This dissertation will elaborate on the understanding of intersubjective meaning making by analyzing the traces of collaborative knowledge construction users leave behind in socio-technical systems. Therefore, it will draw upon more theoretical and more formal models of cognitive psychology to describe and explain the underlying process in detail. This is done with the goal to support intersubjective meaning making and thus elevate informal collaborative knowledge construction in nowadays aordances of social media.

1. gefördert durch das Kompetenzzentrenprogramm
Sebastian Maximilian Dennerlein
9 September, 2013
Social Computing Team & LL Design Team „Bits and Pieces“
© Know-Center 2013
www.know-center.at, www.kti.tugraz.at
Understanding & Supporting
Intersubjective
Meaning Making (IMM)
in Socio-Technical Systems
A Cognitive Psychology Perspective

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Introduction - Motivation
 Situation of self-directed learners in the context of
hypertext/ -media systems:
 Increased meta-cognitive load in addition to demands due to
learning (Narciss et. al., 2007)
 Absence of support has been found detrimental in self
directed learning (Mayer, 2004)
 Nowadays collaborative contexts in socio-technical systems
increase the situation‘s complexity and necessary cognitive
demands
 Reason: Need for Intersubjective Meaning Making (IMM)
in addition to the precondition of the individual situation to be
able to collaboratively construct knowledge
 Consequence: Support is crucial!!

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Introduction – Research Objective
 To be able to assist self directed learners in collaborative
contexts with the needed support, intersubjective meaning
making has to be understood
 IMM is the essence of collaboration: „Collaboration is
primarily conceptualized as a process of shared meaning
construction.” (Stahl et. al., 2006)
 IMM def.: „Intersubjective meaning-making takes place when
multiple participants contribute to a composition of inter-
related interpretations.“ (Suthers, 2006)
 Gaps:
 No clearly defined concept
 No adequate support regarding the manifold process
 Goal: Bridging of these gaps!

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Introduction - Research Questions
 Can the process of Intersubjective Meaning Making (IMM) be
described and explained by an integrated model through
combining more theoretical and more formal approaches of
cognitive psychology?
 Can this integrated model be empirically validated in
different settings by the means of achieving a higher
correspondence of the cognitive and the social system and
a shared understanding respectively?
 How can these insights be used to develop support services
including appropriate affordances to support the process of
IMM in socio-technical systems?

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Introduction – Framework
 Artifact-Actor Network (Reinhardt, 2009) „Social Semantic
Server“ as basis of EU-IP „Learning Layers“: Scaling up
Technologies for Informal Learning (e.g., Ley et al., 2013)
 LL Design Team Bits & Pieces (B&P) – Application Scenario:
 Health care employees are usually under great time pressure while
managing their daily work
 Quick (symbolic) representations and the affordance to visually make
sense of them afterwards are needed
 stimulation of IMM would provide essential support!
+
Actor Network: Artifact Network:
Artifact-Actor
Network (AAN)

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Introduction – Example application
scenario (B&P)
Realization of IMM support by revealing differences between the
individual and collective understanding :
 e.g., highlighting of the most helpful documents of the collective
(green) or emphasizing different categorization approaches of the
collective (yellow).

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Theoretical Background
Distributed Cognition
Formal Aspects of
Socio-Cognitive
Processes
Uptake of
Meaning
…
Stochastic
Modelling of
Mental
Categories
Conceptual
Aspects
Co-
evolution
Model
...
SECI
Model
but: vague description of contained processes

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Theoretical Background
 Basis: Distributed Cognition (DC; Hutchins, 2000)
 distributed cognitive systems can be analysed in terms of how
knowledge is distributed
 BUT: DC remains vague in describing socio-cognitive processes
 Theoretical Aspects: e.g. Coevolution model (Cress et. al., 2008;
Kump et al., 2013)
 description of interaction of internal and external knowledge
representations as a form of co-evolution between the cognitive and
social system
 Formal Aspects: e.g. Uptake of Meaning (Suthers, 2005)
 uptake appears in the sequences of collaborative interactions, „in
which one participant‘s action on a representation [=interpretation]
is taken up by another participant in a manner that indicates
understanding of its meaning“ (Suthers, 2006)

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Theoretical Background
 Practical literature on relevant experiments and methods
 Assessment of internal and external knowledge
representations (Ley et al., 2011; Kump et. al., 2013):
 External: qualitative content analysis of wiki articles
 Internal: SNA of concept maps and association tests
 Method for assessment of uptake – uptake graph (Suthers,
2005)

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Method - Basis
iterative methodological triangulation of ethnography,
experiment and design (Hollan et.al., 2000)
Qualitative analysis of application
domain and materials
Assessment of
cognitive and social
system to analyse
coevolution and
shared
understanding
IMM support services
Domain dependent:
e.g. Health Care –
home visit,
GP practice etc.

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Method – 1. Research Question
 Design of an integrated model based on literature work
 consisting out of:
 Visual representation of IMM
 Process description
 Additionally literature work serves the need to distinguish
IMM from other similar concepts
 E.g. Sense Making
 Hypotheses:
 Intersubjective Interpretations
 IMM
 Subjective Interpretations
 SM
Can the process of IMM be described and explained by an integrated model
through combining theoretical and formal approaches of cognitive psychology?

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1.RQ IMM Model – Visual Representation
(Fu et. al., 2008)
Sketch of visual representation:
 Visual representation of
IMM in collaboration
 Detailed definition of
internalization and
externalization (ass &
acc)
 Inclusion of different
kinds of interpretations

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1.RQ IMM Model – Process Description (B&P)
Experience
Remember
Experience
Re-
Experience
Sense
Making
of Learning
Episode
Share
Awareness
Imitation/
Uptake
Aggregation
Exploitation
Negotiation
(Informal) Sense Making Intersubjective Meaning Making
 IMM not necessarily a linear process!

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Method – 1. Research Question
 Iterative refinement and enrichment of the model by insights
gained in (field-) studies:
 qualitative analysis of realistic work practices to elaborate on
the model and elicit the necessary context for uptake – method:
 qualitative analysis of existing socio-technical systems to break
down the available services (& affordances) useful for IMM
Can the process of IMM be described and explained by an integrated model
through combining theoretical and formal approaches of cognitive psychology?

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1. RQ IMM Model – Mapping of IMM
steps, Affordances & Services
Visualization Recommendation …
Experience
Remember
Re-Experience
Sense Making
Share
Awareness
Imitation
Aggregation
Exploitation
Negotiation
SenseMakingIMM
Affordances
Timeline
visualization
Visualization of personalized
recommendations
support services

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Method – 2. & 3. Research Question
 Inferred model will be transferred into assumptions and
hypotheses
 Testing of corresponding hypotheses in controlled (field-)
experiments
Can this integrated model be empirically validated in different settings by the
means of achieving a higher correspondence of the cognitive and the social
system and a shared understanding respectively?
 Improvement of old or design of new support services to
selectively support steps of IMM
How can these insights be used to develop support services including
appropriate affordances to facilitate the process of IMM in socio-technical
systems?

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Discussion
 Motivation to socially analyse collaboration and its drivers
based on Stahl et.al. (2006)
 claim that theorizing about mental models in individuals'
heads does not help regarding IMM
 BUT: analysis of mental models in comparison to the
collective representation is helpful to analyse meaning
making (Cress et al., 2013; Fu et.al., 2012)
 Important CAVEATS:
 do not limit IMM to one single kind of interpretation
 do not constrain unit of analysis and corresponding log files

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Literature
 Cress, U., & Kimmerle, J. (2008). A systemic and cognitive view on collaborative
knowledge building with wikis. International Journal of Computer-Supported
Collaborative Learning, 3(2), 105-122.
 Cress, U., Held, C., & Kimmerle, J. (2013). The collective knowledge of social tags:
Direct and indirect influences on navigation, learning, and information processing.
Computers & Education, 60(1), 59-73.
 Fu, W.-T. (2008). The microstructures of social tagging: a rational model.. In B.
Begole & D. W. McDonald (eds.), CSCW, 229-238.
 Fu, W.-T., & Dong, W. (2012). Collaborative Indexing and Knowledge Exploration: A
Social Learning Model. IEEE Intelligent Systems, 27(1), 39-46.
 Hollan, J., Hutchins, E., & Kirsh, D. (2000). Distributed cognition: toward a new
foundation for human-computer interaction research. ACM Transactions on
Computer-Human Interaction, 7(2), 174-196.
 Hutchins, E. (2000). Distributed Cognition. Society, 34(6), 1-10.
 Kump, B., Moskaliuk, J., Dennerlein, S., & Ley, T. (2013). Tracing knowledge co-
evolution in a realistic course setting: A wiki-based field experiment. Computers &
Education, in press.
 Ley, T., Cook, J., Dennerlein, S., Kravcik, M., Kunzmann, C., Laanpere, M., Pata,
K., Purma, J., Sandars, J., Santos, P., & Schmidt, A. (2013). Scaling Informal
Learning: An Integrative Systems View on Scaffolding at the Workplace. In D.
Hernández-Leo, T. Ley, R. Klamma, & A. Harrer (Eds.), Proceedings of the 8th
European Conference on Technology-enhanced Learning, 484–489. Heidelberg:
Springer.

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Literature
 Nonaka, I., Toyama, R., & Konno, N. (2000). SECI, Ba and Leadership: a Unified
Model of Dynamic Knowledge Creation. Long range planning, 33(1), 5-34.
 Ley, T., Schweiger, S., & Seitlinger, P. (2011). Implicit and Explicit Memory in
Learning from Social Software: A dual-process account. In C. Delgado-Kloos, D.
Gillet, R. M. Crespo-Garcia, F. Wild, & M. Wolpers (Eds.), Proceedings of the 6th
European Conference on Technology Enhanced Learning, 449–454. Heidelberg:
Springer.
 Mayer, R.E. (2004). Should there be a three-strikes rule against pure discovery
learning? The case for guided methods of instruction. American Psychologist, 59(1),
14–19.
 Narciss, S., Proske, A. & Koerndle, H. (2007). Promoting self-regulated learning in
web-based environments. Computers in Human Behavior, 23(3), 1126–1144.
 Reinhardt, W., Moi, M., & Varlemann, T. (2009). Artefact-Actor-Networks as tie
between social networks and artefact networks. 5th International Conference on
Collaborative Computing Networking Applications and Worksharing, 1-10. IEEE.
 Stahl, G., Koschmann, T., & Suthers, D. (2006). Computer-supported collaborative
learning: An historical perspective. Computer, 409-426.
 Suthers, D. D. (2005). Collaborative knowledge construction through shared
representations. 38th Hawaii International Conference on System Science ,110.
 Suthers, D. D. (2006). Technology Affordances for intersubjective Meaning-making:
A research agenda for CSCL. The International Journal of Computer-Supported
Collaborative Learning, 1(3), 315-337.

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Thanks for your attention!
Sincere thanks are given to my mentor Tobias Ley and my consultant Paul
Seitlinger.
Stefan Schweiger, Peter Kraker, Gudrun Wesiak, Dieter Theiler, Rene Kaiser,
Marina Bratic, Vladimir Tomberg, Christoph Trattner and Stefanie Lindstaedt may
be thanked, too, for helping me with their valuable input.
sdennerlein@know-center.at
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