=Paper=
{{Paper
|id=Vol-1641/paper3
|storemode=property
|title=Ready-to-hand Information and Computer-mediated Activity: Challenges, Opportunities, and Methods
|pdfUrl=https://ceur-ws.org/Vol-1641/paper3.pdf
|volume=Vol-1641
|authors=Anders I. Mørch
|dblpUrl=https://dblp.org/rec/conf/iseud/Morch15
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==Ready-to-hand Information and Computer-mediated Activity: Challenges, Opportunities, and Methods==
https://ceur-ws.org/Vol-1641/paper3.pdf
Ready-to-hand Information and Computer-mediated
Activity: Challenges, Opportunities, and Methods
Anders I. Mørch
Department of Education, University of Oslo, Norway
a.i.morch@iped.uio.no
Abstract: The theme of the workshop, coping with information, participation
and collaboration overload assumes that access to information, participation,
and collaboration is somehow problematic and probably more for older than
younger people. In this position paper I will explore and discuss the problem
along one line of research I have been involved in, addressing one problem
(information overload) and generating another (participation overload). Then, I
will describe a case study in co-creation in the domain of customer engagement
and discuss the methods we used for understanding participation and
collaboration, using a mixed methods approach. Implications for design (i.e.
technology; human organization) to address the problems will be suggested as
points for discussion in the workshop.
Keywords: co-creation, collaborative learning, collaboration, computer-based
critics, mutual development, pedagogical agents, reflection-in-action
1 Introduction
Collaboration software and social networking technologies (SNT) succeed not
primarily because of their user interfaces (high usability), but based on how they
attract a large number of users. They serve as platforms for social interaction and user
generated content and are not merely tools. Once hooked on a platform (e.g.
Facebook or LinkedIn) it may be hard to leave because you have invested
considerable effort in generating content (i.e. pictures, comments, group participation,
adding contacts, liking people, rating performances, and so on). The technology
automates parts of this by creating your account, and providing suggestions for
relevant information to add.
Most recently, analytic tools have been integrated with STSs, for data collection,
analysis, visualization and overview, and recommendations. By analyzing your data
with statistical methods and predictive modeling techniques, these systems can predict
how you will act and recommend what to do (e.g. purchase a certain product; join a
discussion group, contacts to add, improve performance in some area/domain).
17
Proc. of Third International Workshop on Cultures of Participation in the Digital Age - CoPDA 2015
Madrid (Spain), May 26th, 2015 (published at http://ceur-ws.org).
Copyright © 2014 for the individual papers by the papers' authors. Copying permitted for private and academic purposes.
This volume is published and copyrighted by its editors.
2 Coping with Overload
In a series of research efforts spanning several years, in different research groups
(HCI, AI, CSCW, CSCL) at different institutions in US and Norway, I have been
involved in solving problems, generating problems, and researching problems
pertaining to information, participation, and collaboration overload. I summarize the
outcome of these efforts, and raise some issues for further work and discussion.
2.1 Critiquing Systems Supporting Reflection-in-action
Critiquing systems (originating in the KBS/HCC group at CU Boulder) challenged
intelligent tutoring systems in domains in which optimal solutions were not attainable
(Fischer et al., 1991), most notable design. Whereas problem solving aims at optimal
solutions, design is about alternatives (possible solutions) and re-combinations within
a dynamically constrained space (moving target). Design is characterized by multiple
solutions, some better than others, according to a set of subjective criteria
(constraints) that include user (client) requirements, building codes, safety standards,
argumentation, designers’ preferences, and so on. Computer-based critics operates in
this design space and act by informing users (e.g. novice designers) about what moves
they can make to create better designs. By doing this, critics divide the design process
in two sub processes: construction and argumentation. Construction is the activity of
graphically creating the form of the solution by direct manipulation of graphical
building blocks, and argumentation is the activity of reasoning about the problem and
the possible solutions, e.g. considering what to do next, the pros and cons of the
different alternatives, the consequences of making certain moves, and which course of
action to chose (McCall, Fischer & Mørch, 1990).
This distinction led to the notion of integrated design environments, consisting of a
domain-specific construction kit and a hypertext system for representing
argumentation (Fischer et al., 1991). Computer-based critics create an “interruption”
of the construction situation (like a human critic standing behind your shoulder and
giving advice for how to improve a design sketch) when the spatial configuration of
the building blocks constitute a “violation” of one or more of the design rules. The
user interface of the integrated design environment was named Janus (after the
Roman god of two faces in opposite direction), and theoretically it was inspired by
Donald Schön’s notion of Reflection-in-Action (Schön, 1983), which we interpreted
to mean that general information for solving a design problem should be available and
relevant at the time the information is needed, thus coping with information overload.
Using today’s terminology, Schön’s theory suggested the integration of a web based
information system (e.g. a discussion forum) with a domain oriented design
environment for artifact creation, using automated analysis (analytics) to switch
between two modes of designing (constructive design and argumentative design).
Analytic engines built into contemporary networked environments (e.g. e-
commerce sites, social media, learning technologies) can generate overviews and
recommendations based on statistical methods, predicting how a user might act in a
new situation compared to how other users with a longer “forward trajectory” have
18
Proc. of Third International Workshop on Cultures of Participation in the Digital Age - CoPDA 2015
Madrid (Spain), May 26th, 2015 (published at http://ceur-ws.org).
Copyright © 2014 for the individual papers by the papers' authors. Copying permitted for private and academic purposes.
This volume is published and copyrighted by its editors.
acted in the past. Depending on the degree to which the “trajectories” of two users do
align, this approach will (or will not) solve the information overload problem.
2.2 Pedagogical Agents Prompting Participation and Advising Collaborative
Inquiry in a Distributed Collaborative Learning Environment
At the University of Bergen we further developed the idea of critiquing for
application to collaborative learning environments, calling the critics for pedagogical
agents (Jondahl & Mørch, 2002). As with critics, the pedagogical agents had “rules”
for modeling domain knowledge, and these rules represented what we knew about
participation in an inquiry based discussion forum called Future Learning
Environment (FLE) (Dolonen, Chen & Mørch, 2003). We found this “domain” harder
to understand than the domain of kitchen design implemented in the Janus system,
and consequently the rules by which we programmed the pedagogical agents more
speculative and likely to be modified and refined (Mørch, Dolonen & Nævdal, 2006).
Two of the rules in pseudo code form are: if less activity than the average participant
(in number of postings), then suggest higher activity; if there are many unaddressed
problems or questions in the forum, then suggest addressing one of them by an
answer or hypothesis. In this way we not only addressed the information overload
problem (inherited from critiquing systems), but also generated a new problem
(participation overload).
2.3 Mutual Development and Co-creation
Mutual development (Andersen & Mørch, 2009; Mørch & Andersen, 2010) is a
technique for co-creation of software artifacts through collaboration by two groups of
stakeholders: professional software developers and end-user developers. End-user
developers create local adaptations of a software product for personal or
organizational needs, and professional developers create new versions of the software
for sustaining their practice and increase revenue for their business. These end-user
developers have much in common with “lead users.” A lead user (von Hippel, 2005)
is an early adopter of a new innovation, or someone who likes to experiment with the
use of an existing product, or someone who creates an adaptation to a product based
on knowledge of a related product. Product developers will often seek out lead users
for feedback on early (beta) releases before they hit the market.
For a professional organization (e.g. a software house) to incorporate a new feature
first proposed by an end-user (e.g. a customer) into an existing line of products would
normally require multiple levels of collaboration. Developers collaborate when they
provide tools for communication and information sharing with end-user developers
and when they accept end user proposals for features in new releases (Andersen &
Mørch, 2013). Incentives are needed to make collaboration work; and contracts may
be necessary in order to handle ownership of a new innovation.
Mutual development involves multiple stakeholders, often in asymmetrical (e.g.
user-developer) relations. It starts with communication for the purpose of building a
common understanding. It continues by improvement request proposals or hacks
19
Proc. of Third International Workshop on Cultures of Participation in the Digital Age - CoPDA 2015
Madrid (Spain), May 26th, 2015 (published at http://ceur-ws.org).
Copyright © 2014 for the individual papers by the papers' authors. Copying permitted for private and academic purposes.
This volume is published and copyrighted by its editors.
submitted by end user developers, through collaboration with other end user
developers and with professional developers, the latter selecting and filtering out good
proposals for further work and incorporation. Research methods to identify and study
these phenomena (i.e. communication to build common understanding and multi-
disciplinary collaboration) benefit a mixed methods approach (combining qualitative
and quantitative research methods) (Fugelli, Lahn & Mørch, 2013), especially when
the user population is large, such as in crowd sourcing and mass collaboration
(Tapscott & Williams, 2007).
This brief presentation summarizes the work my colleagues and I have been
involved in over a number of years in a series of efforts in system building (software
applications) and empirical studies in user organizations, using techniques from HCI,
AI, CSCW, CSCW and EUD to cope with information, participation, and
collaboration overload, which can be summarized as problem framing experiments:
1. Solving a problem: information overload with computer-based critics, finding
information relevant to the task at hand;
2. Creating a problem: participation overload with pedagogical agents by asking
users to increase their participation in an online collaborative learning environment
in terms of quantity (number of postings) and in terms of quality (choosing the
appropriate inquiry type for a new posting);
3. Studying a problem: research methods using a mixed methods approach for
understanding communication and collaboration practices in a co-creation
community in customer-initiated software product development.
3 Challenges, Opportunities, and Methods for End-user
Development
There are multiple ways to address the aforementioned problems. EUD has a role to
play. Here are some open issues for further work and discussion at the workshop:
EUD in design; e.g. components and rules of composition; how to make design
environments modifiable in terms of composition (design) and recombination
(redesign)?
Ill-defined problems and EUD, i.e. refinement of rules to model a domain that are
crudely rendered at beginning;
Rules for combining software components (tools); rules for combining learning
resources; rules of participation; rules of interaction; rules of collaboration,
Constraints in EUD-enabled SNTs and collaboration software: in terms of roles,
interaction patterns, social structures, etc.
Learning analytics and EUD; what should be the role of EUD in LA research
Research methods: What are “appropriate” methods for analyzing problem
situations, identifying alternative (possible) solutions, combinatorial limitations,
etc.
How to analyze EUD activity and visualize the activity to 1) end user developers,
2) professional developers, and 3) other stakeholders (e.g. customers, managers)?
20
Proc. of Third International Workshop on Cultures of Participation in the Digital Age - CoPDA 2015
Madrid (Spain), May 26th, 2015 (published at http://ceur-ws.org).
Copyright © 2014 for the individual papers by the papers' authors. Copying permitted for private and academic purposes.
This volume is published and copyrighted by its editors.
References
1. Andersen, R., and Mørch, A. I. (2009). Mutual Development: A Case Study in Customer-
Initiated Software Product Development. In V. Pipek, M.B. Rosson, B de Ruyter and V.
Wulf (Eds.). Proceedings 2nd Int'l Symposium on End User Development (IS-EUD 2009).
Berlin Heidelberg: Springer, pp. 31-49.
2. Andersen, R. and Mørch, A.I. (2013). Get Satisfaction: Customer Engagement in
Collaborative Software Development. In Proceedings of the 4th International Symposium
on End-User Development, Springer-Verlag, Berlin, Heidelberg, 235-240.
3. Dolonen, J., Chen, W. and Mørch, A. (2003). Integrating Software Agents with FLE3.
Proceedings of CSCL 2003. Kluwer Academic, pp. 157-161.
4. Fischer, G., Lemke, A.C., McCall, R. and Morch, A.I. (1991). Making Argumentation
Serve Design. Human-Computer Interaction, 6(3&4), pp. 393-419.
5. Fischer, G., Lemke, A.C., Mastaglio, T.W., and Morch, A.I. (1991). The Role of
Critiquing in Cooperative Problem Solving. ACM Transactions of Information Systems,
9(2), pp.123-151.
6. Fugelli, P., Lahn, L.C. and Mørch, A.I. (2013). Shared prolepsis and intersubjectivity in
open source development: Expansive grounding in distributed work. In Proceedings of the
2013 conference on Computer supported cooperative work (CSCW`13). ACM, New York,
NY, USA, 129-144.
7. Jondahl S, Mørch A. Simulating pedagogical agents in a virtual learning environment. In:
Stahl, G, ed. Proceedings Computer Support for Collaborative Learning (CSCL 2002).
Boulder, CO, USA: Lawrence Erlbaum, 2002:531–532.
8. McCall, R., Fischer, G., and Mørch, A. (1990), Supporting Reflection-in-Action in the
Janus Design Environment. In The Electronic Design Studio: Architectural Knowledge
and Media in the Computer Era, 247-259. CAAD Futures. Cambridge, Massachusetts: The
MIT Press, 1990.
9. Mørch, A.I. and Andersen, R. (2010). Mutual Development: The Software Engineering
Context of End-User Development. Journal of Organizational and End User Computing,
22(2), pp. 36-57.
10. Mørch, A.I., Dolonen, A.I. and Nævdal, J.E. (2006). An Evolutionary Approach to
Prototyping Pedagogical Agents: From Simulation to Integrated System. Journal of
Network and Computer Applications, 29(2-3), 177-199.
11. Schön, D.A. (1983). The Reflective Practitioner: How Professionals Think in Action. New
York, NY: Basic Books.
12. Tapscott, D. and Williams, A.D. (2008). Wikinomics: How mass collaboration changes
everything. London, UK: Atlantic Group.
13. Von Hippel, E. (2005). Democratizing innovation. Cambridge, MA: MIT press.
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Proc. of Third International Workshop on Cultures of Participation in the Digital Age - CoPDA 2015
Madrid (Spain), May 26th, 2015 (published at http://ceur-ws.org).
Copyright © 2014 for the individual papers by the papers' authors. Copying permitted for private and academic purposes.
This volume is published and copyrighted by its editors.