1 d. (denis) ssebuggwawo 1, s.j.b.a. (stijn) hoppenbrouwers 1 & h.a. (erik) proper 1,2 1 icis,...
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D. (Denis) Ssebuggwawo1, S.J.B.A. (Stijn) Hoppenbrouwers1
&
H.A. (Erik) Proper1,2
1ICIS, Radboud University Nijmegen, The Netherlands2Public Research Centre -- Henri Tudor, Luxembourg
3rd Working Conference on The Practice of Enterprise Modeling
(PoEM’10)
Delft University, The Netherlands
9-10 November, 2010
Assessing Collaborative Modeling Quality Based on Modeling Artifacts
Overview
Collaborative Modeling Evaluation
Hypothesized Model & Alternative Model
Empirical Results
Conclusion & Future Direction
MENU
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Overriding GoalsDetermine the Efficacy: (Efficiency & Effectiveness )
- evaluate the different constructs (ML, MP, EP, ST) to determine the overall efficiency and effectiveness
Efficiency : reduce the effort
Effectiveness: improve the quality of the result
Determine the Success of collaborative effort : (Success factors)
- evaluate the modeling effort to determine (critical) success factors that influence the efficiency & effectiveness.
Overview
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Modeling ArtifactsAnchoring Collaborative modeling Evaluation on modeling artifacts
Modeling Language (ML)
Modeling Procedure (MP)
End-Products (EP)
Support Tool or Medium (ST/M)
Overview
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The Modeling Artifacts
Overview
Artifact Explanation
ML Concepts (constructs) in which the modelers express and communicate the solution.
MP Processes (methods) for defining the problem and is reaching solution .
EP Intermediary and end-products (models ).
ST Enabling environment and support tools for the interaction and collaboration, communication, etc.
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Supporting FrameworksSEQUAL (Lindland et al., 1994; Krogstie, et al., 2006)
Based on: Semiotic theory
Understanding the quality of conceptual models
TAM (Davis 1986; Davis et al., 1989)
TRA/TPB (Fishbein, 1975; Ajzen, 1991)
About: Attitudes, Beliefs, Intentions/Perceptions, Behaviour
Explaining & predicting user acceptance of IS/ITs
MEM (Moody, 2001; Moody, 2003)
Based on : Methodological pragmatism (Theo.Know validation)
Evaluating IS design methods & TAM
CM Evaluation
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Theory of Reasoned Action (TRA)
CM Evaluation
PERCEPTIONS INTENTIONS BEHAVIOUR
External/ Internal Psychological Behavioural Environment variables variables variables
Attitudes toward Act or Behaviour (AB)
Subjective Norm (SN)
Behavioural Intention (BI)
Actual Behaviour (B)
Behavioural Beliefs and
Outcome Evaluations (bbioei)
Normative Beliefs and
Motivation to Comply (nbjmcj)
Uncontrollable factors Controllable factors
Fig. 1. TRA Model
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CM EvaluationHypothesized Model Interactions
…
ML MP
EPST
ML_1
ML_2
ML_n
ST_1 ST_2 ST_n
…EP_1 EP_2
EP_n
…
MP_1 MP_2
…MP_n
Fig. 2. Hypothesized Model Interactions
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The Constructs
Perceived Quality of the Modeling Language (PQML)
Perceived Usefulness of the Modeling Procedure (PUMP)
Perceived Quality of the End-Products (PQEP)
Ease of Use of the Medium or Support Tool (EOUM/ST)
CM Evaluation
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CM Evaluation: Original Quality Dimensions
Artifact Quality Dimensions # SourcesModeling Language(ML)
construct deficit, construct overload, construct redundancy, construct excess; expressive power, directness, systematicity; syntax, semantic & pragmatic clarity; modeling primitive adequacy
10Wand and Weber (1993), Lindland et al. (1994), Krogstie et al. (2006), Krogstie et al. (2001), List and Korherr (2006), Nysetvold and Krogstie (2005), Soderstrom et al. (2002), Stirna and Persson (2007)
Modeling Procedure(MP)
efficiency; effectiveness; ease of application, in-out-description adequacy, process & relation description adequacy, method compatibility, interaction & collaboration adequacy, communication & negotiation adequacy; rule & goal commitment, shared understanding
10de Brabander and Thiers (1984), Duivenvoorde et al. (2009), Krogstie et al. (2006), Gemino and (2003), Hengst et al. (2006), Reinig (2003), Siau and Wang (2007), Siau and Rossi (1998), Recker (2006), Stirna and Persson (2007), Renger et al. (2008), Becker et al. (2000), Ssebuggwawo et al. (2009)
End-Product(EP)
correctness, completeness, propriety, clarity, consistency, orthogonality, generality, syntax adherence adequacy, semantics adequacy, pragmatics adequacy; user-comprehensibility; modifiability, re-usability, flexibility; user satisfaction.
15Lindland et al. (1994), Krogstie et al. (2006), Sedera et al. (2003), Pfeiffer and Niehaves (2005), Paul et al. (2004), Reinig (2003), Rosemann et al. (2001), Stirna and Persson (2007), Schuette and Rotthowe (1998)
Medium/Support Tool(M/ST)
tool functionality, performance & reliability; efficiency, effectiveness; satisfaction; synchronicity, negotiation/argumentation adequacy, commenting/proposition adequacy, planning/agenda setting adequacy
9Dean et al. (1994), Fjermestad and Hiltz (1999), Stirna and Persson (2007), Krogstie et al. (2006), Ssebuggwawo et al. (2009)
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CM Evaluation: Synthesized Quality Dimensions
Construct Quality Dimensions - New Groupings
PQML Understandability (ML1), Clarity (ML2), Syntax correctness (ML3),
Conceptual minimalism (ML4)
PUMP Efficiency (MP 5), Effectiveness (MP6), Satisfaction (MP7),
Commitment & Shared Understanding (MP8)
PQEP Product Quality (EP9), Understandability (EP10),
Modifiability & Maintainability (EP11), Satisfaction (EP12)
EOUM /ST Functionality (ST13), Usability (ST14), Satisfaction & Enjoyment (ST15),
Collaboration & Communication Facilitation (ST16)
Modeling Experiment:Collaborative modeling session using COMA tool
Evaluation:Using a measurement instrument (Questionnaire) 7-pt Likert Scale
Constructs to assess:PQML, PUMP, PQEP and EOUM
Empirical Results
Modeling Expt. & Evaluation
Goal: Retain factors that account for significant amount variance in the
data. Precursor to CFA.
Principal Component Analysis (PCA):Data reduction : determing the number of factorsFactor rotation : determining the (non-)correlation of factors
Common Factor Analysis/Principal Factor Analysis:understanding the relationship btwn: indicators (measured: MLs, MPs, EPs, STs) variables in terms of factor (latent: PQML, PUMP, PQEP, EOUM) variables
Empirical ResultsValidation & Reliability Tests
Exploratory Factor Analysis(EFA)
A priori hypotheses:Testing: a priori hypotheses/theories
Assessing Goodness-of-fit: Assessing the goodness-of-fit based on variance after factor reduction in EFA
Assessing validity & reliability: Testing and confirming the validity & reliability of a measurement
instrument
Empirical ResultsValidation & Reliability Tests
Confirmatory Factor Analysis(CFA)(Structural Equation Modeling (SEM))
Conclusion:
Rather than model quality, other artifacts can be used in the evaluation of quality and success of a collaborative modeling effort.
Future Direction:
Establishing the interdependencies of the artifacts and their impact on the overall quality
Measuring the acceptability and adoption of the quality framework in practice
Conclusion & Future Direction