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BPM Cluster Meeting 2018

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Slides of my presentation at BPM Cluster meeting, 13 April 2018, Eindhoven, NL

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BPM Cluster Meeting 2018

  1. 1. 1/23 | www.janclaes.info An overview of my previous work and future plans FROM differentiated process modeling TO differentiated problem solving
  2. 2. 2/23 | www.janclaes.info An overview of my previous work and future plans FROM differentiated process modeling TO differentiated problem solving GOAL Present my PhD research ★ Inductive, curiosity-driven ★ ★ Stepwise methodology ★ ★ Publishable ★
  3. 3. 3/23 | www.janclaes.info 1. Collecting observations Properties of Modeler GIVEN TASK Properties of Model Properties of Modeling Process
  4. 4. 4/23 | www.janclaes.info 1. Collecting observations 2010 Eindhoven 102 master students 2011 Eindhoven 14 practitioners 2012 Eindhoven 18 master students 2013 Gent 146 master students 2014 Eindhoven 119 master students 2015 Gent 146 master students DESCRIPTIVE THEORY
  5. 5. 5/23 | www.janclaes.info 2. Data analysis – analysis instrument  PPMChart  CREATE_ACTIVITY  CREATE_START_EVENT  CREATE_END_EVENT  CREATE_AND  CREATE_XOR  CREATE_EDGE  MOVE_ACTIVITY  MOVE_START_EVENT  MOVE_END_EVENT  MOVE_AND  MOVE_XOR  DELETE_ACTIVITY DELETE_START_EVENT  DELETE-END_EVENT  DELETE_AND  DELETE_XOR  DELETE_EDGE  NAME_ACTIVITY  RENAME_ACTIVITY  NAME_EDGE  RENAME_EDGE time modelelements RESEARCH INSTRUMENT
  6. 6. 6/23 | www.janclaes.info Fast modelingSlow modelingInitial delayMany pauzesFew elementsMany elements No (separate) lay-outing Quick lay-outingDedicated lay-outing phase Continuous lay-outingUnpaired event creation Paired event creation No pauzes Serialization Paired gateway creation Delayed edge creation Chunked modeling 2. Data analysis – observations and impressions Based on dataset of 357 unique modeling executions
  7. 7. 7/23 | www.janclaes.info 2. Data analysis – observations and impressions Combined Flow-oriented Aspect-oriented Undirected Based on dataset of 118 unique modeling executions
  8. 8. 8/23 | www.janclaes.info 2. Data analysis – observations and impressions Combined Flow-oriented Aspect-oriented Undirected Based on dataset of 118 unique modeling executions WHY?
  9. 9. 9/23 | www.janclaes.info 3. Theory building Cognitive Load Theory (CLT)  Overload causes..  .. to stop learning  .. to become slower  .. to make cognitive mistakes Normal load Overload Cognitive Fit Theory (CFT)  Lower extraneous load by..  .. adapting learning/problem solving material to task  .. adapting learning/problem solving material to user
  10. 10. 10/23 | www.janclaes.info 3. Theory building Extended Cognitive Fit Theory (ECFT)  Lower intrinsic load by..  .. adapting problem solving strategy to user  .. adapting problem solving strategy to task Cognitive Fit Theory (CFT)  Lower extraneous load by..  .. adapting learning/problem solving material to task  .. adapting learning/problem solving material to user
  11. 11. 11/23 | www.janclaes.info 3. Theory building Structured Process Modeling Theory (SPMT)  Lower intrinsic load by..  .. adapting process modeling strategy to user  (.. adapting process modeling strategy to task) 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 EXPLANATORY THEORY
  12. 12. 12/23 | www.janclaes.info 4. Method development Development of a digital one-hour treatment Structured Process Modeling Method (SPMM)  Measure cognitive variables  Select fitting strategy  Explain and train strategy (=treatment)  Apply strategy PRESCRIPTIVE THEORY METHOD
  13. 13. 13/23 | www.janclaes.info 4. Method development  Results  10-15%* of variation in quality..  30%* of variation in modeling time..  60%* of variation in modeling effort.. .. could be explained by only 8 variables from our theory These are:  Serialization degree, structuredness, and fit  Learning style, field dependency, and need for structure  Interaction effects with time and effort R2 values of linear regression models with p-values below 0.05
  14. 14. 14/23 | www.janclaes.info An overview of my previous work and future plans FROM differentiated process modeling TO differentiated problem solving GOAL Get feedback on my plans ★ FWO postdoc ★ ★ ERC research group ★
  15. 15. 15/23 | www.janclaes.info Research proposals  Generalization to problem solving  Extended Cognitive Fit Theory (ECFT) • Fit between problem solving and user • Fit between problem solving and task  Differentiated problem solving • Descriptive + explanatory + prescriptive • Theory + method • For programming, writing, composing • And problem solving in general (=ECFT)
  16. 16. 16/23 | www.janclaes.info working memory 1. Motivation  Cognitive Load Theory  3 types of load can overload working memory  Criticism about and adaptation of Cognitive Load Theory, while it has proven explanatory power sensory memory long-term memory extraneous load intrinsic load germane load problem
  17. 17. 17/23 | www.janclaes.info 1. Motivation USER sensory memory working memory long-term memory capacity extraneous load intrinsic load germane load PROBLEM STRATEGY complexity serialization preferences & skills FIT FIT FIT DATA STEPS expertise experience
  18. 18. 18/23 | www.janclaes.info 2. Research gap  Effects of fit ask for differentiation  Research is giving up on differentiation where it is clearly relevant for the future  Cognitive Psychology has strong focus on learning  Differentiation in learning is difficult to study  difficulty to measure types of load  difficulty to measure end results of learning  role of ‘challenge’ in learning  The focus on learning is too complex  intangible end results, long term  Lack of process orientation  variable values evolve during the process
  19. 19. 19/23 | www.janclaes.info 2. Research gap  Shift the focus to problem solving  tangible end results, short term (source: Google Scholar) Learning (keywords: learning, learner, teaching, teacher, student, studying, material, lecture, course, lesson, instruction) Problem solving (keywords: problem solving, task, solution) Adaptive (keywords: adaptive, behavior, performance) 56.79233.208 Differentiated (keywords: differentiated, cognitive profile, cognitive style, learning style, holist or serialist, field dependent, field dependency) 1.477229
  20. 20. 20/23 | www.janclaes.info 3. Proposed solution  Study differentiated problem solving  Width a broad scope  Different (types of) users, problems and strategies  But not too broad  Scope of individual complex design problems  High risk  It’s all about balance!  High gain  Breakthrough in cognitive differentiation research  Crossover opportunities between domains
  21. 21. 21/23 | www.janclaes.info 3. Proposed solutions  Overview of problem domains ENGINEERING PROBLEM MANAGEMENT PROBLEM PRESENTATION PROBLEM ARTISTIC ‘PROBLEM’ Notion of flow* programming business process modeling report writing composing No notion of flow* data(base) modeling tbd technical drawing painting creativestructured DOMAIN MATRIX Serialist/holist Field dependency Need for structure Cognitive complexity Cognitive flexibility Category width Ill-structured - Real life - Practitioners Well-structured - Realistic, artificial, but controlled - Students * Temporal flow, in the artefact
  22. 22. 22/23 | www.janclaes.info 3. Proposed solution  With a versatile and generalist P.I. (me )  Data-driven process improvement expert  Technically skilled (programming, experimenting, data/process mining, statistics, visualization)  Relatively unbiased by the psychology field (again )  But capable of setting up an international research network and successful research collaborations quickly  With experience in training, coaching, and supervising  With vision (pioneering PPM research)  With top-tier publications (ESWA, DSS)  With passion
  23. 23. 23/23 | www.janclaes.info  Do you have any questions?  Do you have feedback?  Do you have ERC experience? Thanks for you attention! Jan Claes jan.claes@ugent.be www.janclaes.info

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