Training Design for Complex Learning Jeroen van Merriënboer Open University of the Netherlands

contents complex learning outline of the 4C/ID-model conclusions

1 complex learning diagnosing X-ray pictures engineering software maintaining aircraft analyzing policies based on simulation models diagnosing faults in chemical plants designing electronic circuits controlling air traffic operating complex pieces of medical equipment analyzing statistical data examining patent applications

some characteristics constituent skills goal-directedness simultaneous learning processes lengthy and effortful process

constituent skills Performing substantive examination Issuing the communication or vote (including B09) Re-examining the application Examination of amendments Discussions with applicant Writing further communication or refusal Examining patent applications Preparing the search report Analyze applications Determine main features of invention Classify application Determine invention described/ inventive concept Determine invention claimed Lack of unity? Perform the search Determine search strategy Use search tools Evaluate search results Write B09 (pre-examination result) Determine claimed subject-matter Novelty/ inventive step? Other EPC requirements? Compare documents with invention Select relevant documents co-ordination integration

goal-directedness knowledge-based (controlled) problem solving in its rudimentary form working backward schema-based (controlled) knowledge of subgoals controls behavior finding means for reaching subgoals skill-based (automatic) routine working forward

simultaneous learning processes schema construction leads to the development of schema-based behaviors non-recurrent constituent skills rule-/schema automation leads to the development of skill-based behaviors recurrent constituent skills

lengthy & effortful process at least 100 hours to reach basic level of proficiency may take thousands of hours of practice to become a “real” expert learners have to invest large amounts of effort in acquiring the skill cognitive capacity constraints

2 outline of 4C/ID-model working on realistic learning tasks in (simulated) task environments learning tasks complex learning outcomes; competencies simultaneous, integrated process of schema construction rule automation [attitude formation] cases projects problems transfer!

4 components learning tasks backbone of training program supportive information JIT-information part-task practice

component 1: learning tasks (whole-task practice) schema construction strategic knowledge (how-to-approach) mental models (how-it-works) rule automation (to some degree......)

Task classes higher complexity for each new task class diminishing support within a task class

component 2: supportive information systematic approaches to problem solving modeling examples help to develop strategic knowledge conceptual/theoretical/physical models case studies help to develop mental models

component 3: JIT-information for “recurrent” aspects of learning tasks present precisely when necessary

component 4: part-task practice repetition JIT-info cognitive context

analysis analyse non- recurrent aspects analyze recurrent aspects identify rules identify prerequisite knowledge identify cognitive strategies identify mental models describe the complex skill sequence skill clusters and/or task classes 1234

3 conclusions learning tasks backbone of training program new developments pre-authoring system (EC-funded ADAPTit project) media-specific extensions of the model questions & discussion