Conceptual Overview of HCI and Interaction Design

A study guide, by Zach Tomaszewski

for ICS 699, Fall 2006, directed by Dr. Dan Suthers


Scope of HCI has historically progressed from ergonomics (70s), to considering human cognition and psychology (80s), to effects of/on workflow and communication (90s), to effects on culture and society. These various aspects of HCI can be broken down in the following ways:

This overview sketch was built from:


Cognition involves: attention, perception/recognition, memory, learning, communicating (listening, reading, speaking), problem-solving (planning, reasoning, problem-solving).

Frameworks for exploring cognition

Norman (including 7 Stages of Action)
People form mental models (of a system)
Able to mentally simulate its operations to make predictions. [See Interaction.]
People are information processors

Foundation for: GOMS (Goals, Operators, Methods, Selection)

External Cognition
Parallel/Neural Processing
Connectionist/neuron-based theory of cognition.
Distributed Cognition
Whole system as an Info Processor. [See Collaboration.)

Collaboration & Communication


Coordination (of behavior)


Language as Action (Speech Act, Conversation for Action, etc.)
Seeing conversations/statements as: assertives, commissives, declarations, directives, expressives.
Distributed Cognition
Info propagated through system in various representational forms, through conversation and coordination.
Common Ground Theory (Contribution Theory)
Communication is not just info transfer (except perhaps at very low-level with standardized vocabulary). Need to negotiate meaning, or at least shared understanding. Proposition is common ground if all involved know it and know that all involved also know it. Start with conversational rules and other communal common ground. Rest of common ground developed through conversation in shared context. Grounding constraints/resources.

Affect and Emotion

Designs may strive to:

Convey or elicit (positive) emotions
Can use icons/animation to express emotion; pleasing aesthetics; helpful interface agents; emoticons (for expression of emotion through CMC).
Avoid (negative) emotions, particularly frustration
Often frustrated by poor usability. Also: In general: good/clear design, helpful feedback/useful error messages, and contextual/relevant help all help alleviate frustration.

May also use emotion through an anthropomorphic agent.

Also, affective computing--building systems to either exhibit or recognize (thru methods: predictive; real-time (physiological, gesture, facial expression, speech, etc); retrospective (user-reported)) emotion. Various levels possible (arousal/avoidance vs. specific emotion).


Important aspects of product (for sales): aesthetics/appearance, price/cost, maintainability, number of features, prestige, usability.

efficiency, effectiveness, safety, utility (to user), learnability, memorability.
User experience
satisfying, enjoyable, fun, entertaining, helpful, motivating, aesthetically pleasing, supportive of creativity, rewarding. (Some of these may actually conflict with usability--as in making a game challenging.)
Interaction modes
instructing/commands; conversing/agent; manipulating (and navigating); exploring/browsing (information).
Interaction system paradigms
WIMP/windows, ubiquitous computing, etc. [General platform for intended system.]
Mental Model
Norman: Users form a mental model of the system. In perfect world, Gulfs of Execution and Evaluation between user and system are bridged.
Ergonomic/Motor Details

Interaction Design

Four basic steps:

Three focuses:

Life Cycle models

As laid out above: ID needs, design, build alternative prototypes, evaluate
linear progression from requirements to testing; from software engineering
Boehm's Spiral model
spiral to reduce risks [of design commitment]
Rapid Applications Development
time-boxing into smaller projects; high user involvement in requirements stage
Star model
from HCI, constantly return to evaluation
Usability engineering

Some Specific Design Approaches

Scenario-based Design (Rosson & Carroll)
Uses narrative scenarios so design artifacts are more approachable by non-designer stakeholders. Problem scenario (what a specific user does right now) -> activity scenario (how they could do it in abstract) -> information and interaction scenarios (what interaction and info needed to achieve activity) -> scenario machines (narrow, deep prototypes).
Usage-centered Design (Constantine and Lockwood)
Focused on the tasks/use. User roles (relations to system) and tasks they engage in -> essential use cases -> contexts (combining different use cases into info and operators with fewest different contexts) -> abstract interface.

Needs and Requirements

Determining user needs and translating them into system requirements.

Data gathering
Data interpretation/analysis
Different techniques to capture the discovered user needs:

Design and Prototyping


User-Centered Design
Conceptual design [System designer's model]
Frameworks/aspects to consider Expanding this:
Physical design [System image]


Aids discussion with stakeholders, design team, and in testing during design iteration. May be evolutionary prototyping (becomes system) or throw-away prototypes.

Low Fidelity.
Cheap and quick. Doesn't look like finished product. Include: storyboards of use; sketches of interfaces; index card walk-throughs; wizard of Oz software.
High Fidelity
Expensive, more time consuming. Users can get sidetracked by superficial details and bugs; but closer to actual system, so may be easier to visualize and understand. Includes: horizontal (wide range of functions in low detail) or vertical (can complete one task all the way through)


Evaluation Paradigms: quick and dirty (fast, informal data); usability testing (carefully controlled); field studies (situated in natural conditions); predictive (actual users not required).

Preparation for Evaluation
Preece et al's DECIDE framework: goals for testing; operationalize as specific questions to answer; choose testing paradigm/techniques; identify practical issues (time, money, scheduling, expertise in testing); handle ethical questions (consent, user compensation, etc.); evaluate data (reliability, validity, etc.); do pilot study first.
Observing Users
Asking Users
Testing Users
Modeling users: Experts and Predictive models.
Inspections of design by an expert evaluator, rather than a user.