ITM 734 Introduction to Human Factors in Information Systems Cindy Corritore This material has been developed by Georgia Tech HCI faculty, and continues to evolve. Human Abilities: Cognitive Abilities

ITM 734 (Corritore)2 Basic Human Capabilities Do not change very rapidly  Not like Moore’s law! Have limits, which are important to understand Our understanding of human capabilities does change, ie  Cognitive neuroscience  Theories of color perception  Effect of groups and situation on how we act and react

ITM 734 (Corritore)3 The “Model Human Processor” A true classic - see Card, Moran and Newell, The Psychology of Human- Computer Interaction, Erlbaum, 1983  Microprocessor–human analog using results from experimental psychology  Provides a view of the human that fits much experimental data

ITM 734 (Corritore)4 Block Diagram - Model Human Processor (MHP) LONG-TERM MEMORY SHORT-TERM (WORKING) MEMORY AUDITORY IMAGE STORE VISUAL IMAGE STORE PERCEPTUAL PROCESSOR COGNITIVE PROCESSOR MOTOR PROCESSOR

ITM 734 (Corritore)5 MHP is not Complete Only two senses  Certainly the most important Focus is on a single user interacting with some entity (computer, environment, tool)  Neglects effect of other people

ITM 734 (Corritore)6 Three Processors Perceptual Processor Cognitive Processor Motor Processor Each has a cycle time (average and range), determined experimentally  Represented by C

ITM 734 (Corritore)7 Block Diagram - MHP – Three Processors, Cycle Times LONG-TERM MEMORY SHORT-TERM (WORKING) MEMORY AUDITORY IMAGE STORE VISUAL IMAGE STORE C = Cycle Time [Range] PERCEPTUAL PROCESSOR C = 100 [5-200] ms COGNITIVE PROCESSOR C = 70 [27-170] ms MOTOR PROCESSOR C = 70 [30-100] MS Eye movement (Saccade) = 230 [70-700] ms

ITM 734 (Corritore)8 Through all of this …. limited cognitive resources/load (memory load)  analogy  flawed plans (heuristics)  simulations (cognitive/mental models) goal – to minimize complexity through improved fit (between user, computer, and task)

ITM 734 (Corritore)9 Block Diagram – MHP – Three Memories LONG-TERM MEMORY SHORT-TERM (WORKING) MEMORY AUDITORY IMAGE STORE VISUAL IMAGE STORE PERCEPTUAL PROCESSOR COGNITIVE PROCESSOR MOTOR PROCESSOR Memory 1 - Perceptual Buffers to briefly store impressions Memory 2 - working memory, small capacity, conscious thought, calculations Memory 3 - permanent memory, hugh capacity

ITM 734 (Corritore)10 Block Diagram – MHP – Three Memories, Rep’n, Decay Time, Size LONG-TERM MEMORY SHORT-TERM (WORKING) MEMORY AUDITORY IMAGE STORE VISUAL IMAGE STORE R = Acoustic D = 1.5 [ ] s S = 5 [ ] letters R = Visual D = 200 [ ] ms S = 17 [7-17] letters R= Acoustic or Visual D (1 chunk) = 73 [73-226] s D (3 chunks) = 7 [5-34] s S = 7 [5-9] chunks R = Representation D = Decay Time S = Size C = Cycle Time [Range] PERCEPTUAL PROCESSOR C = 100 [5-200] ms COGNITIVE PROCESSOR C = 70 [27-170] ms MOTOR PROCESSOR C = 70 [30-100] MS Eye movement (Saccade) = 230 [70-700] ms R = Semantic + Visual + Auditory D = Infinite S = Infinite

ITM 734 (Corritore)11 Memory 1 – Perceptual Stores (sensory memory) Memory structures  Image Stores - Holds fixed image of outside world long enough for some analysis Processes - Info goes to brain for more processing  e.g. Pattern recognition  Uses context & knowledge to make sense of what is seen/heard

ITM 734 (Corritore)12 Perceptual Stores Visual and auditory impressions  Visuospatial sketchpad, phonological loop Very brief, but accurate representation of what was perceived  Details decay quickly ( ms visual; sec auditory)  Limited capacity ( letters visual; auditory)

ITM 734 (Corritore)13 Perceptual stores buffers for incoming data via senses different one for each sense short-lived and space-constrained persistence (fireworks in vision after the fact) some processing even if not attended attention brings it into STM  cocktail party phenomenae

ITM 734 (Corritore)14 Memory 2 – Short Term Memory STM Representation is either auditory or visual Rehearsal needed to prevent decay (try it)  Without rehearsal, decays in minute or less  Can store as long as are able to pay attention to rehearsal – harder than you think (try it) –Another task prevents rehearsal - interference –New info can “push out” old info - interference Capacity is 5 to 9 “chunks” of information

ITM 734 (Corritore)15 About Chunks A chunk is a meaningful grouping of information – allows assistance from LTM vs NSAFBICIANASA vs. NSA FBI CIA NASA My chunk may not be your chunk  User and task dependent

ITM 734 (Corritore)16 STM gateway to sensory and LTM?  no – conversation goes directly to LTM role of rehearsal exaggerated (moving from STM to LTM)  lots in LTM that is not rehearsed (eg. snapshot of a birthday celebration)

ITM 734 (Corritore)17 STM characteristics recency - last few items in list recalled better than middle - holding most recent items in STM  negate with interference?  visual and auditory channel - no interference if different channel primacy - first few items in list recalled better than middle (more rehearsal)

ITM 734 (Corritore)18 STM characteristics quick access and quick decay (volatile) limited in size  chunking (experts vs. novices) - phone number – forgetting  time decay?  interference with new items? (eg. similarity)  attention moves off item?

ITM 734 (Corritore)19 Memory 3 – Long-Term Memory LTM Seemingly permanent & unlimited Slow but variable access speed Access is harder, slower  -> Activity helps (we have a cache) Representations are semantic (declarative, procedural) and visual and auditory  Facts, procedures, pictures, sounds Retrieval depends on network of semantic associations (“linked lists”) File system full

ITM 734 (Corritore)20 LTM characteristics Retrieval depends on ….  recency  expectations  similarity of information  connectedness  rehearsal  richness & nature of processing at learning –level or depth or processing (shallow vs deep perceptual analysis) –distinctiveness of processing –amount of processing elaborate far better

ITM 734 (Corritore)21 Richness paragraph – listen and remember …..

ITM 734 (Corritore)22 Types of LTM Explicit and Implicit  conscious recollection, top-down retrieval from multiple systems with massive integration (E)  unconscious recollection, bottom-up from single system (I) – more automatic

ITM 734 (Corritore)23 Types of LTM Episodic and Semantic  episodic: self-awareness component, things that happen to you, complex (E)  semantic: stuff we know, knowledge about the world, relationships, implicit - dictionary, thesaurus likely stored the same way

ITM 734 (Corritore)24 Types of LTM Declarative and Procedural  knowing that, explicit primarily, relationships, integration of information (D) – knowing things and their relationships  knowing how, mostly implicit, not relational – how to do things

ITM 734 (Corritore)25 Memory structures for stories, events … Schema - framework that includes frames & scripts  become chunks for expanding memory  basis for expectations Bartlett’s Schema Theory  framework for stories that affects comprehension  told American Indian stories, then recall - – readjusted story elements and themes to fit their model Chunking in experts Helps make it easier to recall, group information Experts have great, robust schema and chunks

ITM 734 (Corritore)26 LTM processes Storage  rehearsal Retrieval  Forgetting  Recognition vs recall  Frequency and recency effects

ITM 734 (Corritore)27 Storage- Rehearsal Memorization involves storing the information and one or more access paths Good memories are rich semantic networks with many (unique) access paths Learning is aided by meaningfulness, structure, familiarity and concreteness Active memorizing requires effort, motivation Passive memorizing - unpredictable, often episodic, context sensitive Similar items interfere if they are not separated during memorizing - learning transfer effects - old interfere with new; new overwrite old

ITM 734 (Corritore)28 Facilitating Memorization Structure information to help chunking - use categories, ordering, associations Encourage reasoning during memorizing - active memory Help access by multiple pathways - memorizing tricks e.g. keywords, cognitive aids, mnemonics, link to image memory (rooms) Make associations clear and keep them consistent

ITM 734 (Corritore)29 Facilitating Memorization Make separate and recognizable contexts for recall - important for script / skill memory Increase depth of encoding  Richness  Visualization –sorting - demo.html demo.html  Uniqueness  Interaction Recognition vs Recall

ITM 734 (Corritore)30 Facilitating Memorization: Mnemonics cognitive mnemonics  ABC’s with tune  on old olympus mountain tops a finn and german viewed some hops (12 crainial nerves: OOOMTAFAGVSH) – seems to be more to remember?

ITM 734 (Corritore)31 Facilitating Memorization: Mnemonics check out: factors.arc.nasa.gov/cognition/tutorials/index.html mnemonic for Norman principles: visibility, feedback, cognitive/conceptual model, affordance, mapping My Fat Cat Ate Veggies

ITM 734 (Corritore)32 Recall vs. recognition Knowledge in the World Theory is GUI’s - Alan Kay developed in 1960’s  Steve Jobs in late 1970’s from Xerox Parc  keep knowledge in world to supplement head knowledge  recall vs. recognition  remember just enough detail to get by – exceptions rather then norms  experts not expert in knowledge in the head as much as expert in how to locate needed knowledge in the world (Norman Ch 2)

ITM 734 (Corritore)33 Design implications Reduce cognitive load!!!

ITM 734 (Corritore)34 Design implications Mental models natural extensions of schema - support schemas  metaphors - desktop/office  match system information structure with familiar memory structures so user can use their schema

ITM 734 (Corritore)35 Design implications Design interfaces that help users ‘grow’ good mental models  meaningful and familiar command names (eg. from task world)  balance this with existing conceptual models of item names (ie. cut, copy) Incorporate closure (finish) on tasks  helps build mental model  helps identify chunks for memory when become an expert Consistency - to build mental model; don’t have to remember as much

ITM 734 (Corritore)36 Design implications Rich encoding -  multimedia  interaction  context? May just be to ‘remember your site’ or help with visualization    lking+website&creative= lking+website&creative=

ITM 734 (Corritore)37 Design implications Focus on recognition rather than recall  interface contains prompts/information  studies on computer experts found they don’t have better recall, but high recognition of what is and isn’t available on interface and where to find it (mental maps)  GUI’s combination of recognition (menu’s) and recall (quick keys)

ITM 734 (Corritore)38 Design implications Place the burden of remembering on the machine, not the human  Don’t require user memory (eg. between screens)  Don’t have computer ask for info it can derive

ITM 734 (Corritore)39 Design implications Design minor messages, alerts, warning to be minimally disruptive  prevent user from forgetting data stored in short term memory

ITM 734 (Corritore)40 Attention Humans can focus mental resources on a single event/object  helps to simplify environmental input (filter)  works with perception - perceive what attending to  can divide attention (multiprocessing, not parallel) – problem - distraction on second task, don’t return to first task in right place. often use world reminders to hold place in first task (post-it note)

ITM 734 (Corritore)41 Attention examples  driving a car -must attend to some stimuli, ignore others  listening to this lecture - attend to slides and words, ignore other students, physical plant noises

ITM 734 (Corritore)42 Divided attention doing two things at once affected by  task similarity – similar how?  practice (experience) - automaticity  task difficulty – require more resources than are available? what happens: interference

ITM 734 (Corritore)43 Success in time sharing attention four mechanisms account for how well we divide our attention 1. automaticity and resources 2. resource allocation and switching 3. structural factors 4. confusion and similarity

ITM 734 (Corritore)44 1. automaticity and resources Automatic vs. Controlled : perform task without thinking about it or require attention, conscious control. Happens over time. Controlled – do something directed by thought. Automatic:  good as fast, doesn’t interfere with other tasks (need minimal attention), unconscious  bad - unavailable to conscious level, hard to change (driving a shift), can interfere with other automatic processes, harder to unlearn

ITM 734 (Corritore)45 automaticity Stroup effect – read the words on next page outloud as fast as you can …

ITM 734 (Corritore)46 Mismatch Stroop effect: name the colour: RED GREEN BLUE YELLOW BROWN PURPLE Color has not been shown empirically to be superior

ITM 734 (Corritore)47 1. automaticity and resources automatic processing can time-share efficiently  doesn't require a lot of cognitive resources –eg. walking  factor: effort and difficulty of additional tasks if task difficult, requires more resources  if have dual tasks, performance will decrease since resources are being shared  automatic tends to reduce the difficulty

ITM 734 (Corritore)48 1. automaticity and resources can only increase performance so much  level equal to ‘full’ resource use on a task, performance data limited (no further benefit from adding more resources) –perfect example: no matter how hard I try (invest resources & effort), I won't improve my understanding of a discussion in French beyond a rudimentary level. –also called resource-limited

ITM 734 (Corritore)49 1. automaticity and resources bottom line  increase effort into a task, improve performance to point if resource limited  increase difficulty of task decreases performance unless add resources  in dual tasks, if increase resources for one task, will decrease resources for second task and subsequent performance –depends on automaticity

ITM 734 (Corritore)50 2. resource allocation and switching result of two + tasks co-occuring now look at how you can allocate and switch attention between tasks  we don't have elaborate schemes to optimize resource allocation –can improve time sharing with these strategies –totally depends on the individual can train how to control attention

ITM 734 (Corritore)51 2. resource allocation and switching factors  switch cost (so tend to stay with same task even if low priority)  cognitive distance of tasks - if close, more confusion when switch (so more costly)  faster switch if salient reminders available about task (eg. you can see it vs. just remembering)

ITM 734 (Corritore)52 3. structural factors perceptual resources required, brain structures used, info processing required Bottleneck Theory- use same resources, get a bottleneck that shared tasks must wait for bottom line  amt. of interference between two tasks depend on degree to which each requires same resources (shared levels on these three dimensions)

ITM 734 (Corritore)53 4. confusion and similarity confusion: increasing the similarity of processing material decreases efficiency (too similar)  eg. mental math and spelling, Stroup effect –semantic value of word interferes with ability to report ink color what happens: responses for one task activated and interfere with second task

ITM 734 (Corritore)54 Visual attention theories how attention works  overall gestalt (salient features), focus down on objects and components  affected by experience (bananas yellow)

ITM 734 (Corritore)55 Designing for attention examine which configurations minimize task interference  voice recognition software - may interfere if user has to perform other verbal activities –best with spatial activities avoid imposing two tasks using similar materials (confusion) –entering digits while others speaking digits

ITM 734 (Corritore)56 Designing for attention what about background music?  requires spatial perception  decreased performance with lyrics and word processing examine mental workload urgent info in prominent area; less urgent to specific area(s)

ITM 734 (Corritore)57 Designing for attention Ways to focus user attention  structure information – group like things physically, with fonts, with color, spacing, lines, etc. – use same spot for same types of information  to help with distractions: system should inform you where you were in task when left – let user know position in state space  avoid unnecessary information display (KISS)  make things easy to use/move thru (so user not focused on mechanics of how to use system)

ITM 734 (Corritore)58 Designing for attention taking advantage of automatic processing: quick keys across systems  standards (like Windows 95 ^c, ^v, ^x) become automatic – problem - appears unrelated to task to most people avoid automaticity by interrupting process (eg. put a window up in middle of keystroke sequence) – good for deleting

ITM 734 (Corritore)59 Learning Two types:  Procedural – How to do something  Declarative – Facts about something Involves  Memorization  Understanding concepts & rules  Acquiring & automating motor skills –Swimming, Bike riding, Typing, Writing. Tennis –Driving to work Even when don’t want to

ITM 734 (Corritore)60 Learning Facilitated  By structure & organization  By similar knowledge, as in consistency in UI design  By analogy  If presented in incremental units  Repetition Hindered  By previous knowledge –Try moving from Mac to Windows => Consider user’s previous knowledge in your interface design

ITM 734 (Corritore)61 Observations Users focus on getting job done, not learning to effectively use system Users apply analogy even when it doesn’t apply  Or extend it too far - which is a design problem –Dragging floppy disk icon to Mac’s trash can does NOT erase the disk, it ejects disk!

ITM 734 (Corritore)62 Problem Solving Storage in LTM, then application Reasoning  Deductive - If A, then B  Inductive - Generalizing from previous cases to learn about new ones  Abductive - Reasoning from a fact to the action or state that caused it

ITM 734 (Corritore)63 Goal in UI design - Facilitate Problem Solving! How can you help the user apply these three kinds of reasoning while learning/using a UI? …..  Deductive  Inductive  Abductive

ITM 734 (Corritore)64 Reasoning about a UI Deductive: If I want to delete something, I must first select it. Facilitate by animating the disappearance of selected object Inductive: I could make text bold by selecting it and then using the Bold command. Maybe I could italicize in the same way. Facilitate by putting bold and italic commands together Abductive: Timeout on the web browser if not connected. Facilitate by telling the user why the timeout occurred

ITM 734 (Corritore)65 Observations On Learning a UI We are more heuristic than algorithmic  We try a few quick shots rather than plan –Resources simply not available We often choose suboptimal strategies for low priority problems We learn better strategies with practice

ITM 734 (Corritore)66 Implications of Observations Allow flexible shortcuts  Forcing plans will bore user Allow multiple ways of doing things  Select-cut-paste  Select-drag Provide active rather than passive help  Recognize dead ends and inefficient methods

ITM 734 (Corritore)67 Language Domain terminology - use Technical terminology - avoid We read word shapes, not letters  Unless all caps Should systems have natural language interfaces?  Stay tuned

ITM 734 (Corritore)68 People Good 1.xxx 2.yyy 3.zzz Bad 1.aaa 2.bbb 3.ccc Fill in the columns - what are people good at and what are people bad at?

ITM 734 (Corritore)69 People Good  Infinite capacity LTM  LTM duration & complexity  High-learning capability  Powerful attention mechanism  Powerful pattern recognition Bad  Limited capacity STM  Limited duration STM  Unreliable access to LTM  Error-prone processing  Slow processing

ITM 734 (Corritore)70 Evaluate these vs  Analytics can identify key areas