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 facilityHarrisburg

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