This document summarizes research investigating the process of process modeling and its relation to modeling quality. It describes 6 research gaps in current knowledge and overviews 3 studies conducted: 1) developing a new visualization tool (PPMChart) to better understand modeling patterns, 2) exploring relationships between modeling patterns and model quality, and 3) theorizing a Structured Process Modeling Theory (SPMT) to explain observations. The theory combines existing cognitive load and fit theories. Future work is proposed to further validate findings through additional research cycles.
Design Knowledge Gain by Structural Health MonitoringFranco Bontempi
The design of complex structures should be based on advanced approaches able to take into account the behavior of the constructions during their entire life-cycle. Moreover, an effective design method should consider that the modern constructions are usually complex systems, characterized by strong interactions among the single components and with the design environment. A modern approach, capable of adequately considering these issues, is the so-called performance-based design (PBD). In order to profitably apply this design philosophy, an effective framework for the evaluation of the overall quality of the structure is needed; for this purpose, the concept of dependability can be effectively applied. In this context, structural health monitoring (SHM) assumes the essential role to improve the knowledge on the structural system and to allow
reliable evaluations of the structural safety in operational conditions. SHM should be planned at the design phase and should be performed during the entire life-cycle of the
structure. In order to deal with the large quantity of data coming from the continuous monitoring various processing techniques exist. In this work different approaches are discussed and in the last part two of them are applied on the same dataset. It is
interesting to notice that, in addition to this first level of knowledge, structural health monitoring allows obtaining a further more general contribution to the design knowledge
of the whole sector of structural engineering. Consequently, SHM leads to two levels of design knowledge gain: locally, on the specific structure, and globally, on the general class of similar structures.
Design Knowledge Gain by Structural Health MonitoringStroNGER2012
The design of complex structures should be based on advanced approaches able to take into account the behavior of the constructions during their entire life-cycle. Moreover, an effective design method should consider that the modern constructions are usually complex systems, characterized by strong interactions among the single components and with the design environment.
A modern approach, capable of adequately considering these issues, is the so-called performance-based design (PBD). In order to profitably apply this design philosophy, an effective framework for the evaluation of the overall quality of the structure is needed; for this purpose, the concept of dependability can be effectively applied.
In this context, structural health monitoring (SHM)
assumes the essential role to improve the knowledge on the structural system and to allow reliable evaluations of the structural safety in operational conditions. SHM should be planned at the design phase and should be performed during the entire life-cycle of the structure.
In order to deal with the large quantity of data coming from the continuous monitoring various processing techniques exist. In this work different approaches are discussed and in the last part two of them are applied on the same dataset.
It is interesting to notice that, in addition to this first level of knowledge, structural health monitoring allows obtaining a further more general contribution to the design knowledge of the whole sector of structural engineering.
Consequently, SHM leads to two levels of design knowledge gain: locally, on the specific structure, and globally, on the general class of similar structures.
Design Knowledge Gain by Structural Health MonitoringFranco Bontempi
The design of complex structures should be based on advanced approaches able to take into account the behavior of the constructions during their entire life-cycle. Moreover, an effective design method should consider that the modern constructions are usually complex systems, characterized by strong interactions among the single components and with the design environment. A modern approach, capable of adequately considering these issues, is the so-called performance-based design (PBD). In order to profitably apply this design philosophy, an effective framework for the evaluation of the overall quality of the structure is needed; for this purpose, the concept of dependability can be effectively applied. In this context, structural health monitoring (SHM) assumes the essential role to improve the knowledge on the structural system and to allow
reliable evaluations of the structural safety in operational conditions. SHM should be planned at the design phase and should be performed during the entire life-cycle of the
structure. In order to deal with the large quantity of data coming from the continuous monitoring various processing techniques exist. In this work different approaches are discussed and in the last part two of them are applied on the same dataset. It is
interesting to notice that, in addition to this first level of knowledge, structural health monitoring allows obtaining a further more general contribution to the design knowledge
of the whole sector of structural engineering. Consequently, SHM leads to two levels of design knowledge gain: locally, on the specific structure, and globally, on the general class of similar structures.
Design Knowledge Gain by Structural Health MonitoringStroNGER2012
The design of complex structures should be based on advanced approaches able to take into account the behavior of the constructions during their entire life-cycle. Moreover, an effective design method should consider that the modern constructions are usually complex systems, characterized by strong interactions among the single components and with the design environment.
A modern approach, capable of adequately considering these issues, is the so-called performance-based design (PBD). In order to profitably apply this design philosophy, an effective framework for the evaluation of the overall quality of the structure is needed; for this purpose, the concept of dependability can be effectively applied.
In this context, structural health monitoring (SHM)
assumes the essential role to improve the knowledge on the structural system and to allow reliable evaluations of the structural safety in operational conditions. SHM should be planned at the design phase and should be performed during the entire life-cycle of the structure.
In order to deal with the large quantity of data coming from the continuous monitoring various processing techniques exist. In this work different approaches are discussed and in the last part two of them are applied on the same dataset.
It is interesting to notice that, in addition to this first level of knowledge, structural health monitoring allows obtaining a further more general contribution to the design knowledge of the whole sector of structural engineering.
Consequently, SHM leads to two levels of design knowledge gain: locally, on the specific structure, and globally, on the general class of similar structures.
HTML, CSS i Javascript Web tehnologije - 3. predavanje - Startit.rsMilovan Jovičić
Kurs HTML, CSS i Javascript web tehnologija
3. predavanje - HTML5 elementi i uvod u CSS
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Modeling Framework to Support Evidence-Based DecisionsAlbert Simard
Describes a framework for modelling in a regulatory environment founded on sound scientific and knowledge management concepts. It includes 1) demand (isue-driven) and supply (model driven) approaches to modelling, 2) balancing modeler, manager, and user perspectives, 3) documentation to demonstrate due diligence, and a 700-term glossary.
Educational Process Mining-Different PerspectivesIOSR Journals
Process mining methods have in recent years enabled the development of more sophisticated Process
models which represent and detect a broader range of student behaviors than was previously possible. This
paper summarizes key Process mining perspectives that have supported student modeling efforts, discussing
also the specific constructs that have been modeled with the use of educational process mining and key
upcoming directions that are needed for educational process mining research to reach its full potential. Process
mining aims to discover, monitor and improve real processes by extracting knowledge from event logs readily
available in today’s information systems. This paper is designed to give a view on the capabilities of process
mining techniques in the context of higher education system which involves and deals with administrative and
academic tasks like enrolment of students in a particular case, alienation of traditional classroom teaching
model, detection of unfair means used in online examination, detection of abnormal values in the result sheet of
students, prediction about students performance, identify the drop outs, and students who need special attention
and allow the teacher to provide appropriate advising /counseling and so on.
The operation research book that involves all units including the lpp problems, integer programming problem, queuing theory, simulation Monte Carlo and more is covered in this digital material.
HTML, CSS i Javascript Web tehnologije - 3. predavanje - Startit.rsMilovan Jovičić
Kurs HTML, CSS i Javascript web tehnologija
3. predavanje - HTML5 elementi i uvod u CSS
Kurs je održan u okviru projekta besplatne obuke građana i u organizaciji Startit centra - više informacija na www.startit.rs
Modeling Framework to Support Evidence-Based DecisionsAlbert Simard
Describes a framework for modelling in a regulatory environment founded on sound scientific and knowledge management concepts. It includes 1) demand (isue-driven) and supply (model driven) approaches to modelling, 2) balancing modeler, manager, and user perspectives, 3) documentation to demonstrate due diligence, and a 700-term glossary.
Educational Process Mining-Different PerspectivesIOSR Journals
Process mining methods have in recent years enabled the development of more sophisticated Process
models which represent and detect a broader range of student behaviors than was previously possible. This
paper summarizes key Process mining perspectives that have supported student modeling efforts, discussing
also the specific constructs that have been modeled with the use of educational process mining and key
upcoming directions that are needed for educational process mining research to reach its full potential. Process
mining aims to discover, monitor and improve real processes by extracting knowledge from event logs readily
available in today’s information systems. This paper is designed to give a view on the capabilities of process
mining techniques in the context of higher education system which involves and deals with administrative and
academic tasks like enrolment of students in a particular case, alienation of traditional classroom teaching
model, detection of unfair means used in online examination, detection of abnormal values in the result sheet of
students, prediction about students performance, identify the drop outs, and students who need special attention
and allow the teacher to provide appropriate advising /counseling and so on.
The operation research book that involves all units including the lpp problems, integer programming problem, queuing theory, simulation Monte Carlo and more is covered in this digital material.
Why do we perform research?
What exactly is research?
How to perform research?
How to perform natural science?
How to perform design science?
How to design research?
Digital Transformation and IT Strategy Toolkit and TemplatesAurelien Domont, MBA
This Digital Transformation and IT Strategy Toolkit was created by ex-McKinsey, Deloitte and BCG Management Consultants, after more than 5,000 hours of work. It is considered the world's best & most comprehensive Digital Transformation and IT Strategy Toolkit. It includes all the Frameworks, Best Practices & Templates required to successfully undertake the Digital Transformation of your organization and define a robust IT Strategy.
Editable Toolkit to help you reuse our content: 700 Powerpoint slides | 35 Excel sheets | 84 minutes of Video training
This PowerPoint presentation is only a small preview of our Toolkits. For more details, visit www.domontconsulting.com
Falcon stands out as a top-tier P2P Invoice Discounting platform in India, bridging esteemed blue-chip companies and eager investors. Our goal is to transform the investment landscape in India by establishing a comprehensive destination for borrowers and investors with diverse profiles and needs, all while minimizing risk. What sets Falcon apart is the elimination of intermediaries such as commercial banks and depository institutions, allowing investors to enjoy higher yields.
LA HUG - Video Testimonials with Chynna Morgan - June 2024Lital Barkan
Have you ever heard that user-generated content or video testimonials can take your brand to the next level? We will explore how you can effectively use video testimonials to leverage and boost your sales, content strategy, and increase your CRM data.🤯
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What is the TDS Return Filing Due Date for FY 2024-25.pdfseoforlegalpillers
It is crucial for the taxpayers to understand about the TDS Return Filing Due Date, so that they can fulfill your TDS obligations efficiently. Taxpayers can avoid penalties by sticking to the deadlines and by accurate filing of TDS. Timely filing of TDS will make sure about the availability of tax credits. You can also seek the professional guidance of experts like Legal Pillers for timely filing of the TDS Return.
The world of search engine optimization (SEO) is buzzing with discussions after Google confirmed that around 2,500 leaked internal documents related to its Search feature are indeed authentic. The revelation has sparked significant concerns within the SEO community. The leaked documents were initially reported by SEO experts Rand Fishkin and Mike King, igniting widespread analysis and discourse. For More Info:- https://news.arihantwebtech.com/search-disrupted-googles-leaked-documents-rock-the-seo-world/
RMD24 | Retail media: hoe zet je dit in als je geen AH of Unilever bent? Heid...BBPMedia1
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Personal Brand Statement:
As an Army veteran dedicated to lifelong learning, I bring a disciplined, strategic mindset to my pursuits. I am constantly expanding my knowledge to innovate and lead effectively. My journey is driven by a commitment to excellence, and to make a meaningful impact in the world.
Putting the SPARK into Virtual Training.pptxCynthia Clay
This 60-minute webinar, sponsored by Adobe, was delivered for the Training Mag Network. It explored the five elements of SPARK: Storytelling, Purpose, Action, Relationships, and Kudos. Knowing how to tell a well-structured story is key to building long-term memory. Stating a clear purpose that doesn't take away from the discovery learning process is critical. Ensuring that people move from theory to practical application is imperative. Creating strong social learning is the key to commitment and engagement. Validating and affirming participants' comments is the way to create a positive learning environment.
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Marvin neemt je in deze presentatie mee in de voordelen van non-endemic advertising op retail media netwerken. Hij brengt ook de uitdagingen in beeld die de markt op dit moment heeft op het gebied van retail media voor niet-leveranciers.
Retail media wordt gezien als het nieuwe advertising-medium en ook mediabureaus richten massaal retail media-afdelingen op. Merken die niet in de betreffende winkel liggen staan ook nog niet in de rij om op de retail media netwerken te adverteren. Marvin belicht de uitdagingen die er zijn om echt aansluiting te vinden op die markt van non-endemic advertising.
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Unveiling the Secrets How Does Generative AI Work.pdfSam H
At its core, generative artificial intelligence relies on the concept of generative models, which serve as engines that churn out entirely new data resembling their training data. It is like a sculptor who has studied so many forms found in nature and then uses this knowledge to create sculptures from his imagination that have never been seen before anywhere else. If taken to cyberspace, gans work almost the same way.
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FACULTY OF ECONOMICS AND BUSINESS ADMINISTRATION
www.janclaes.info
Jan Claes
Supervisors UGent : Geert Poels & Frederik Gailly
Supervisors TU/e : Paul Grefen & Irene Vanderfeesten
Investigating the process of process modeling
and its relation to modeling quality
The Role of Structure Serialization
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CHAPTER 1 – INTRODUCTION
Research gaps
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Context
Increasing complexity of organizations
(globalization, customization, cost-effectiveness, …)
Process orientation
(efficiency, responsiveness, differentiation)
Process models
(representing process steps and execution constraints)
Process of Process Modeling
(translate mental image of process into formal model)
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Research gaps
GAP 1. Need for accurate measurements
GAP 2. Need for detailed, yet cognitive effective
visualizations
GAP 3. Knowledge about how people construct
process models (=PPM)
GAP 4. Knowledge about relation between PPM
and model quality
GAP 5. Need for practical process modeling methods
GAP 6. Knowledge about process modeling
challenges
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CHAPTER 2 – VISUALIZATION
PPMChart
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Study 1 – Visualization
Current techniques
Too high-level (Modeling Phase Diagrams)
Not cognitive effective (Dotted Chart)
Design method
9 principles of cognitive effective visualization
Evaluation method
Qualitative evaluation with 6 academic researchers
Modeling pattern discovery
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Study 1 – Visualization
Cognitive effective visualization design principles
Visual expressiveness (maximal use of graphical variables)
Perceptual discriminability (visual matches conceptual distance)
Graphic economy (maximal six values per variable)
Dual coding (combine graphics with text)
Semiotic clarity (exactly one symbol per exactly one concept)
Semantic transparency (intuitiveness through natural mapping)
Complexity management (modularization and hierarchical structuring)
Cognitive integration (easy integration with other charts/models)
Cognitive fit (fit with task and user)
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CHAPTER 3 – EXPLORATION
Relation with quality
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Study 2 – Exploration
Relation between modeling patterns and
process model quality
Exploration method
Compare PPMCharts with process models
Discover links
Evaluation method
Measure definition
Quantitative data collection
T-tests
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Study 2 – Exploration
Fast
modeling
Slow
modeling
Quick
lay-outing
Dedicated
lay-outing
phase
Continuous
lay-outing
Serialization
Chunked
modeling
Structuredness Movement Speed
Based on dataset of 40 unique modeling executions
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Study 2 – Exploration
Conjecture 1: Structured modeling
results in
understandable models
Conjecture 2: A high number of move operations
results in
less understandable models
Conjecture 3: Slow modeling
results in
less understandable models
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Structuredness
• MaxSimulBlock
• PercNumBlockAsAWhole
Speed
• TotTime
• TotCreateTime
Movement
• AvgMoveOnMovedElements
• PercNumElementsWithMoves
Study 2 – Exploration
Measurement
Model quality
• Perspicuity
a model that is unambiguously interpretable and can be made sound
with only small adaptations based on minimal assumptions on the
modeler’s intentions with the model
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Study 2 – Exploration
T-test
t=-2,231 (p=0,028)
T-test
t=2,199 (p=0,030)
Based on dataset of 103 unique modeling executions
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Study 2 – Exploration
T-test
t=-1,984 (p=0,049)
T-test
t=0,457 (p=0,648)
Based on dataset of 103 unique modeling executions
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Study 2 – Exploration
T-test
t=-2,183 (p=0,031)
T-test
t=2,505 (p=0,014)
Based on dataset of 103 unique modeling executions
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CHAPTER 4 – THEORISATION
Structured Process Modeling Theory (SPMT)
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Study 3 – Theorization
Explanatory theory
Theory building method
6 observations, 3 impressions (induction)
Explanation via existing theories (deduction)
Evaluation method
Assessment of novelty, parsimony, consistency,
plausibility, credibility, and transferability
Inconclusive empirical results, but open-world
assumption
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Study 3 – Theorization
Combined
Flow-oriented Aspect-oriented
Undirected
“Modeling
styles”
Based on dataset of 118 unique modeling executions
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Study 3 – Theorization
Observation 1. Almost all modelers paused frequently
during the modeling process
Observation 2. A large group can be categorized as
“flow-oriented process modeling”
Observation 3. A smaller group can be categorized as
“aspect-oriented process modeling”
Observation 4. Another large group used a combination
of both former styles
Observation 5. Another small group can be categorized
as “undirected process modeling”
Observation 6. The “undirected” sessions lasted longer
than the other approaches
Based on dataset of 118 unique modeling executions
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Study 3 – Theorization
Impression 1. Modelers need serialization of the modeling
process to deal with its complexity
Impression 2. Structured serializing of the modeling process
helps avoiding ‘mistakes’
Impression 3. Structured serializing does not support every
modeler to avoid ‘mistakes’ to the same extent
Based on dataset of 118 unique modeling executions
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Study 3 – Theorization
Cognitive Load Theory
Working memory capacity is limited
Working memory overload causes decrease in
• Effectiveness (i.e., more mistakes)
• Efficiency (i.e., more time and effort)
• Learning
Cognitive Fit Theory
Load is lower when there is a fit
• Between representation, tool or strategy on the one hand
• And task or modeler on the other hand
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Study 3 – Theorization
A B The more A, the more B A B The more A, the less B A B The more A, the more B on the long term+ +–
input material representation fit
working memory capacity
extraneous cognitive load germane cognitive load
cognitive schema construction
process model quality overall construction time
cognitive overload
intrinsic cognitive load
++
+
+++
–
task complexity
+
prior knowledge
––
– –
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Study 3 – Theorization
A B A determines BA B The more A, the more B+ A B The more A, the less B– A B A translates into B
learning style
degree of serialization
adopted serialization style
field-dependency need for structure
– +
course of intrinsic cognitive load
for process modeling phases
course of intrinsic cognitive load
for aggregation phases
course of cognitive overload
course of intrinsic cognitive load
for strategy building phases
+ + +
serialization style fitstructuredness of serialization
– –– –
1 2 3
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Study 3 – Theorization
Novelty (uses existing theories in fundamental new way)
Parsimony (11 constructs, 15 associations)
Consistency (can explain additional observations)
Plausibility (accurate and profound explanation)
Credibility (building blocks are established theories)
Transferability (problem solving in general)
Falsifiability (inconclusive, but open-world assumed)
Utility (only on longer term)
Consistency based on dataset of 143 unique modeling executions
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CHAPTER 5 – CONCLUSION
Summary & Future work
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Studies
Research
Cycle 3
Exploration
Research Cycle 1
Structured Process Modeling Theory
(SPMT)
RC6
SPMT
measures RC5
Cognitive
measures
RC4
Perspicuity
Engineering
Cycle 1
PPMChart
RC2
Modeling
styles
RC 7. Design validation
RC 7. Research design
EC 2. Problem investigation
RC 3. Problem investigation
RC 3. Research design
RC 3. Design validation
RC 3. Evaluation
RC 4. Evaluation
RC 4. Problem investigation
RC 4. Research design
RC 4. Design validation
RC 4. Research
RC 3. Research
EC 1. Problem investigation
EC 1. Solution design
EC 1. Design validation
EC 1. Implementation
EC 1. Evaluation
RC 1. Problem investigation
RC 2. Problem investigation
RC 2. Research design
RC 2. Design validation
RC 2. Research
RC 2. Evaluation
RC 1. Research design
RC 1. Design validation
EC 2. Evaluation
RC 8. Evaluation
RC 8. Research
RC 8. Design validation
RC 8. Research design
RC 8. Problem investigation
RC 7. Evaluation
RC 7. Research
RC 7. Problem investigation
EC 2. Design validation
EC 2. Solution design
RC 1. Evaluation
RC 1. Research
RC 6. Evaluation
RC 6. Research
RC 6. Design validation
RC 6. Research design
RC 6. Problem investigation
RC 5. Evaluation
RC 5. Research
RC 5. Design validation RC 5. Research design
RC 5. Problem investigation
EC 2. Implementation
EC2
Structured Process
Modeling Method
(SPMM)
RC8
Training
RC7
Influenceability
of method
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Studies
Study 1. Visualization
• EC1. How can the operations of the process of process modeling
be presented in a cognitive effective and efficient way?
• RC2. How do people construct process models in terms of
modeling styles?
PPMChart
Research instrument
(visualization)
Study 3. Theorization
• RC1. Why do people struggle with the complexity of process
modeling?
• RC2. How do people construct process models in terms of
modeling patterns?
SPMT
Theory – type II
(explanation)
Study 2. Exploration
• RC3. How are process and product of modeling related?
• RC4. How to measure (syntax) errors with cognitive origin?
• RC2. How do people construct process models in terms of
modeling patterns?
Process vs. product
Conjectures
(exploration)
GAP 2
GAP 3
GAP 6
GAP 3
GAP 4
GAP 1
GAP 3
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Future work
Study 5. Tool support
• EC3. How to support measurement of cognitive profile?
• EC4. How to support measurement of modeling effectiveness
and efficiency?
• EC5. How to support the SPMM
SPMTool
Tool support
(implementation)
GAP 1
GAP 1
GAP 5
Study 4. Method
• EC2. How to create process models in an effective and efficient
way?
• RC7. Is it possible to change a modeler’s approach towards
process modeling?
• RC8. How to transform the SPMT into a prescriptive theory?
SPMM
Practical method
(prescription)
GAP 5
GAP 6
GAP 5
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Key publications
Publications in international journals
Indexed by Web Of Science
• J. Claes, I. Vanderfeesten, J. Pinggera, H.A. Reijers, B. Weber, G. Poels, A visual
analysis of the process of process modeling, Information Systems and e-Business
Management, Vol 13(1), p. 147-190, 2015.
Under review
• J. Claes, I. Vanderfeesten, F. Gailly, P. Grefen, G. Poels, The Structured Process
Modeling Theory (SPMT) A cognitive view on why and how modelers benefit from
structuring the process of process modeling, resubmitted after revision to Information
Systems Frontiers.
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Key publications
Publications in international conference
proceedings
Indexed by Web Of Science
• J. Claes, I. Vanderfeesten, H.A. Reijers, J. Pinggera, M. Weidlich, S. Zugal, D. Fahland,
B. Weber, J. Mendling, G. Poels, Tying Process Model Quality to the Modeling Process:
The Impact of Structuring, Movement, and Speed, Proc. BPM '12, LNCS 7481,
Springer, 2012, p. 33-48.
• J. Claes, I. Vanderfeesten, J. Pinggera, H.A. Reijers, B. Weber, G. Poels, Visualizing the
Process of Process Modeling with PPMCharts, Proc. BPM '12 Workshops, LNBIP 132,
Springer, 2012, p. 744-755.
• J. Claes, F. Gailly, G. Poels, Cognitive Aspects of Structured Process Modeling, Proc.
CAiSE '13 Workshops, LNBIP 148, Springer, p. 168-173, 2013.
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FACULTY OF ECONOMICS AND BUSINESS ADMINISTRATION
www.janclaes.info
Thanks for your attention!
Do you have any questions?
Jan Claes
jan.claes@ugent.be
http://www.janclaes.info
Twitter: @janclaesbelgium
Editor's Notes
Moody, D. L. (2009). The “Physics” of Notations: Toward a Scientific Basis for Constructing Visual Notations in Software Engineering. Software Engineering, IEEE Transactions on, 35(6), 756–779.
Moody, D. L. (2009). The “Physics” of Notations: Toward a Scientific Basis for Constructing Visual Notations in Software Engineering. Software Engineering, IEEE Transactions on, 35(6), 756–779.
WMC capacity: Miller, G. A. (1956). The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychological Review, 63(2), 81–97.
CLT: Sweller, J., Van Merriënboer, J. J. G., & Paas, F. G. W. C. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296.
CFT: Vessey, I., & Galletta, D. (1991). Cognitive Fit: An Empirical Study of Information Acquisition. Information Systems Research, 2(1), 63–84.