Learning

1. Learning Teppo Räisänen http://www.oamk.fi/~teraisan/ Teppo.raisanen@oamk.fi

2. Stimulus Treshold • Human senses are used a lot for filtering of information • E.g hearing during sleeping • Normal signals are filtered • Abnormal sounds invoke actions • If filtering would not be applied, human brains would overload with information

3. Stimulus Treshold • Signals that are observed are ones that • are interesting • are signals of danger • One can learn to filter even repetitive signals of danger (’false alarms’) • E.g alarm sounds used in Harrisburg nuclear facility

4. Attention • Filtering of signals can be either conscious or subconscious • ’Attention’ is used to refer conscious efforts • Observing faint signals can be achieved by concenrating • Weak sounds • Small visual objects

5. Attention • One’s current state of attention is largely dependent of one’s mental state • A Motivated person reacts to faint signals • Unmotivated or tired persons needs strong signals to surpass stimulus treshold • Coffee, smoke

6. Memory • Ability to use memory and recall are essential • Even most simple routines require use or memory • Memory is divided into • Long term memory • Short term memory

7. Memory • Long term memory has a immense capacity • Humans do, however, forget things • Recapitulation vs. forgetfulness • According to some theory we don’t actually forget anything • Fetching information from long term memory can be a slow process

8. Memory • Short term memory has a small capacity • Capacities are individual qualities • 7 +/- 2 rule • Some individuals may have a considerably larger capacity

9. Reasoning • Humans • gather information using their senses • filter information • learn skills and absorb information • have memory and ability to recall • In addition we need to be able to adapt to new kinds of situations

10. Reasoning • We use various problem-solving methods • Solutions of problems are based on earlier experiences and knowledge • Reasoning can be divided into • deductive reasoning • inductive reasoning • abductive reasoning

11. Deductive Reasoning • Deductive reasoning is based on premises • Observations are applied to premises, which leads to conclusions • E.g. ”During winter it’s cold outside”, ”If it is cold outside, I won’t go outside” => ”It’s winter, so I won’t go outside”

12. Deductive Reasoning • Deducive logic does not apply well in all situations • For example interpretations of concepts may vary: • What is a ’winter’? • How ’cold’ is defined?

13. Inductive Reasoning • Inductive logic is based on generalizations of individual obser-vations • E.g. ”Each of 100 elephants observed have trunks” => ”All elephants have trunks”

14. Inductive Reasoning • Inductive reasoning often leads to wrong conclusions, if fully applied • Elephant #101 may not have a trunk • Often we’ll still get results that are of accectable reliability

15. Abductive Reasoning • Abductive logic is based on cause/effect thinking • E.g. ”If one does not eat healthy food, one will become ill” => ”One is ill, therefore one has not eaten healthy food” • Users of applications often make wrong assumptions about program’s actions

16. Learning And Unlearning • Learning of skills and absorption of information have differences • Skills are learned and unlearned slowly • Information is learned and unlearned quickly • Can you think of any examples?

17. Learning And Unlearning • There are many pedagocic theories and viewpoints to learning, e.g. • Behaviorism • Cognitivism • Constructivism • Knowledge of theoretical background is very useful when designing UIs

18. Learning And Unlearning • Learnability is one of fundamental aspects of usability • UI should be as intuitive as possible • Even the most intuitive UI requires some earlier learning from the user • UIs become much more intuitive, when graphical UIs were introduced

19. Learning And Unlearning • Learning model can be formulated as • Experimentation • Feedback • Forming of conceptual model • For applications to be as learnable as possible, they should follow the same conceptual model

20. Repetition • Repetition is necessary for permanent learning results • Trough repetition we learn • phone numbers • passwords • many unnecessary things

21. Learner Types • Learning is effective if more than one senses can be used • Use of senses in learning is an individual quality: • Visual learners • Auditive learners • Kinestetic learners

22. Learner Types • According to studies most people of western cultures seem to be visual learners • Pure types are very rare • Use of senses is of course also dependent on the task of learning

23. Learner Types • There are also other kinds of categories of learners, e.g.: • holistic vs. serialistic learners • introvert vs. extrovert types • Existence of different learner types should be considered when designing any kind of product

24. Special Groups • There are also groups of individuals, which have special requirements for learning • the elderly • children • disabled persons

25. Special Groups • In future a growing part of software users will be aged persons • The problem in designing is often to find suitable persons for testing • There exists applications, which simulate environments of disabled persons

26. Learning type test • Let’s do a learning type test