COM 3210, Week 6

1. COM 3210, Week 6 Making sense from prior experience

2. Topics • Types of reasoning that users engage in • Learning theories • Learning models • Conclusions for interface design

3. 1. Reasoning • Two types of reasoning: • Based on analogies • Based on metaphors

4. Analogy and Metaphor • An analogy provides an explicit, isomorphic mapping between objects of two domains • A metaphor is a looser connection that draws on similarities, but also includes dissimilarities.

5. Examples • Killing a tumor is like a general’s army attacking a fortress surrounded by mines • Your PC’s operating systems works like a desktop • whether something is an analogy or a metaphor also depends on the scope of the comparison

6. Computing metaphors • No chance for real analogies in computing • computing metaphors use real world objects in a computing environment • they provide an intuitive understanding of the computing object and initiate a process of active learning • computer metaphors are indispensable as overarching design strategies, but choose carefully

7. The desktop metaphor • Pictures of trash can Macintosh

8. The desktop metaphor • “The use of the trash can to eject a disk was present form the very beginning of the Macintosh interface. […] The original Mac had not hard disk. […] Because most users typically would switch back and forth between several diskettes during a session, it was deemed appropriate for the Mac to keep a memory image of the list of files of the various disks, regardless whether or not the diskette was actually inserted in the drive. […] Often, during the course of a session, the user would finish using a particular diskette, […] To reclaim vluable space, the now unwanted list of files represented by the grayed-out icon could bethrown away by dragging it into the trash…” Tom Erickson, Apple

9. 2. Learning Theories • Major groups: • behaviorist theories • constructivist theories

10. Behaviorist theories • Learning as changes of observable external behavior • Stimulus - response, selective reinforcement • habits • Prominent Behaviorist: Skinner • Learning as a reactive process

11. Constructivist theories • Learning as constructing meaning in one’s mind • building of conceptual structures through reflection and abstraction • not directly observable • requires self regulation • learning as an active process • Piaget, Gestalt

12. Constructivist approaches • Perception • Organization • Decision making • Problem solving • Attention • Memory

13. 3. Some practical learning models • concept formation • learning by exploration • learning by explanation • learning by imitation • learning by chunking • proceduralization

14. Concept formation • Common response to a class of stimuli • discrimination of distinctive features of objects • conjunctive: Car - 4 wheels and engine • disjunctive: meazels - one or several of the following symptoms: • relational: rectangle - four sided object with the two opposite sides of the same length

15. Concept formation • Users acquire new concepts and refine them • e.g. Children learn about dogs and cats • first concept: animals have four legs (humans have two) • refinement: birds are animals and have only two legs.

16. Concept formation • What kind of concept does a computer user need to learn? • How can designers support concept formation

17. Learning by experimentation • Learning as an active process • exploration and experimentation: “Learning by doing” • experiential learning theory (Gibbs 1988): Concrete experience Active experimentation Reflective observation Abstract conceptualization

18. Learning by experimentation • How can designers facilitate this kind of learning? • Restricted functionality at first • training wheels • feedback • safety nets • ‘undo’

19. Explanation-based learning • general ideas and supporting facts such that the learning can see the relationship between them • e.g. lectures • mental models • What are sources of explanation for computer users? • What makes a good explanation?

20. Minimalist instruction • people rather learn by experimentation than by explanation • explanation i.e. instruction should support that • instruction should be as little as possible, but as much as necessary

21. Minimalist instruction • Focus on real world activities of the task domain • Choose an action oriented approach (how to do things) • emphasize error recognition and recovery • eliminate repetitions, summaries, reviews, and exercises

22. Learning by imitation • Piaget: three types of human adaptation: • Play: assimilating objects to predetermined activities regardless of the object’s attributes, e.g. using chair as horse • Simple Imitation: change behavior to be something else, e.g. using mam’s lipstick, but also dance lessons

23. Intelligent Adaptation • Assimilating aspects of the environment to the cognitive structure and • accommodating cognitive structures to the environment • guided by structures and resulting in changed structures • e.g. apprenticeship (crafts), pilot-training, nurse training, learning to drive a car

24. Immitation and intelligent adaptation • Learning to do things: skills • can start as imitation and may move on to intelligent adaptation • How can this be exploited in interface design? • How can a designer support this type of learning?

25. Learning by chunking • Forming general rules from specific instances • declarative chunking: e.g. grouping digits of a phone number. • Procedural chunking: grouping several actions into a new action, e.g. drag and drop

26. Proceduralization • From declarative to procedural knowledge • from facts to how-to-do knowledge • from knowing everything about typewriters to learning how to type • from knowing everything about windows to learning how to use it • Consistency is important, but can be harmful or annoying

27. Exercise: answer the following questions • What is the tree that grows from an acorn? • What is the black cover garment that one wraps around one self? • What sound does a frog make? • “knock knock” stories are a kind of … • What’s the term to say you’ve got no money? • What’s the clear part of an egg?

28. Habit intrusion • Users tend to behave in habitual ways • even if it is not appropriate • How can designers incorporate habitual behaviour?

29. 4. Design principles for learnability (Dix) • Predictability - help users predict future actions • Synthesizability - help user asses effects of past action • Familiarity - help users to apply past knowledge • Generalizeability - help users to extend knowledge • Consistency - similar behavior in similar situations

30. Summary week 6 • Reasoning by analogy and by metaphor • Models of learning: • concept formation • experimentation • explanation • imitation and intelligent adaptation • chunking • proceduralization

31. Further reading • Preece, J. et al. (1994) Human Computer Interaction • Eberts, R. (1994) User Interface Design • Dix et al. (1998) Human Computer Interaction • Carroll, J. (1990) The Nurnberg Funnel MIT Press • Carroll, J. (1998) Minimalism: Beyond the Nurnberg Funnel MIT Press • Huthicns, E. (1995) Cognition in the Wild. MIT Press • Gibbs, G. (1988) Learning by Doing