Interface Seams: Notes on Guindon – “Designing the Design Process”

Abstract

• Top-down decomposition is problematic…
• Opportunistic decomposition is better suited…
• … interleaving decisions at various levels…
• Verbal protocols…
• … causes of opportunistic design
• A top-down decomposition… a special case
• Two cognitive models
• Implications

This Study Shows…

… the design process frequently deviates from a top-down approach. But more importantly, it shows that these deviations are not noise or special cases resulting from bad design habits or performance breakdowns. Rather, they are a natural consequence of the ill-structuredness of problems in the early stages of design.
 
 

Deviations Occur When…

• Artifact is new to designer
• Integration of multiple knowledge sources
• Subproblems appeared
• • critical,
  • very different, or
  • had an immediately known solution

Early Design

Design Problems are Ill-Structured

Simon (1973)

• Incomplete and ambigous specification of goals
• No pre-determined solution path
• The need for integration of multiple knowledge domains

Evidence for Prescriptive Design Models

• Jeffries et al ’81: Two novices, four experts. Showed some deviations form top-down design.
• Adelson and Soloway, ’84, ’85: Two novices, three experts. Expert designs were systematic and unbalanced. Designs are unbalanced when a mental model exists.
• Kant and Newell ’84: Two PhD students. Problem-solving and refinement.
• Parnas and Clements, Mills, Dijkstra, …

Design Decomposition is Opportunistic

• Data-driven rules (not goal-driven)
• Opportunistic planning
• • "Blackboard architecture"
  • Take immediate advantage of discoveries
• Occasional performance breakdowns (e.g., memory limitations)

Categorization Rules

The Lift Problem

N elevators for M floors

"Ecologically valid"
 

Method

• 8 protocols ==> 3 in depth ==> 2 reported
• "Prototypical" style
• Styles guided by
• • Software design method,
  • Past experience, or
  • Programming paradigm

Analysis

• Videotape and transcript reviewed by 4 researchers: brainstorming
• Prompted review session with participant
• Iterative development of analysis scheme (Templates: activity and level)
• In-depth analysis

Causes of Opportunistic Design Decomposition

• Sudden discovery of unbalanced partial solutions
• • Partial solution from rest of problem
  • Simulation bug
  • Low-level solution before decomposition
  • Data-triggered rules
• Immediate solution development for new requirements (60% of new requirements solved immediately)
• Drifting
• • Follow train of thought; little cognitive cost
  • Partial solutions may provide critical insights
• Solution development by problem domain scenarios: Triggered recognition of unbalanced solution or new requirements

Differences between Designers

• Specialized design schema
• Designer 2 schema allowed straightforward decomposition
• Frequent and varied deviations

Different Psychological Models (Caricatured)

• Anderson: top-down design process with hierarchical goal structures
• Hayes-Roth: Flexible and easily re-organizable goal structures and online planning.
• "…very difficult to demonstrate empirically the validity of one psychological model against another."
• Could embody both, and compare.

Implications for Training, Methods, and Environments

• "…until the proper design decomposition… the design process should be opportunistic"
• Don’t force a strict order of activites
• Allow rapid shifts between tools for objects and their representations
• Allow easy navigation between objects, but support an agenda

More Implications

• Representations should have smooth progression from informal to formal
• Easy editing and reorganization
• Requirements traceability
• Representation of interim and partial design objects

Critique

• 4 studies, 15 subjects
• Strict top-down decomposition is a strawman
• "Drifting" == end-to-end tracing
• Hidden agenda for environments (?)
• Environment sounds like Fischer’s CPS
• Wrong question?