based upon the reflective observation. This phase
may involve the following set of tasks:
Conceptualizing the scaled distance as a control parameter and the center of mass as
a collective variable, and plotting the stability profile of the center of mass vs the
scaled distance D.
Emphasizing the discussion of the qualitative structural change occurring at the
instability (i.e., critical) point at D =1.4, i.e., the abrupt transition of the center of
mass to a new value and the transition from the parallel to the newly adopted
diagonal stance (the concept of a phase transition or bifurcation).
Plotting of the stability change experienced due to the partner’s perturbations as a
function of the scaled distance D from the target.
Plotting of the perceived variability of the center of mass and the lower limbs at
scaled distances far from, and at, the point of instability when not perturbed by the
partner (critical enhancement of fluctuations). Discussing the increase in the
perturbations to form the new stable state of the diagonal stance.
Comparing the degree of stability of the parallel stance to the diagonal stance and to
the lying position.
Plotting of these stability profiles on an energy landscape plot.
Notice that the concept of stability may be studied in a perceptually grounded fashion
with inanimate mechanical bodies as well, with learners acting and observing the effects
produced on the body. However, important phenomena like the enhancement of fluctuations
close to the critical point will not be obtained in this case. In more formal learning settings,
the whole procedure may be videotaped and essential variables may be estimated, such as the
center of mass displacement and the leg displacement, and then put to further use.
Experimenting with the new concepts. This learning phase is the one in which the
unifying power of the DSSP concepts should be used. After reviewing the final conceptual
and explanatory outcome of the analysis in the previous phase, the teacher may connect
concepts and explanations used in the balance task with concepts from other science fields.
For example, according to the teacher’s preferences and background, the energy landscape
plotted to demonstrate the experienced stability profile of the body during the balance task
may be compared to a similar landscape from transition state theory in chemical kinetics [24]
or to the Jeans instability of star formation in astrophysics [25]. Alternatively, teachers may
compare it to the potential energy landscape of the inflationary scenario of cosmology or to
the phase transitions in condensed matter and elementary particle physics [26, 27]. At this
level, distinguishing between context-dependent and context-free (i.e., unifying) concepts and
explanations is clearly one of the aims. For example, a context-dependent concept like the
center of mass may be associated with the reaction coordinate in chemical reactions or with
the gas density in the star formation scenario, all playing the role of a unifying concept of
collective variable. The increase in fluctuation (or in the initial perturbation) as a unifying
concept may be associated with the following context-dependent concepts: in the balance task
it may be associated with the formation of a new (diagonal) stance, in chemical reactions with
Hristovski, R., Balagué, N., & Vázquez, P.
10
the activation and formation of new chemical bonds, and in the star formation process with
the increase in gas density or with the exponential stretching of primordial fluctuations and
the seeds of galaxy formation. The context-dependent concept of stable parallel or diagonal
stance in the balance task may be associated with the general concept of stability and
contextualized again in examples of stability in neurosciences and psychology [28, 29] or
stable collective attitudes and frozen conflicts in social groups [30]. In the balance task, the
teacher may pay attention to the fact that forces generated within the body (the neuro-
musculo-skeletal system) are basically of electromagnetic type and emphasize that what
learners witness is the competition between the only two long-range (macroscopic) forces in
the universe: the biologically highly organized electromagnetic force, and gravity. This may
be linked to the competition between these two forces (or their derivatives) in creating
stability or instability in stars.
We have shown how a simple balance task can be a fruitful source of experiential
learning of a plethora of unifying explanatory concepts from the DSSP conceptual space and
how they can be linked them with phenomena relevant to traditionally distant science fields.
Similar physical activity tasks may enrich the set of examples and start the new cycle of the
four learning phases mentioned above. The task disengagement induced by fatigue [31], the
instability of the focus of attention and the spontaneous switch to task-related thoughts close
to fatigue-induced exhaustion [32] are only a few examples. Phenomena from collective
sports may also prove fruitful for the experiential grounding of general concepts such as
networks, interactions and self-interactions, symmetry and asymmetry, and metastability.
5. Conclusion
The application of systems science and its perspectives from the viewpoint of science
education were analyzed and discussed. In its current form, the science education material
belonging dominantly to fields other than physico-chemical sciences increases the
fragmentation of scientific language. This is not the case in the domain of science research,
which is characterized by increasing degrees of language coherence. This tension between
science education and science research may be bridged by introducing the contemporary
explanatory patterns already existing in the science research area. These explanatory patterns
belong predominantly to the DSSP conceptual space. The experiential learning modules based
on the formation of perceptually-grounded concepts by use of physical activities represent a
viable way of introducing the DSSP explanatory patterns and creating a more integrated
system of science education. The benefits we envision are particularly relevant to the
enhancement of learning transfer and the synthetic world view formation in learners.
Additionally, concepts grounded in physical activities may underpin and reinforce intuitive
aspects. Based in part on previous research on this topic, the best way to link different science
fields for educational purposes seems to be to design separate subject and teacher profiles
specialized in creating learning environments with the main aim of integrating the
explanatory patterns of science using the DSSP explanatory language.
Acknowledgments
With the support of the Institut Nacional d’Educació Física de Catalunya (INEFC) de la
Generalitat de Catalunya. A part of the research was financed by the University of “Ss. Cyril and
Methodius” program for research projects, No. 02-663/28 from 14.09.2012
Experiential Learning of Unifying Principles of Science through Physical Activities
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Experiential Learning of Unifying Principles of Science through Physical Activities
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... They are also task specific because they are formed to satisfy certain scientific task goal constraints. Hence, explanatory patterns can be conceptualized as emergent task specific (functional and thus meaningful) dynamic coordinative language patterns at a social level, akin to their conceptualization at an individual level of the learner subject to a guided discovery learning process (Hristovski et al. 2014). ...
... A preliminary study was recently conducted to form a clearer picture of the ongoing self-organizing process within scientific explanatory patterns and their properties, including the degree of mutual coherence and flexibility (Hristovski 2013;Hristovski et al. 2014). The conceptual content of explanatory patterns in high school and higher education textbooks and contemporary scientific modeling papers were compared in 10 traditionally disparate science fields. ...
... The primary principal components (PC) were weakly correlated and resulted in one secondary PC, which was saturated mostly by natural science concepts, while other scientific disciplines shared less information with this component, which had low projections. More information on the interesting structure of the PCs is given in Hristovski et al. (2014). ...
Chapter
We conceptualize science as a social cognitive embodied-extended system with a perpetual action-perception-explanatory pattern formin cycle. This cognitive cycle encompasses the natural environment. The cycle is irreducible to inner cognitive processes of scientists. Its technologically embodied-extended nature necessarily makes the cognitive cycle to be context dependent, bringing about context dependence in the explanatory part shared via language. Despite of the context-dependence of scientific practices the past decades have witnessed a large-scale diffusion of explanatory concepts, i.e. themata, coming from dynamical systems theory and statistical physics into science fields which, till then, seemed totally disconnected. This trend increases the coherence of explanatory patterns and consequently enhances and diversifies the language communication possibilities between scientific practices. The structure that emerges is one which, on the one hand, possesses explanatory stability, that is, a coherent and pluri-contextual explanatory backbone that co-relates classically independent or weakly dependent scientific fields, and on the other hand, allows context-dependent flexibility and adaptivity of explanatory patterns to specific processes it strives to understand. The picture that emerges reveals the science as a social self-organizing adaptive cognitive system.
... These issues may be due to a variety of reasons, such as disciplines researching sport at varying levels from molecular to the environment, whilst also applying discipline-specific terminology [1,7]. Within the tertiary education sector, the fast growth of sport science has led to a focus on specialisation [10,11], which has partially been attributed to the lack of an overarching, unifying framework [7,11]. Furthermore, current practices are often seen to offer the illusion of integration, but do not fully combine methods and techniques alongside theories and concepts [1]. ...
... Independent methodologies and measurement techniques could be reconciled to build upon and learn from one another. Interdisciplinarity offers collaborative problem-solving which may potentially lead to enhanced inquisition, the identification of new questions and the resolving of existing problems [10]. For interdisciplinarity to occur, new methods and procedures are required, which may challenge engrained and culturally pervasive disciplinary norms. ...
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Commonly classified as individual, task or environmental, constraints are boundaries which shape the emergence of functional movement solutions. In applied sport, an ongoing challenge is to improve the measurement, analysis and understanding of constraints to key stakeholders. Methodological considerations for furthering these pursuits should be centred around an interdisciplinary approach. This integration of methodology and knowledge from different disciplines also encourages the sharing of encompassing principles, concepts, methods and data to generate new solutions to existing problems. This narrative review discusses how a number of rapidly developing fields are positioned to help guide, support and progress an understanding of sport through constraints. It specifically focuses on examples from the fields of technology, analytics and perceptual science. It discusses how technology is generating large quantities of data which can improve our understanding of how constraints shape the movement solutions of performers in training and competition environments. Analytics can facilitate new insights from numerous and complex data through enhanced non-linear and multivariate analysis techniques. The role of the perceptual sciences is discussed with respect to generating outputs from analytics that are more interpretable for the end-user. Together, these three fields of technology, analytics and perceptual science may enable a more comprehensive understanding of constraints in sports performance.
... Science communities explore and strive to explain the immense diversity of processes observed at different levels and time scales of substance organization in nature. As the key properties of each level cannot be formal, i.e., mathematically, deduced from the laws that govern the behaviour of the more microscopic components (Hristovski, 2013, Hristovski, Balagué and Vázquez, 2014, 2019, different scientific disciplines have emerged (see Fig 1). The diversity of levels and phenomena constrains the scientific language of each discipline to form a specific vocabulary for naming and explaining the properties and processes under study, as well as communicating knowledge among scientists. ...
... This is how the high disciplinary specialization and the development of context-specific science languages have entailed a lack of communication and transfer of knowledge among scientists (Hristovski, 2013). It is in such context that the SUMA educational framework suggests applying movement analogies (Hristovski, Balagué & Vázquez, 2014) to learn the unifying concepts of science provided by the DST and SP. Such concepts are increasingly used in a wide spectrum of scientific disciplines, and particularly, are useful to understand the behaviour of simple, as well as, of complex dynamic systems. ...
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Contemporary education, based on a fragmented structure of topics, limits reasoning and critical thinking in students, contributing little to the development of the integrative competencies and knowledge considered essential in modern society. Interdisciplinary approaches give raise to new specialties, but do not reduce the barriers within and between STEM (Science, Technology, Engineering and Mathematics), Humanities and Arts. The proposal of the SUMA (Synthetic Understanding through Movement Analogies) educational framework is applying movement analogies to learn the unifying concepts of science, that is, concepts that persist despite the changes of scientific paradigms or theories, and have a pluri-contextual character. This way, the SUMA framework aims to capitalize on the current perspective of cognitive science that defines cognition as ecological, embodied and enactive, and emphasizes body movement as a means to acquire abstract concepts. After explaining the origins, rationale, ongoing research and supporting tools (learning platform) of the SUMA educational approach, the proposed learning phases illustrate the differences between the more known interdisciplinary physical education and the current approach.
... The embodied learning in SUMA educational framework is based on Kolb's (1984) experiential learning approach (Hristovski et al., 2014), and it consists of the following teaching phases: The introspection in the first phase is not necessarily movement-based because it can be based on any life experience, but it is further scaffolded using a movement activity. These phases can be supported by various contexts, such as learning in natural settings or using educational technology, such as videos, augmented learning and virtual environments, and individual or group arrangements (Hristovski, Balagué, Almarcha and Martínez, 2020;Torrents et al., 2021). ...
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The transfer of knowledge among academic subjects and linking different phenomena are crucial education competencies in Bloom's taxonomy of learning goals. From another side, modern cognitive science defines cognition and learning as embodied. The Synthetic Understanding through Movement Analogies (SUMA) educational framework proposes embodied learning of general scientific principles and concepts and knowledge transfer among academic disciplines encompassing sciences, humanities and arts. Accordingly, this research aimed to evaluate the educational potential of teaching a set of Dynamic Systems Theory (DST) concepts through body movement experiences in first-grade high school students. Five classes of high school students (n = 71; 23 girls, 46 boys and 2 non-binaries, aged 12-13 y.) followed a four-week intervention addressed to teaching five DST concepts (order parameter, stability, control parameter, instability and phase transition) and transfer them to biological and social phenomena. Students followed four teaching phases: a) embodied experience, b) reflective observation of the experience, c) abstract conceptualization of the experience using the five general concepts, d) transfer of knowledge through the concepts to different phenomena from biological and social science academic subjects. Students' integration and transfer of knowledge abilities were evaluated pre-and post-intervention through a questionnaire and three open-ended questions. Results were compared using non-parametric Wilcoxon matched-pairs test and effect sizes were calculated through PS dep measures. Students' abilities to integrate and transfer knowledge increased post-intervention (Z= 7.322, p< .0001, PSdep = 1). The effect of the intervention points to the potential of teaching general DST concepts through body movement experiences in high school students for achieving the goals of an embodied and unificatory transdisciplinary education.
... Differing from interdisciplinarity and multidisciplinarity, transdisciplinarity calls for a "space of knowledge beyond the disciplines" [28, p.2]. Within such a 'space', previously independent theoretical and methodological constructs can be blended to afford inquisitive and collaborative thinking, allowing researchers and practitioners in sport the opportunity to ask new questions, and work toward the solving of existing problems viewed through a different lens [29,30]. Moreover, transdisciplinarity extends beyond abstractions of knowledge, calling for integration, interaction and engagement between the inquirer and inquiry [28]. ...
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Where do novel and innovative ideas in sport science come from? How do researchers and practitioners collectively explore the dynamic landscape of inquiry, problem, solution and application? How do they learn to skilfully navigate from current place and practice toward the next idea located beyond their current vantage point? These questions are not just of philosophical value but are important for understanding how to provide high-quality support for athletes and sport participants at all levels of expertise and performance. Grounded in concepts from social anthropology, and theoretically positioned within an ecological dynamics framework, this opinion piece introduces a hunter-gatherer model of human behaviour based on wayfinding, situating it as a conceptual guide for implementing innovations in sport science. Here, we contend that the embedded knowledge of a landscape that guides a successful hunting and gathering party is germane to the pragmatic abduction needed to promote innovation in sport performance, leading to the inquisition of new questions and ways of resolving performance-preparation challenges. More specifically, exemplified through its transdisciplinarity, we propose that to hunt ‘new ideas’ and gather translatable knowledge, sport science researchers and practitioners need to wayfind through uncharted regions located in new performance landscapes. It is through this process of navigation where individuals will deepen, enrich and grow current knowledge, ‘taking home’ new ideas as they find their way.
... Por lo tanto, la estructura del lenguaje científico emergente se caracteriza tanto por su estabilidad y coherencia, correlacionando campos científicos clásicamente independientes, y por su flexibilidad y adaptación a contextos y procesos específicos. Es decir, el lenguaje científico se comporta como un sistema social adaptativo auto-organizado (Hristovski, Balagué, & Vázquez, 2014). ...
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Las autoras del trabajo titulado “Unificar las cièncias del deporte” (núm. 114, julio-sep. 2013), responden a la réplica enviada por el Prof. Raúl Martínez Santos titulada “Reflexiones y condiciones para una unificación de las ciencias del deporte” .
... Per tant, l'estructura del llenguatge científic emergent es caracteritza tant per la seva estabilitat i coherència, correlacionant camps científics clàssicament independents, i per la seva flexibilitat i adaptació a contextos i processos específics. És a dir, el llenguatge científic es comporta com un sistema social adaptatiu autoorganitzat (Hristovski, Balagué, & Vázquez, 2014). ...
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In the current sporting landscape, it is not uncommon for professional sport teams and organizations to employ multidisciplinary sport science support teams. In these teams and organizations, a "head of performance" may manage a number of sub-discipline specialists with the aim of enhancing athlete performance. Despite the best intentions of multidisciplinary sport science support teams, difficulties associated with integrating sub-disciplines to enhance performance preparation have become apparent. It has been suggested that the problem of integration is embedded in the traditional reductionist method of applied sport science, leading to the eagerness of individual specialists to quantify progress in isolated components. This can lead to "silo" working and decontextualized learning environments that can hinder athlete preparation. To address this challenge, we suggest that ecological dynamics is one theoretical framework that can inform common principles and language to guide the integration of sport science sub-disciplines in a Department of Methodology. The aim of a Department of Methodology would be for group members to work within a unified conceptual framework to (1) coordinate activity through shared principles and language, (2) communicate coherent ideas, and (3) collaboratively design practice landscapes rich in information (i.e., visual, acoustic, proprioceptive and haptic) and guide emergence of multi-dimensional behaviors in athlete performance.
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The aim of the paper is to point out one way of integrating the supposedly incommensurate disciplines investigated in sports science. General, common principles can be found among apparently unrelated disciplines when the focus is put on the dynamics of sports-related phenomena. Dynamical systems approaches that have recently changed research in biological and social sciences among others, offer key concepts to create a common pluricontextual language in sport science. This common language, far from being homogenising, offers key synthesis between diverse fields, respecting and enabling the theoretical and experimental pluralism. It forms a softly integrated sports science characterised by a basic dynamic explanatory backbone as well as context-dependent theoretical flexibility. After defining the dynamic integration in living systems, unable to be captured by structural static approaches, we show the commonalities between the diversity of processes existing on different levels and time scales in biological and social entities. We justify our interpretation by drawing on some recent scientific contributions that use the same general principles and concepts, and diverse methods and techniques of data analysis, to study different types of phenomena in diverse disciplines. We show how the introduction of the dynamic framework in sport science has started to blur the boundaries between physiology, biomechanics, psychology, phenomenology and sociology. The advantages and difficulties of sport science integration and its consequences in research are also discussed.
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We present a phenomenological model outline of self-organization in the scientific conceptual space with emphasis of the position of sport sciences. The obtained model has a rugged structure of basins of attraction and the learning dynamics is defined as a hopping of the learning system within the confined general basin of attraction. The paper examines how changes in the conceptual space change the structure and the dynamics of exploratory behavior of learners. When concepts of higher explanatory generality are absent the system becomes fragmented in mutually weakly connected or disconnected basins of attraction which corresponds largely to the current state in science and humanities education. On the contrary, when such concepts are present, the height of the barriers significantly lowers and the system reconfigures itself into a landscape of connected basins of attraction offering a unification of apparently distant areas of knowledge. The general explanatory concepts play the role of ‘catalysts’ which lower the transition barriers between conceptual spaces of scientific fields. We further discuss how general explanatory concepts from the nonlinear dynamical systems theory and statistical physics can become tenets of a new educational program and teacher profile.
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