Dossier Philoformation - 18e Colloque des Nouvelles Pratiques Philosophiques (NPP) à l'Université de Genève (23-24 novembre 2019)
Studying philosophical dialogue using Epistemic Network Analysis (ENA) within an
international school curriculum
Katarina Hayek1 a fait une recherche épistémique dans deux classes de
l'École Internationale de Genève dont la finalité est de mesurer l'efficacité épistémique
de la Philosophie pour enfants, menée sous la forme de discussions. Son projet est d'utiliser
des outils offerts par l'ENA (Epistemic Network Analysis) qui est le fruit de recherches
L'intérêt de travailler dans l'école internationale de Genève est de proposer ces outils
d'analyse pour aborder des élèves suivant un programme construit par l'école en partenariat
avec l'UNESCO. Cette grande institution et plus spécifiquement son Bureau d'éducation, a conçu
ce programme dans le but de préparer le jeune à vivre avec les compétences nécessaires au
monde du XXIe siècle. Le but de ce programme est que le jeune soit "capable d'interagir en
mobilisant et utilisant d'une façon éthique, des données, des connaissances, des aptitudes,
des compétences, des valeurs, des attitudes, et des technologies de façon à s'engager
effectivement et agir dans des contextes différents du XXIème siècle pour atteindre le bien
tant individuel que collectif et global"
Pour analyser l'impact de ce programme sur l'éducation des jeunes, Katarina Hayek a suivi
et travaillé des discussions philosophiques avec des enfants (méthode plutôt Lipmanienne) dans
un certain nombre de cours, pendant deux ans. Cette analyse a relevé d'une part les attitudes
sociales, d'autre part, les interactions intellectuelles, finalement la capacité de penser et
s'exprimer librement des participants.
En mettant dans un graphique les diverses habiletés des interactions avec autrui et
d'autre part les différentes facettes de la pensée critique, on peut noter les différentes
qualités des interactions et de là, l'influence de certaines compétences intellectuelles sur
la création d'une interaction sociale.
On peut aussi voir la progression du même graphique dans le temps d'une part d'une
compétence et d'autre part de son effet sur une autre et la réciprocité de leurs
Les outils de l'ENA permettent d'analyser finement un état présent d'une classe et des
individus qui la composent. Ainsi on peut évaluer un moment présent. Mais cela permet aussi
d'évaluer les mêmes données dans un temps postérieur, et ainsi les progrès réalisés.
Dans les graphiques présentés par la recherche de Madame Hayek, on voit des compétences
telle la créativité, la question provocante et discutable, le caractère, le respect d'autrui,
la gestion de soi, la réflexion, la négociation, l'attention à apprendre, la pensée liée à une
attitude de "care", la pensée liée à la critique. Ces compétences sont analysées et mises en
relation, quand une compétence tend à enrichir l'autre.
Dans sa conclusion, Madame Hayek montre comment cette analyse permet de mettre en valeur
un des aspects du développement du programme de l'Unesco : la progression du
développement de compétences essentielles à ce programme grâce à la formation à la discussion
Research surrounding the study of classroom discourse is evolving rapidly as researchers
become more attune to its contribution to understanding and conceptualising the social
contexts of teaching and learning. The Philosophy for Children (P4C) practice is a meaningful,
data rich, and collaborative context and can hence serve as a window into the development of
students' complex thinking. Yet at present there is less research aimed at closely analysing
or assessing the philosophical dialogues themselves as compared to studies looking at P4C's
impact in other subject domains. If P4C is to be valued for facilitating meaningful dialogue
then it is precisely this dialogue that should be analysed. P4C should be valued as a practice
in itself rather than as a means to an evaluative end. It is therefore deemed ineffective to
solely measure its effectiveness through external skill-based or subject-based measuring tools
(Lien, 2004). Nonetheless, epistemic philosophical progress is difficult to assess and
practitioners may often question "are we getting anywhere?"Golding (2017) notes that the best
way to know if progress is being made is to get a full view of "the dynamic journey" through
studying philosophical dialogue.
I/ Project Overview
This study explores how an innovative tool, Epistemic Network Analysis (ENA), could
provide a method to closely study P4C dialogue and further highlight its importance within the
primary school curriculum at the International School of Geneva.
A total of 341 minutes of P4C dialogue from four classes (N=87 participants) was analysed
from September 2019 to March 2020. The dialogue was transcribed and closely studied in order
to code for student demonstration of curriculum competences. Subsequently, ENA software was
used to quantify, visualise and analyse these competences in network models.
II/ Research Background
The International School of Geneva's Curriculum: The ULP Framework
In September 2018, the International School of Geneva (ISG) in partnership with UNESCO's
International Bureau of Education (IBE) created and launched the Universal Learning Programme
(ULP): a K-Year 11 (ages 3-15) curriculum developed in response to the perceived need to
provide students with 21st century competences. It is founded upon the belief that competence
is "the developmental capacity to interactively mobilize and ethically use information, data,
knowledge, skills, values, attitudes, and technology to engage effectively and act across
diverse 21st century contexts to attain individual, collective, and global good" (Marope,
2017). From September 2018 to present, the ULP curriculum has been progressively implemented
at the International School of Genevaand is currently in the process of undergoing appraisal
III/ Philosophy for Children (P4C) and Assessment
The Philosophy for Children (P4C) practice is a fundamental component of the ISG primary
school curriculum and aims to develop both collaboration and character in students. The P4C
programme was created by Professor Matthew Lipman and his colleagues in the 1960s and 1970s in
New Jersey, USA. However, the roots of P4C developed long before the 1960s. The programme is
built upon ancient Greek ideas of Socratic dialogue where philosophical discussion is sparked
by asking questions or reflecting upon stories.
At the International School of Geneva, philosophical sessions are often started by reading
a novel that stimulates thought and leads students to collaboratively create their own
questions. Students are invited to vote on which question they would like to discuss and then
there is a group dialogue surrounding the question selected.
According to Vygotsky, the classroom is transformed into a micro-society where there is a
simulation of the real ethics of social life (1985). Dewey (1983) noted that this is
especially significant when learners interact together in what is referred to as a community
of inquiry (CI). Within the CI, it is thought that learners "internalise universal concepts
and fundamental principles of social life on a day-by-day basis" and their dialogue becomes an
individual and social experience (Dewey, 1983; Vygotsky, 1985 as cited in Daniel &Auriac,
2011). The objective of P4C is not for students to "learn philosophy" by memorising famous
philosophers' names or theories but rather to have them "do philosophy" by engaging in the
practice of philosophy through critical thinking.
Within the ISG, P4C provides a setting in which students are encouraged to think for
themselves and to practice their skills in context. It focuses on what
students are able to express through a facilitative approach. It is also an area where
transdisciplinarity is inherent, with topics discussed often branching out into differing
areas of knowledge. It therefore provides a potential way to examine multiple linked
curriculum competences simultaneously.
A Potential Tool for P4C Assessment: Epistemic Network Analysis
Epistemic network analysis (ENA) is a network modeling method developed by David W.
Shaffer and his colleagues in the early 2000s at the Wisconsin Center for Education Research
at the University of Wisconsin-Madison, USA (Shaffer et al., 2009).
In order to understand the method of ENA, it is useful to first consider its origins in
epistemic frame theory. Stemming from the concept of Communities of Practice (Reimann, 2008),
epistemic frame theory suggests that any community of practice has a culture that is composed
of skills, knowledge, identity, values, and epistemologies. This collection forms the
epistemic frame of the community of practice. In simple terms, ENA is a form of network
analysis designed to closely study and assess these epistemic frames (Shaffer, 2018). It
attempts to study the patterns of association between knowledge, skills and values as they are
expressed in dialogue. ENA bridges principles from social network analysis (SNA) and discourse
analysis in order to model patterns in what people say and do (Wooldridge, Carayon, Shaffer,
& Eagan, 2018). It was originally developed in order to model theories of cognition,
discourse and culture. In contrast with other network modeling techniques, ENA is designed to
study a small set of constructs that are demonstrated through highly dynamic and dense
interactions (Gasevic&Ferreia, 2019).
The ENA method is founded on the idea that "the structure of connections among cognitive
elements is more important than the mere presence or absence of those elements in isolation"
(Shaffer, 2018). The connections in data are therefore viewed as valuable for critical
analysis (Shaffer et al., 2009). It builds on the theories of DiSessa (1985), who defined
learning as a process where students connect elements of experiential knowledge through their
inherent frameworks in order to develop new knowledge and deep understanding. Within
education, ENA has been used extensively by researchers. For example, Chiu & Linn used ENA
to show how learners develop STEM expertise by "constructing a knowledge web: a repertoire of
ideas and the connections among them" (2011). It has been used to model cognitive connections
during problem-solving among students and their interaction with mentors (Shaffer & Nash,
2012). ENA has also been used in a variety of research contexts outside of the field of
education. Nonetheless, it has not been used to study P4C dialogue and there remains a gap in
the research on how it could be effective in studying the thinking patterns within
IV/ Research Design
The project presented here applied ENA methods to P4C sessions in order to closely examine
students' complex thinking during philosophical discussions. This section outlines the
research steps and decisions taken.
A/ Sampling strategy and characteristics of the study group
The International School of Geneva's primary school comprises both French and English
language classes with students from age three to ten. Students begin to follow P4C lessons at
age five. They then follow regular weekly or bimonthly P4C sessions. Classes from grades two
to four which conducted these regular P4C sessions in English were included within the study.
Grade one was excluded based on the reasoning that they had limited experience of the P4C
programme. This resulted in data from four classes (with a total of 87 students) in years two
to four to comprise the sample for this study.
B/ Process of video data analysis and ethical considerations
In order to closely analyse the conversations taking place during P4C sessions, video
recordings are regularly made by classroom teachers and staff and stored within the school
data repository. For the purpose of this study, the video recordings were anonymously
transcribed without reference to particular student names or classes. These anonymised
transcriptions served as the foundation for subsequent coding analysis.
C/ Creation of the "Codebook"
A document, named the "codebook", outlines each of the school's curriculum constructs. For
each construct it provides its definition, guidance notes, keywords and some examples of how
the construct may be identified in practice. Table 1 below is an extract example of the
Table 1: Extract from ISG codebook
|Code||Guidance Note||Definition||Source||Example (YES)||Example (NO)|
|Curiosity||Demonstrates a desire to know something more than what is evident.
Questions or statements indicating curiosity require responses beyond simple
clarification - necessitates a higher level of thinking.||"Desire for information in the absence of extrinsic reward."||Pekrun, R. (Ed.), Linnenbrink-Garcia, L. (Ed.). (2014). ||"Why does time pass?"||"What is the name of the character again? I forgot."|
These constructs can also be referred to as "codes". Within social sciences, coding is the
analytical process of attaching meaningful attributes, "codes", to data (Ingram & Elliott,
2020). For the purposes of this study, the ISG "codes" were compared and refined against
The codebook remains a working document. The focus here is not on finding the perfect
definition of each construct, but rather a working definition that serves to unite the
community in their understanding of how the competences are understood within the context of
P4C. Furthermore, as this research takes perspectives from the Grounded Theory approach, the
generation of the codebook and the research process as a whole is purposefully iterative. This
is described more in the next section.
D/ Coding: The application of the codebook to classroom data
An early adopter of the grounded theory, Charmaz, stated that "codes rely on interaction
between researchers and their data. Codes consist of short labels that we construct as we
interact with the data." (2012, p. 5). The coding process was therefore largely an iterative
and recursive process.
The classroom P4C transcripts were coded line by line for presence or absence of
constructs. Coding was undertaken by two researchers with differing perspectives and
backgrounds in order to maximise objectivity. The data was coded by an English-speaking native
with a background in teaching, and a coder of Chinese background who worked in the field of
economics and educational policies. Each coder coded the transcripts and discussed
differences. During coding, each utterance was coded for occurrence of constructs, resulting
in coded transcriptions. Thus, originally qualitative conversations were operationalised for
detailed analytical processes carried out using ENA.
E/ Modelling networks using the epistemic network analysis (ENA) tool
Coded transcriptions were uploaded to the ENA Web Tool version 1.6.0 (Marquart, Hinojosa,
Swiecki, & Shaffer, 2018). Within the ENA tool, the coded transcript data is segmented
according to discourse analysis principles: it is firstly broken up into lines which represent
the smallest unit of data. These lines are then grouped into stanzas (lines which are related
to one another). In doing so, ENA adopts three key assumptions. First, that it is possible to
systematically identify a set of meaningful features in the data (codes). This assumption
further implies that utterances (or lines) can be coded according to the competence codebook.
Secondly, it assumes that the data has local structure represented in conversations (or
stanzas). Thirdly, the way in which the codes are connected to one another is significant for
analysis of the data (Shaffer, Collier, &Ruis, 2016).
For the purpose of this study, all lines of data (all student and teacher utterances)
within each lesson were considered. A moving window process was applied in order to construct
a network model for the data. This shows how codes in one line are connected to codes that
occur within the recent temporal context (Siebert-Evenstone et al., 2017), which was defined
as 10 lines. The ENA model aggregates the resulting networks in the model according to a
binary summation where the networks for a given line reflect either the presence or absence of
a co-occurrence between codes, after which it normalises the networks before subjecting them
to the dimensional reduction. This is an important step as it accounts for the fact that
different units of analysis may have different amounts of coded lines in the data. Singular
value decomposition (SVD) was applied as the dimensional reduction, as it maximises the
variance explained by each dimension (see Shaffer et al., 2016 for a more detailed explanation
of the mathematics; see Arastoopour, Swiecki, Chesler, & Shaffer, 2016 and Sullivan et
al., 2018 for examples of this kind of analysis). The model ultimately results in a network
graph where the node (dots) size represents the frequency of the code occuring and the
thickness of the lines connecting these nodes shows how strong the relationship is between
those codes. These networks can be used for visual, descriptive and statistical analysis
(Wooldridge et al., 2018).
The results presented in this section highlight ENA's capabilities in reflecting the
community of inquiry's thinking during philosophical dialogue.
A/ Competence assessment within a single class : Year Two data
In order to illustrate how ENA can be used to study a single P4C session, dialogue from a
randomly selected P4C session from a year two class within the school repository was analysed.
Table 2 presents an overview of the data.
Table 2: Year Two (21 students, 9 boys, 12 girls, ages: 6-7, 1 female teacher)
P4C session overview
|Stimulus ||Question for discussion |
|Question was raised spontaneously by a student during a regular class and
noted down for later discussion. ||Why do we need to listen? |
As shown in Table 2, the question for discussion was "Why do we need to listen?" The
discussion lasted 32 minutes altogether.
Figure 2: Year 2 P4C dialogue ENA network model
The network shows a relatively balanced structure between the coded competences. The
network structure indicates that students were not only demonstrating these competences in
isolation but were connecting them when speaking. The network is weighted slightly towards the
lower left quadrant indicating that the competences of interacting with others
and critical thinking were demonstrated more frequently
during the P4C discussion.
Nodes which are positioned closer together are more often linked in the data as compared
to those which are less linked. A triangle of thicker edges at the left side of the space
connecting the competence nodes of character, respect for
others , critical thinking and interacting with
others illustrates that students predominantly demonstrated these competences and
drew upon these competences together. This is further demonstrated by the relatively larger
size of these nodes as compared to, for example, creativity which shows
a smaller node in grey.
Displaying competences in the network model allows for interpretation of the way in which
connections between the competences are being made, in addition to which competences are being
demonstrated relatively more often. However, while studying the competences and connections
between these competences in a single network can be illustrative in itself, notable
characteristics become most apparent when networks are compared.
B/ Competence assessment between groups within a single class: Year two student vs
Figure 3: Student (green) and teacher (purple) networks Year
Figure 4: Year Two Subtracted network graph Teacher vs
Figure 3 and 4 depict network models constructed from the same P4C session dialogue data
shown in Table 2. Models were produced to show the student's competence network (green) and
the teacher's competence network (purple).
A subtracted network graph serves to highlight the differences between the students'
competence network and the teacher's network (Figure 4). While students made stronger links
between self-management and how to learn, as
reflected by the more pronounced green edge connecting these nodes in the upper right
quadrant, the teacher's network shows a very thick edge highlighted in purple between the
competences caring thinking and provocative/debatable
questioning. This suggests that the teacher was likely structuring the dialogue
through a series of questions while also modeling caring thinking. Within the teacher network,
there is also a clustering of utterances in the lower right quadrant surrounding these
competences. For this reason, the teacher network mean (shown as a purple square) is
positioned in the same lower right quadrant and the network is weighted towards this side.
In contrast, students had a larger spread of utterances linking competences, as
demonstrated by the distribution of green dots across the projected space. There are however
two notable triangles with a common vertex of critical thinking, linking
respect for others and character in the upper
left quadrant and self-managementand how to learn
in the upper right quadrant. The student network is weighted towards the upper half
of the space, with the mean shown as the green square found higher than that of the teacher
network mean. Visually, it can be noted that there is a meaningful difference between the
means of the student network as compared to that of the teacher network. Although the ENA tool
is capable of computing inferential statistics related to the data, the current research
design does not meet the fundamental assumptions underlying these statistics and therefore
reporting them would be misleading and incorrect (White & Gorard, 2017).
C/ Competence assessment within a single class over time
Data from one year three class between September 2019 and March 2020 was used in order to
illustrate how competences shown during P4C sessions could be assessed within a single class
Table 3: Class 3A P4C sessions overview: September and March
Table 3: Class 3A (22 students, 12 boys, 10 girls, 1 male teacher)
overview: September and March
|Stimulus||Month||Question selected by class for discussion|
|Elfie (Lipman, 2003) Chapter One||September||Why do some people feel shy?|
|Elfie (Lipman, 2003) Chapter Three||March||Why do we dream?|
Due to the convenience sampling design of this study and the fact that by design, children
create the questions within a P4C class, it was not possible for the class to discuss the same
question for both lessons. As shown in Table 3, the questions are not identical. However, the
competences communication, reflection, critical thinking, and
collaboration can be compared between September and March as these
competences were found to be most common to all P4C sessions regardless of the question or
Figure 5: Class 3A networks from September (blue) and March
Figure 6: 3A Subtracted network graph September (blue) vs March
Figure 5 shows 3A's P4C session network from September in blue and March in red. The
connections between the competence nodes reflection and
critical thinking in both networks indicate a strong demonstration and
co-occurrence of these competences in both P4C sessions. However, there was not found to be a
significant difference between the two sessions as shown by the absence of an edge connecting
these competence nodes in the subtracted network graph (figure 6). The means shown by the blue
and red boxes are positioned close to one another signifying that the data did not suggest a
large difference between the networks. Nonetheless, the subtracted network graph shows a
greater co-occurrence between the competences reflection and
communication in September in contrast to a greater co-occurrence between
critical thinking and collaboration in March.
Additionally, the subtracted network shows that overall there was a greater co-occurrence of
reflection and collaboration, and
communication and critical thinking in September. This may
suggest that the dialogue in September was broader in that it was touching upon several
competences simultaneously in comparison with the dialogue from March where the results
suggest students were focused entirely on collaborating to think critically.
Although this example served to show the potential in comparing a single group over time,
it should be noted that the time period between the sessions was limited. The goal was
observational: to observe the state of P4C sessions at different time periods without
manipulating any other factors, yet this also meant that the class was responding to two
different questions and this may explain the difference in competences identified and
highlighted in the results. It does however show that researchers may wish to consider the use
of ENA in more robust longitudinal studies in the future.
D/ Competence assessment between classes: Year Three P4C Sessions
Classroom P4C data was analysed from two grade three classes. Both classes follow the same
structure for P4C sessions. P4C sessions take place every two weeks at 13h30, after lunch and
mindfulness. The session begins with students sitting in a circle. A chapter from Lipman's
novel Elfie (2003) is read aloud, first by the teacher and then by the
students taking turns. After reading aloud, the students have a few minutes to discuss the
chapter and formulate a question related to the story. Once the questions are reviewed, the
class conducts a blind vote, wherein each student votes for the question they would like to
discuss that session. The question with the most votes becomes the question for the dialogue.
Data from the classes were compared using subtracted network models. In doing so, the most
notable characteristics of each group become more evident. Competences which were most common
between the dialogues were selected for network construction to compare how these competences
differed between the classes. Nonetheless, it should be noted that although both groups read
the same extract from the novel, the questions produced are not identical. These differences
are due to the fact that students focus on different aspects of the story and create questions
they find most interesting and relevant. This is shown in table 4 in the next section.
E/ Year 3 P4C Sessions - October 2019
In October, both year three classes focused on chapter two of the novel Elfie
by Lipman (2003). They both followed the structure detailed in the previous
section. Table 4 shows how each class responded to the stimulus.
Table 4: Year 3 P4C Sessions - October
Table 4: Year 3 P4C Sessions - October
|Class ||Group Composition ||Stimulus ||Question selected by class for discussion |
12 boys, 10 girls
1 male teacher
|Elfie (Lipman, 2003) Chapter Two||Why are people so different? |
|3B* ||22 students |
9 boys,13 girls
1 male teacher
|Elfie (Lipman, 2003) Chapter Two||What is forgetting? |
*3A and 3B are not references to particular classes within the school. The A and B solely
serve to distinguish between the different year three classes within this study.
Figure 7 shows the network of 3A in red, the network in 3B in blue and the subtracted
network graph below. The weighted network accounts for the difference in the number of
utterances between the classes and therefore enables comparison.
The networks of 3A and 3B have a very similar structure of connections. The thick edge
connecting the competence nodes reflection and critical
thinking in the lower right quadrant of both 3A and 3B's networks illustrates
that these competences were often drawn upon together and were demonstrated more frequently
than the other competences over the course of 3A and 3Bs philosophical dialogues. Although the
overall network structure of 3B is similar to that of 3A's, illustrating that there were
common competences demonstrated in similar ways by both groups, there are some slight
differences between the networks. For example, it can be seen that 3A's network has, on a
whole, heavier weighted edges between the nodes. This group was consistently demonstrating and
linking competences throughout the sequence of their P4C dialogue. In contrast, 3B has thinner
edges. However, 3B has a thicker edge connecting the competence nodes of
negotiation and reflection. This illustrates that students
within class 3B were negotiating with one another over the course of their dialogue.
Figure 7: Year three ENA networks - October
The differences between 3A and 3B networks become more apparent when studying the
subtracted network model (figure 8). The fact that this model is predominantly showing edges
in red reflects that 3A connected these competences more frequently during their P4C
discussion than the class of 3B. However, the edge shown in blue in the subtracted network
model, between negotiation and reflection provides
further support that students in class 3B were negotiating with one another over the course of
dialogue more than those in class 3A. The means of 3A and 3B (indicated by boxes) are situated
in close proximity to each other. This confirms the similar structure of the networks and
suggests that dialogues in 3A and 3B showed similar features.
Figure 8: Year three subtracted network graph - 3A vs 3B -
Studying these models revealed a notable difference in the way in which class 3A
collaborated as compared to class 3B. A subtracted network model (Figure
8) derived by the decomposition approachshowed that 3B made more
connections between negotiation and reflection as
compared to 3A, highlighting that this class more frequently demonstrated the microcompetence
of negotiation when collaborating with each other.
The process of ENA outlined how the ISG curriculum competences can be defined, identified
and assessed through the P4C programme. This was achievable through the creation of a
codebook, coding of dialogue, and finally network modelling and analysis. The use of ENA
served as a tool to explain student competences within a single P4C discussion and also
highlight how competences can be demonstrated through different philosophical inquiries.
Lastly, it showed that ENA may provide a means to view competence development over time within
the students' evolution within the P4C programme.
The ENA networks allow us to view how the community of inquiry uses philosophical dialogue
in order to draw upon the constituent elements of competence together and to connect these
competences over the course of their dialogue. The value of ENA is in its ability to visually
show the connections between the competences rather than solely the competences themselves,
though it also serves as a descriptive tool for visually displaying what is coded. The network
model should therefore be considered alongside the context of the philosophical dialogue.
Researchers should start with the coded dialogue, create and study the network model and then
return to the original P4C session in order to deeply understand where the connections in the
model come from. The online ENA web tool allows the user to click on the connections between
competence nodes and review the metadata that resulted in the connection (Shaffer, 2016). In
doing so, the network becomes both the tool and the visual for understanding assessment within
the P4C context.
In sum, ENA may help to assess the curriculum competences displayed during P4C dialogue
through thick description: the method of closely studying connections in data in order to
further understand how and why learning happens (Shaffer, 2018). ENA's potential for providing
a holistic view of how students connect the constituent elements of competence within
philosophical interactions can provide insight into how they learn.
Lastly, it can be noted how the P4C programme shares common goals with the ISG primary
school curriculum. For example, one of the seven macrocompetences that the ULP aims to develop
is interacting with others (UNESCO-IBE and International School of
Geneva, 2018). It defines this competence as collaborating in order to address complex
problems. In studying the P4C dialogue, interacting with others was
frequently demonstrated and coded accordingly.
The P4C programme also aims for children to practice critical thinking by giving reasons
and providing evidence (Fisher, 2007). Studying P4C dialogue provides a window into how
students are able to express their reasoning.
Ultimately, the P4C programme is a pillar of the curriculum within the International
School of Geneva and provides valuable insight into the way students learn while also helping
them to develop as thoughtful individuals.
VII/ Implications for future research
Future research may wish to consider longitudinal studies in order to evaluate competence
development over time, as this could not be confidently explored in the current study due to
time constraints. By carrying out longitudinal studies, researchers can more accurately
examine how network models of competence may change over time during the P4C programme.
Furthermore, although the ENA approach adopted within this study provided one example of
how P4C sessions could be studied, multiple methods could be explored in order to capture the
complexity and multifaceted nature of philosophical discussions.
VIII/ A final thought
Assessment, like philosophy, is not an exact science. It is a process. Only through the
purposeful process of "observing, interpreting and recording evidence of learning" (Marope,
2017, p. 26) can we truly attempt to comprehend how students express their inner thinking.
This study contributes to this collaborative and iterative process and hopes to inspire others
to do the same.
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(1) Katarina Hayek is an international primary school teacher with experience teaching
various curricula in Switzerland, Italy and the United States. With degrees from McGill
University in Canada and Durham University in the United Kingdom, she views research as a
fundamental part of teaching and learning. Her most recent research, conducted within the
International School of Geneva, focuses upon the Philosophy for Children (P4C) programme and
investigates dialogical assessment using Epistemic Network Analysis (ENA).
Diotime, n°85 (07/2020)