hci Flashcards

(57 cards)

1
Q

State the universal design principles.
(hint: 7)

A
  1. accessible
  2. flexible
  3. simple and intuitive
  4. effective communication
  5. error tolerance
  6. low physical effort
  7. size, space for approach and use
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2
Q

State Shneiderman and Plaisant’s (2010) eight golden rules.

A
  1. consistency
  2. shortcuts
  3. feedback
  4. yield closure (confidence completeness)
  5. prevent errors
  6. easy reverse
  7. interface control
  8. minimise cognitive strain
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3
Q

What is the first wave?

A
  • engineering roots
  • problem solving
  • “technical paradigm”
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4
Q

What is the second wave?

A
  • cognitive reduction
  • information processing
  • “cognitive paradigm”
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5
Q

What is the third wave?

A
  • ubicomp tech
  • social change
  • “ethnographic paradigm”
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6
Q

What could the fourth wave be?

A
  • values, ethics and politics
  • avoiding centrality of technological notions of interactive designs
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7
Q

What are the interface differences?

A
  1. gesture
  2. haptic (vibrations)
  3. multimodal
  4. shareable
  5. shape-changing
  6. tangible (sensors)
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8
Q

What are frameworks?

A

Provides advice for designing UX. Interrelated concepts/specific questions.

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9
Q

Name the HCI conceptualised types.

A
  1. paradigm
  2. vision
  3. model
  4. framework
  5. theory
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10
Q

What is a paradigm?

A

The inspiration for a conceptual model. A generalised approach to carry out research.

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11
Q

What is a vision?

A

Imagines life in the future. Used as a driving force for research and development.

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12
Q

What is a theory?

A

An explanation for a phenomenon. Can be used to predict what users will do with new interfaces.

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13
Q

What is a model?

A

Used for predictions. A simplification of a HCI phenomenon.

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14
Q

name the five types of evaluations for collaborative techniques.

A
  1. field work
  2. interviews
  3. questionnaires
  4. observations
  5. log studies
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15
Q

What are the eight design considerations for interactive collaborative interfaces?

A
  1. conformity vs individuality pressures
  2. privacy and protection
  3. sources of friction between participants?
  4. protection from hostile, aggressive or malicious behaviour?
  5. expected and tolerable network delays?
  6. how will high-level management participate?
  7. any status rise or fall?
  8. evaluation of success?
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16
Q

What is the time/space groupware matrix?

A

________________|same time | different time
++++++++++++++++++++++++++++++++++
same place |face-to-face|continuous
++++++++++++|+++++++++++++++++++++
different place |remote |coordination
(sync) (async)

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17
Q

What is CSCW?

A
  • Computer supported cooperative work
  • a field of study
  • studies how people can work more effectively together
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18
Q

What are some features of CSCW design?

A
  • supports users needs
  • accommodates disruptions from co-workers
  • deals with privacy
  • establishes responsibility
  • can be used be a large group of users
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19
Q

What is ubicomp?

A
  • Ubiquitous computing
  • connecting computers into the everyday by shrinking and embedding
  • part of the third wave of computing
  • e.g. smart devices
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20
Q

What are the five areas of usability?

A
  1. learnability
  2. efficiency
  3. memorability
  4. errors
  5. satisfaction
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21
Q

What are the additional seven ubicomp usability areas?

A
  1. conciseness
  2. expressiveness
  3. ease
  4. transparency
  5. discoverability
  6. programmability
  7. invisibility
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22
Q

What is UCAMP?

A
  • to do with wearables
  • U: user
  • C: corporal
  • A: attention
  • M: manipulation
  • P: power
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23
Q

What are some design issues for intelligent interactive systems?

A
  1. error corrections and detections
  2. agency
  3. transparency
24
Q

What is the markov assumption?

A

The probability of a word only depends on a finite set of previous words.

25
What is the sub-word language model?
Captures valid sequences and assigns them probabilities.
26
What is the equation for self-information?
I(m) = -log2(p(m))
27
What is self-information of a message m in bits?
- Self-information ( I(m) ) quantifies how surprising a message ( m ) is, based on its probability ( p(m) ). - Rare events have high self-information (low probability). - Frequent events have low self-information (high probability).
28
What are the seven interactions by intention?
1. select 2. explore 3. reconfigure 4. encode 5. zoom/elaborate 6. filter 7. connect
29
What is the mantra said in visualisation?
1. overview first 2. zoom and filter 3. THEN details on demand
30
What is the expressiveness principle?
- visual encoding should express all the info in the dataset attributes - ordered data should look ordered and categorical data should not look ordered - ensures visualisation is accurate and truthful to the data
31
What is the effectiveness principle?
- the importance of the data attribute should be encoded with the most effective visual variable in order to be noticeable - ensures visualisation is clear and easy to interpret for the audience
32
What is iid?
- independent and identically distributed - each variable in a sequence is distributed according to the same probability distribution and all vars mutually independent
33
What do we use for model validation?
- R^2 - the coefficient of determination - 1 - (SSerror/SStotal) - closer to 1, the better the model
34
What is Occam's Razor?
Among several competing models, the simplest model that can explain the phenomenon should be preferred.
35
What are models?
- used to make predictions
36
What is overfitting?
Overfitting occurs when a model learns too much from the training data, capturing noise and specific details rather than general patterns. As a result, it performs well on training data but poorly on unseen data.
37
What are some assumptions for Fitts' Law?
1. closed-loop interaction 2. will only model biologically possible intervals 3. a and b (the regression coefficients) vary depending on the task 4. pointing devices can be compared using their throughput
38
What is throughput?
- TP = IDavg/MTavg - the above is dependent on an arbitrary ID - TP = 1/b - the above ignores a though - number of bits of information a user can communicate per second independent of a specific target
39
What is ID?
- index of difficulty - ID = log2((D+W)/W) - measure of difficulty hitting a target of a certain diameter from a certain distance
40
What is Fitts' Law?
- linear regression model - predicts that the avg Movement Time (MT) to hit a target (1D) is proportional to the distance and width of the target - MT = a + bID
41
What are the five experimental design steps?
1. setup 2. participants 3. apparatus 4. material 5. procedure
42
What is counter balancing?
presenting conditions to each group in a different order
43
What is asymmetrical skill transfer?
presenting condition A before condition B helps the performance of B more than presenting condition B before A helps the performance of A.
44
What is between-subject design? List some advs and disadvs.
- each participant exposed to one condition - adv: 1. no skill transfer 2. no need to counter balance - dis: 1. variance not controlled 2. each participant is a source of error 3. quickly becomes expensive 4. typically demands more participants
45
What is within-subject design?
- each participant exposed to all conditions - adv: 1. variance controlled 2. requires fewer participants - dis: 1. usually needs counter balancing 2. more care needed in the design 3. risk of asymmetrical design transfer
46
What is the external and internal validity trade off?
- more internal validity, less external validity - interval: to what extent is bias minimised - external: to what extent can the results be generalised to other situations and people
47
What are some threats to validity?
1. reproducibility 2. study heterogeneity 3. internal validity 4. external validity
48
What are the five interaction types?
1. instructing 2. conversing 3. manipulating 4. exploring 5. responding
49
What is the research cycle for interaction techniques?
1. identify the problem 2. identify the relevant design principles 3. propose a solution 4. evaluate said solution 5. extract design implications 6. use said design implications as new design principles 7. repeat the cycle
50
What are six issues to consider when creating new interaction techniques?
1. learning curve 2. walk-up use (can it be used right away) 3. robustness and error handling 4. intrusiveness 5. social acceptability 6. context of use
51
What are the three main assumptions that must be true about the data for ANOVA to be a valid test?
1. independence 2. normality 3. homogeneity
52
What are Nielsen's 10 heuristics?
1: Visibility of System Status 2: Match Between the System and the Real World 3: User Control and Freedom 4: Consistency and Standards 5: Error Prevention 6: Recognition Rather than Recall 7: Flexibility and Efficiency of Use 8: Aesthetic and Minimalist Design 9: Help Users Recognize, Diagnose, and Recover from Errors 10: Help and Documentation
53
What is Participatory design?
Direct involvement of people in the collaborative design of the things and technologies they use. Pros: * More user involvements bring more accurate information about tasks * Gives end-users an opportunity to influence design decisions Cons: * Extensive user involvement is lengthy and thus costly * May generate antagonism from end-users not involved in the participatory design, or from end-users whose suggestions are rejected * May force designers to compromise their designs to satisfy incompetent end-users who are participating in the design process
54
What are GOMS?
a predictive method that can be used to evaluate a user interface design before any users have actually used the system * Goals : Aims of the user * Operators: Actions that can be done in the interface, such as clicking, dragging and typing * Methods: Sequences of sub-goals and operators that can be used to achieve a particular goal * Selection rules: The rules by which a user chooses a particular method (from a set of methods) to achieve a goal
55
What are Cognitive models?
model users’ higher level cognitive functions and aim to predict user performance of arbitrary user interfaces Two primary types of cognitive models in HCI: * Predictive models that predict user performance by modelling interaction as a series of steps, with time estimates for each step * Simulations that simulate actual human behaviour when interacting with a user interface
56
What is a KLM GOMS?
Keystroke level GOMS * A subset of GOMS that only includes operators and methods * KLM predicts task completion times * All operators have a specific execution time * Task completion times are calculated by summing up the execution times for the different operators that need to be used to perform the task Limitations: * Assumes error-free expert behaviour * Assumes reliable fixed time estimates are available for all operators
57
Explain the Sign Test
* We have n paired observations: (X1,Y1), (X2,Y2),...,(Xn,Yn) * We compute the median values for {Xi} and {Yi} * The null hypothesis is that the median difference is zero * We now compute the differences between the pairs: (Y1-X1),(Y2-X2),...,(Yn-Xn) * Differences that are zero are ignored, we may thus end up with fewer observations than n * We call this adjusted number n' * Compute the number of differences that fall below zero, we will call this number r^- * Compute the number of differences that fall above zero, we will call this number r^+ * Now we take the minimum of r^+ and r^- : r = min(r^+,r^-) * The null hypotheses states that the population median of the pair-wise differences is zero * Under this null hypothesis we would expect ½ of the pair-wise differences to be above zero (r^+) and half of them to be below zero (r^-) * Therefore, under the null hypothesis, r^+ and r^- follow a binomial distribution ) B(n,p) with p = 0.5 and n = n' * We now use the binomial distribution to find the probability of observing a value r or lower given p = 0.5 and n = n' * We have now obtained a probability of how likely our observations model the null hypothesis (no difference between the population medians) * This probability is our p-value * If this p-value is less than our preset significance level (for example, 0.05), then we reject the null hypothesis because there is less than (assuming a significance level of 0.05) 5% chance that our observations of differences in the medians would occur if the population medians are identical