Hci 1

• Cognition


  The process through which we become acquainted with things, or we gain knowledge
• Aspects of cognition


  • Understanding
  • Remembering
  • Reasoning
  • Attending
  • Being aware
  • Acquiring skills
  • Creating new ideas
• Objective of HCI


  Understand and represent how humans interact with computers in terms of how knowledge is transmitted between the two
• Human Information Processing (1960s and 1970s)

  • Humans represented as information processors: everything that is sensed (sight, hearing, smelling, touch, taste) was considered to be information which the mind processes
  • The information entered and exists the mind through a series of ordered processing stages
• Extended stages of the Information Processing Model

  1. Input or Stimuli

  2. Attention

  3. Encoding

  4. Memory

  5. Comparison

  6. Response Selection

  7. Response Execution

  8. Output of response
• Sensory Stores


  Info from outside registered by modality-specific sensory stores (different stores for visual, auditory, and tactile material)
• Short-term memory (also called Working memory)


  Working area where information is held temporarily for another processing activity like handling inputs, selecting, retrieving, storing, planning and preparing outputs. Limited capacity: 7+-2 chunks of information
• Long-term memory


  Information entering long-term memory assumed to be permanent
• Computational approaches to cognition

  • Information Processing model
  • Connectionist approaches (neural networks / parallel distributed processing): Brain metaphor where cognition is represented at the level of neural networks of interconnected nodes
• Types of knowledge representation

  • Analogical Representations
  • Propositional representations
  • Distributed representations
• Analogical representations


  Picture-like images (e,g, picture of an apple)
• Propositional representations


  Abstract and language-like statements that make assertions (e.g. the book is on the table)
• Distributed representations


  Networks of nodes where knowledge is implicit in the connections between the nodes
• Knowledge representation approaches


  • Semantic networks: nodes and links. Nodes represent objects (e.g. cat, dog, horse, or classes of objects e.g. animals). Links correspond to relationships between the objects (e.g. a cat is an animal; or dog can bite)
  • Schemata: Schema is a network of general knowledge based on previous experience. Functions to facilitate our understanding of commonplace events so we can behave in a certain way in different situations

  
• Schema example


  • Restaurant Script
• Mental models


  Alternative to schema. Dynamically constructed – creations of the moment -by activating stored schemata. Representations of the surrounding world, the relationships between its various parts and a person's intuitive perception about their own acts and their consequences. Can help shape behavior and set an approach to solving problems
• Mental models are either analogical representations or a combination of analogical and propositional representations
• Mental models are distinct from, but related to images
• Mental models can be thought of as 'the relative position of a set of objects in an analogical manner that parallels the structure of the state of objects in the world
• Mental models are constructed when we need to make an inference or a prediction about a particular state of affairs
• Mental models are incomplete and constantly evolving. They are usually not accurate representations of a phenomenon; they typically contain errors and contradictions. They are parsimonious and provide simplified explanations of complex phenomena