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

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Notes on Guindon – "Designing the Design Process"

Reviewer: William C. Wake, 9-16-94. (Published on xp123.com April, 1999.)

"Designing the Design Process: Exploiting Opportunistic Thoughts", by Raymonde Guindon. Human-Computer Interaction, 1990, V5, pp. 305-344.

From Guindon’s abstract:

"This study shows that top-down decomposition is problematic in the early stages of design. Instead, an opportunistic decomposition is better suited to handle the ill-structuredness of design problems. …"

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

Specification of Requirements

  • Informal
  • Incomplete
  • Ambiguous
 ==> transforms to ==> High-level design

  • Notation
  • Refined requirements
  • Software subsystems

 

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

  Unbalanced Balanced
Solution Development
  • Drifting
  • Immediate recognitions of solution in other part of problem
  • Simulating scenarios
  • Immediate solution for inferred requirement
  • Design schema
  • Design method or notation
  • Solution schema
  • Design heuristics
Solution Evaluation If solution unbalanced
  • Test cases
  • Systematic requirements review
  • If solution balanced
Requirements Inferences and additions
  • Systematic strategy
  • Simulating scenarios

 

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?