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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Evaluating Collaborative Modeling Processes</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Towards Understanding</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Supporting Collaborative Modeling Games</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Denis Ssebuggwawo?</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Background</institution>
          ,
          <addr-line>Context and Motivation</addr-line>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Institute of Computing and Information Sciences, Radboud University Nijmegen Heyendaalseweg 135</institution>
          ,
          <addr-line>6525 AJ Nijmegen</addr-line>
          ,
          <country>The</country>
          <addr-line>Netherlands, EU</addr-line>
        </aff>
      </contrib-group>
      <pub-date>
        <year>2009</year>
      </pub-date>
      <abstract>
        <p>Collaborative modeling is an approach aimed at enhancing productivity in Systems Design. Such an approach brings together stakeholders with varying degrees of skills and knowledge. Although much attention has been paid to the models created, little empirical work has focused on the modeling process itself, especially its evaluation. This raises the question whether an approach for analyzing and evaluating modeling processes exists yet. We aim to analyze and evaluate this neglected aspect. With the help of a three-tier framework, and by taking a game design theoretical approach to modeling, we identify the di erent aspects that drive the modeling process. We use this framework to develop an understanding of the inner structure of the modeling process with a view of evaluating it. We give some preliminary results to illustrate our framework and sketch an outline of future scienti c inquiry to re ne and tighten this framework.</p>
      </abstract>
      <kwd-group>
        <kwd>Collaborative Modeling</kwd>
        <kwd>Modeling Process Evaluation</kwd>
        <kwd>Modeling Game</kwd>
        <kwd>Game Design Theory</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>1.1</p>
    </sec>
    <sec id="sec-2">
      <title>Introduction</title>
      <p>
        Common Conceptual Modeling Assumptions
Some of the most popular conceptual modeling assumptions include the
following: modeling is product-oriented and design centered, the modeling process
involves two roles: domain expert, and model builder (systems analyst) each
playing their di erent roles at di erent times of conceptual modeling. Quality
assessment and measurement is often restricted to only the end-products - the
models (see, for example, [
        <xref ref-type="bibr" rid="ref7">7</xref>
        ]). We contend and hypothesize that conceptual
modeling should be not only a product-oriented and design-centered approach but
should also be a conversational activity and should be human-centered. There
are also intermediary products that need to be analyzed and evaluated.
      </p>
      <p>
        The process-oriented modeling approach assumes that the produced models
should contain \shared knowledge" and the modeling process is governed and
directed by a number of modeling rules and goals [
        <xref ref-type="bibr" rid="ref15">15</xref>
        ]. Modelers, however, do
not concisely and explicitly perform \step-wise" thinking, in particular for
nonexperts, in a product-oriented approach to incorporate such shared-knowledge in
their models. Viewing modeling as consisting of the process and the products ,
helps us study the commitments, agreements, negotiations, decision making and
consensus, etc. of the modelers and the rules and goals governing this process.
1.3
      </p>
      <p>
        The Research Problem, Questions and Objectives
One of the problems identi ed in collaborative/group modeling is lack of an
approach (and related tool-support) that can be used to study and improve
the communicative acts that lead to the generation of the models. Taking a
game-metaphorical approach to systems design (see, for example, [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ]) has the
potential of helping us determine the rules/goals driving the modeling games. To
achieve this, we eventually aim to design collaborative modeling games(CMGs)
in which the modeling process plays a signi cant role and human interaction and
communication take center stage.
      </p>
      <p>The following questions motivate our way of thinking in this research. The
main research question is: How can we evaluate enacted modeling processes (in
view of them achieving set goals)? To adequately answer this question, we raise
the following sub-questions: What is the quality of modeling? How can we
measure modeling process quality?
Our long-term objectives is to analyze, evaluate and understand collaborative
modeling games (CMGs) with the longer-term aim of supporting conceptual
modeling with a tool. A more immediate objective is to evaluate currently
available collaborative modeling sessions as if they are games to measure their e
ectiveness and e ciency.</p>
      <p>Figure 1 shows the design, execution, evaluation and validation cycle of the
CMGs.
2</p>
    </sec>
    <sec id="sec-3">
      <title>Related Work</title>
      <p>It being such a broad and multi-disciplinary area, it is hard to review all the
literature related to Collaborative (Group) modeling within the constraints of paper's</p>
      <p>
        Design the CMG
(Design Science Approach)
size. We therefore highlight only works directly related to our own. Bostrom et
al. [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ] provide one of the earliest attempts to consider group facilitated
meetings using a Group Support Systems (GSS) tool. This work is important since
it shows how a GSS tool can be used to help stakeholders generate information,
organize it, evaluate and select alternatives and nally communicate their
actions. Although communication is one of the aspects talked about and the role
of the facilitator is emphasized, communication is between the meeting
participants and the facilitator. This is signi cantly di erent from our approach where
communication plays a central role in the negotiation between the participants
to reach agreement and a common shared understanding.
      </p>
      <p>
        In [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ] the authors draw on Electronic Meeting Systems (EMS) technology
and re-engineering techniques to develop a method and a support tool for
modeling business processes. This is a richer approach in user involvement and idea
generation than other traditionally known collaborative modeling approaches
and tools. It, however, lacks the theoretical rigour and underpinning for process
modeling as it in uences only the quality of the generated models. The approach
is thus product-quality oriented. The work in [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ] and [
        <xref ref-type="bibr" rid="ref10">10</xref>
        ] was the rst attempt
to critically analyze the role of communication in modeling and the modeling
process. Our current work extends this work in emphasizing communication in
the modeling process and trying to nd out out how modelers generate their
models. It, however, di ers from it in that the current work employs the gaming
approach to modeling to determine the rules and goals under which modeling
processes take place.
      </p>
      <p>
        The research work in this paper builds more on the work of Rittgen [
        <xref ref-type="bibr" rid="ref11 ref12">11,12</xref>
        ].
Rittgen observes that in a collaborative environment, participants engage in
di erent types of conversations prior to the creation of an accepted model. Our
work, however, di ers from Rittgen's in that we take a more holistic approach
that looks at modeling as a game-design theoretic approach.
      </p>
    </sec>
    <sec id="sec-4">
      <title>Conceptual Framework and Methodological Approach</title>
      <p>
        In this section we present the basic conceptual framework to help us analyze the
process of modeling. The developed framework is related to two previously
developed frameworks: The Semiotic Quality (SEQUAL) framework of Krogstie et
al. [
        <xref ref-type="bibr" rid="ref7">7</xref>
        ] and The Quality of Modeling framework QoMo of van Bommel et al. [
        <xref ref-type="bibr" rid="ref15">15</xref>
        ].
The basic concepts of our \RIM" (Rules, Interactions and Models) framework
are shown in Fig. 2.
      </p>
      <p> </p>
      <p>Interactions lead to production of models, and 
generated (intermediate) models drive further 
interaction. 
Interactions </p>
      <p>Log 
&lt;&lt;time, t&gt;&gt; </p>
      <p> </p>
      <p>Models 
&lt;&lt;time, t&gt;&gt; </p>
      <sec id="sec-4-1">
        <title>A range of interactions over a period of time </title>
        <p>changes the rules of play and interactions are 
guided and restricted by rules of play. 
 </p>
        <p>Rules 
&lt;&lt;time, t&gt;&gt; </p>
      </sec>
      <sec id="sec-4-2">
        <title>Some  rules/goals  of  modeling  apply  to intermediary and end‐products and these  products may lead to new rules/goals. </title>
        <p>
          The RIM framework is a three-tier framework that examines the
communicative acts (interactions) in a modeling session, the rules/goals set, and the models
produced as a result of the interaction and collaboration which is, metaphorically
speaking, a sort of modeling game [
          <xref ref-type="bibr" rid="ref6">6</xref>
          ]. The di erent players work under a set of
rules and goals. The rules/goals, interactions and models are all time-stamped
to help us track and identify he interplay between any pair.
        </p>
        <p>
          In addition to the framework above we use the collaborative evaluation
(COME) framework given in Fig. 3 to evaluate the modeling process games
(CMGs) using a number of artifacts to be evaluated in view of the CMGs.
Employing the design science approach [
          <xref ref-type="bibr" rid="ref4">4</xref>
          ], we put these artifacts to use within the
context of evaluation and improvement of the CMGs.
        </p>
        <sec id="sec-4-2-1">
          <title>Validate Evaluation Approach</title>
          <p>  Evaluation Activities &amp; Criteria 
Generate  
(Rated/Weighted)evaluation:  
Criteria (guidelines, metrics, 
benchmarks) </p>
        </sec>
        <sec id="sec-4-2-2">
          <title>Evaluate by : </title>
          <p>Criteria (guidelines, 
metrics, benchmarks) 
 
 
s
s
e
s
‐rs
a
e
re‐assess</p>
        </sec>
        <sec id="sec-4-2-3">
          <title>Validate: </title>
          <p>Criteria (guidelines, 
metrics, benchmarks) 
Evaluate Artifact
 
e
t
a
r
e
n
e
g
‐
e
R
  
h
c
a
o
r
p
p
A
 
n
o
i
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a
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a
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    ii
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t
i
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n
o
i
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a
u
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a
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E
 
e
s
U
 
 </p>
        </sec>
        <sec id="sec-4-2-4">
          <title>Evaluation </title>
        </sec>
        <sec id="sec-4-2-5">
          <title>Approaches </title>
        </sec>
        <sec id="sec-4-2-6">
          <title>Discursive </title>
        </sec>
        <sec id="sec-4-2-7">
          <title>Evaluation</title>
        </sec>
        <sec id="sec-4-2-8">
          <title>Cause &amp; Effect  diagrams</title>
        </sec>
        <sec id="sec-4-2-9">
          <title>Ontological </title>
        </sec>
        <sec id="sec-4-2-10">
          <title>Analysis </title>
        </sec>
        <sec id="sec-4-2-11">
          <title>Lab, action &amp;  interpretive  research </title>
          <p> </p>
        </sec>
        <sec id="sec-4-2-12">
          <title>Field, surveys &amp;  case studies </title>
          <p> </p>
        </sec>
        <sec id="sec-4-2-13">
          <title>Participant/ </title>
        </sec>
        <sec id="sec-4-2-14">
          <title>Expert‐based </title>
          <p>evaluation 
 </p>
        </sec>
        <sec id="sec-4-2-15">
          <title>Analysis, </title>
        </sec>
        <sec id="sec-4-2-16">
          <title>Verification,  etc. </title>
          <p> 
In this section, we present an analysis of the results obtained from a collaborative
modeling session in a pilot study. In this rst phase of our reserved project, the
emphasis was on making the interactions and a few goals and rules using only
the RIM framework.
The business process scenario given out to modelers, was about developing a
Hazardous Material Management System (HMMS) by the Materials Management
Department (MMD) of a city council. Two researchers and three modelers(two
systems analysts (SA) and one domain expert (DE)) participated in the actual
modeling. Figure 4 shows one of the screen-shots from the modeling session
video recording. The session (which took 18 minutes) was video recorded with
good sound quality. The modelers were also given a digital writing pad, which
was recorded alongside the video. This provided us with a full, synchronized
recording of all raw data we could wish for.
 </p>
          <p>Fig. 4. Screenshot of a collaborative modeling session
4.2</p>
          <p>
            Results and Analysis
We rst transcribed the video recordings, then made an annotation and
categorization of the speech acts. We mainly drew on Language-Action Perspective
(LAP) theory, Speech-Act Theory (SAT), Discourse Analysis and the
Communicative Action Theory (CAT), see for example, [
            <xref ref-type="bibr" rid="ref3">3</xref>
            ]. Table 1 shows a sample
categorization of the speech acts.
          </p>
        </sec>
      </sec>
    </sec>
    <sec id="sec-5">
      <title>Findings and Discussion</title>
      <p>In this section we give some of our observations from the data obtained from
the modeling session. The ndings are given within the framework and
methodological approach in Fig. 2.</p>
      <p>Setting the Agenda. It is noted that modelers, without the help of a
facilitator, set their own agenda by structuring the modeling process in the following
phases: (I) - Setting the main approach:choosing the language and subdivision of
work (II) - Exploring and deciding which actors take part in the modeling process
and (III) - Modeling the sub-processes.</p>
      <p>
        Categorization of the Conversations. It was noted from the video and
the transcription that the communication among the modelers can broadly be
categorized as a negotiation. This was the same conclusion reached in [
        <xref ref-type="bibr" rid="ref11">11</xref>
        ]. This
comes from the argumentations (argue for/against) resulting in either
acceptance,i.e.agreement (support) or rejection of the proposals. Rejection indicates
disagreement. More details are found in [
        <xref ref-type="bibr" rid="ref14">14</xref>
        ].
      </p>
      <p>
        Categorization of Modeling Rules and Goals. From the transcription
and observations it was noted that the rules and goals guiding the modeling
process could be categorized as: imposed in the scenario or created within the
modeling game. These rules and goals were further categorized as explicit -directly
set and stated or implicit - indirectly stated and set. In [
        <xref ref-type="bibr" rid="ref14">14</xref>
        ] these rules and goals
are explained in more detail. They include: rules that were set for the game are:
Goal setting rule: creation goal, Goal setting rule: validation goal and rules that
were set in the game are: Goal setting rule: grammar goal, Goal setting rule:
creation goal and Goal setting rule: grammar goal.
6
      </p>
    </sec>
    <sec id="sec-6">
      <title>Conclusions and Further Research</title>
      <p>This paper has looked at a research program aimed at shedding light on the
process (act) of modeling. We employ an interactive and collaborative modeling
approach, within the context of communicative modeling of business processes,
to one modeling case. We have developed a three-tier conceptual framework and
a methodological approach which can be used to analyze and understand the
communicative process of modeling. Three key concepts: interactions, rules/goals
and the modeling products have been identi ed.</p>
      <p>Contribution and Direction for Further Research. Our contribution in
this research is a framework that can be used to analyze modeling games and
an evaluation mechanism to measure the e ectiveness and e ciency of these
modeling games. We intend to focus on developing an evaluation mechanism and
its requirements using the framework in Fig. 3 and to develop a methodology to
enable us draw scienti cally sound and de nitive conclusions about collaborative
modeling processes.</p>
    </sec>
  </body>
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