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UX from 30,000ft - COMP33512 - Lectures 13 & 14 - Week 7 - 2013/2014 Edition #comp33512

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Information about UX from 30,000ft - COMP33512 - Lectures 13 & 14 - Week 7 - 2013/2014...
Technology

Published on March 11, 2014

Author: simon-harper

Source: slideshare.net

Description

Designing your evaluations is one of the most important aspects of any user experience process. If these evaluations are designed badly you will not be able to apply the correct analysis, and if you cannot apply the correct analysis you will not be able to make any conclusions as to the applicability or success of your interventions at the interface or interactive level. In reality this means that if this is not done correctly the previous ≈215 pages of this book have been, to a large extent, pointless.
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Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up The User Experience from 30,000ft #comp33512 Week 07 – Lectures 13/14 Simon Harper University of Manchester Semester 2 – 2013/14 last update: March 11, 2014 The User Experience from 30,000ft 1 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up UX Pop Quiz 1. What are the pros and cons of gamification? 2. How could you include social / group dynamics into your system? 3. How can you enhance the users perception of fun? 4. What is the ‘skeptic’ view of Gamification? 5. List a principle and describe it. The User Experience from 30,000ft Preamble 2 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Hold On! Where’s Affective Computing? ...skipping ahead one Week! The User Experience from 30,000ft Preamble 3 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Designing Your Evaluations 1. Badly Designed = Incorrect Analysis; The User Experience from 30,000ft Preamble 4 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Designing Your Evaluations 1. Badly Designed = Incorrect Analysis; 2. Incorrect Analysis = Incorrect Conclusions; which means The User Experience from 30,000ft Preamble 4 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Designing Your Evaluations 1. Badly Designed = Incorrect Analysis; 2. Incorrect Analysis = Incorrect Conclusions; which means 3. Success of your Interventions in Doubt. The User Experience from 30,000ft Preamble 4 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Designing Your Evaluations 1. Badly Designed = Incorrect Analysis; 2. Incorrect Analysis = Incorrect Conclusions; which means 3. Success of your Interventions in Doubt. This Means If evaluations are not designed correctly the previous ≈207 pages of the course notes have been, to a large extent, pointless. The User Experience from 30,000ft Preamble 4 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Science and Generalisation Inductive reasoning Evaluates and then applies to the general ‘population’ abstractions of observations of individual instances of members of the same population The User Experience from 30,000ft Science and Generalisation 5 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Science and Generalisation Inductive reasoning Evaluates and then applies to the general ‘population’ abstractions of observations of individual instances of members of the same population Deductive reasoning Evaluates a set of premises which then necessitate a conclusion – for example: {(1) Herbivores only eat plant matter; (2) All vegetables contain only plant matter; (3) All cows are herbivores} → Therefore, vegetables are a suitable food source for Cows. The User Experience from 30,000ft Science and Generalisation 5 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Science and Generalisation Inductive reasoning Evaluates and then applies to the general ‘population’ abstractions of observations of individual instances of members of the same population Deductive reasoning 1. Therefore, the conclusion must be true provided that the premises are true; 2. Note that you could not say ‘Therefore, all cows eat vegetables’ because fruit also contains only plant matter; as do grass and trees. The User Experience from 30,000ft Science and Generalisation 5 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Scientific Bedrock To Be scientific, A method of inquiry must be based on the gathering of observable, empirical and measurable evidence, and be subject to specific principles of reasoning. The User Experience from 30,000ft Science and Generalisation 6 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Scientific Bedrock Figure: ‘The Scientific Method’ The User Experience from 30,000ft Science and Generalisation 6 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Scientific Bedrock An Inductive Example 1. Firstly, we create an hypothesis which, in the best case, cannot be otherwise interpreted and is ‘refutable’; for example we might make the statement ‘all swans are white’. In this case we may have travelled widely and tried to observe swans in every country and continent in an attempt to support our hypothesis. The User Experience from 30,000ft Science and Generalisation 6 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Scientific Bedrock An Inductive Example 2. While, we may be able to amass many observations of white swans we must also realise that a statement must be refutable. If the hypothesis remains intact it must be correct; in our example we may try to observe every swan that exists in, say, the UK, or Europe, or the Americas, which is not white. The User Experience from 30,000ft Science and Generalisation 6 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Scientific Bedrock An Inductive Example 3. However, one instance of an observation of a non-white swan will disapprove our hypothesis; in this case when we arrive in Australia we discover a black swan, in this case we can see all swans are not white and our hypothesis is found to be incorrect. The User Experience from 30,000ft Science and Generalisation 6 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Scientific Bedrock Many debates regarding the question of whether inductive reasoning leads to truth; We can make some inductive leaps if they are based on good science; These leaps may not be absolutely accurate; but May well assist us in our understanding; in the UX domain we use mathematical (statistical) methods to help us understand these points. The User Experience from 30,000ft Science and Generalisation 7 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Mathematical (Statistical) Methods Generalise results to enable us to say something about the wider population; so We use well formed and tested statistical tests; Which enables use to mathematically generalise to a population; this is called, External Validity. The User Experience from 30,000ft Science and Generalisation 8 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Mathematical (Statistical) Methods Generalise results to enable us to say something about the wider population; so We use well formed and tested statistical tests; Which enables use to mathematically generalise to a population; this is called, External Validity. No 100% Certainty All we have is a level of confidence in how a particular test relates to the population, and therefore how useful the knowledge generated from it really is. The User Experience from 30,000ft Science and Generalisation 8 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Variables / UX Behavioural: Equated to the user; Stimulus: Equated to the interface or the computer system; Observable Response: the thing we measure to understand if there is a benefit after we have manipulated the stimulus; and Subject: Factors such as age, weight, gender. Independent Variable: The thing that we manipulate – the lower the number of independent variables, the more confident we can be about the data collected and the results of the analysis; and Dependent Variable: The thing that we measure. The User Experience from 30,000ft Science and Generalisation 9 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Measuring Dependent Variables Nominal Scale: Which denotes identity; Ordinal Scale: Which denotes identity and magnitude; Interval Scale: Denotes identity, magnitude and has the benefit of equal intervals; and Ratio Scale: Which has the positive properties of the three we have already seen as well as a true zero point. The User Experience from 30,000ft Science and Generalisation 10 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Measuring Dependent Variables Nominal Scale: Which denotes identity; Ordinal Scale: Which denotes identity and magnitude; Interval Scale: Denotes identity, magnitude and has the benefit of equal intervals; and Ratio Scale: Which has the positive properties of the three we have already seen as well as a true zero point. Variables, and their measurement, are important. They inform the experimental design process and the kind of analysis that will be possible once the data has been collected. The User Experience from 30,000ft Science and Generalisation 10 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Hypothesis Testing Null Hypothesis: Which dictates that there is no difference between two conditions beyond chance differences; or Hypothesis: Which dictates there is a difference and supports the hypothesis proposed. The User Experience from 30,000ft Science and Generalisation 11 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Hypothesis Testing Null Hypothesis: Which dictates that there is no difference between two conditions beyond chance differences; or Hypothesis: Which dictates there is a difference and supports the hypothesis proposed. Strong and Weak A hypothesis must be ‘strong’ to be testable. The User Experience from 30,000ft Science and Generalisation 11 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Hypothesis Testing Null Hypothesis: Which dictates that there is no difference between two conditions beyond chance differences; or Hypothesis: Which dictates there is a difference and supports the hypothesis proposed. Strong and Weak A hypothesis must be ‘strong’ to be testable. Nothing is Ever Proved Hypotheses are supported or disproved - NOT ever proved (in empirical work).. Why? The User Experience from 30,000ft Science and Generalisation 11 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Let’s Have a Break! Back in 10 Minutes! Come see me now if you have Questions Regarding this Lecture! The User Experience from 30,000ft Break! 12 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Evaluation Design and Analysis Experimental Design; Data Collection and Tools; Data Analysis; mostly Statistical Analysis. The User Experience from 30,000ft Evaluation Design and Analysis 13 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Evaluation Design and Analysis Descriptive Statistics; Inferential Statistics. Internal Validity; External Validity; and Confounding Variables. The User Experience from 30,000ft Evaluation Design and Analysis 14 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Participants Simple Random Sampling Probabilistic — Simple random sampling equates to drawing balls at a tom-bola. The selection of the first has no bearing, and is fully independent of, the second or the third, and so forth. This is often accomplished in the real world by the use of random number tables or, with the advent of computer technology, by random number generators; Systematic Sampling Probabilistic — Systematic samples are a variation of random sampling whereby each possible participant is allocated a number, with participants being selected based on some systematic algorithm. In the real world we may list participants numbering them from, say, one to three hundred and picking every seventh participant, for instance; The User Experience from 30,000ft Evaluation Design and Analysis 15 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Participants Stratified Sampling Probabilistic — Stratified samples are used to reduce the normal sampling variation that is often introduced in random sampling methods. This means that certain aspects of the sample may become apparent as that sample is selected. In this case, subsequent samples are selected based on these characteristics, this means that a sample can be produced that is more likely to look like the total population than a random sample; Multistage Sampling Probabilistic — Multistage sampling is a strategy for linking populations to some kind of grouping. If a sample was drawn from, say, the U. of Manchester then this may not be representative of all universities. In this case, multistage sampling could be used whereby a random sample is drawn from multiple different universities independently and then integrated. In this way we can ensure the generalisability of the findings; and The User Experience from 30,000ft Evaluation Design and Analysis 15 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Participants Quota Sampling Non-Probabilistic — Almost all non-governmental polling groups or market research companies rely heavily on non-probability sampling methods; the most accurate of these is seen to be quota based sampling. Here, a certain demographic profile is used to drive the selection process, with participants often approached on the street. In this case, a certain number of participants are selected, based on each point in the demographic profile, to ensure that an accurate cross-section of the population are selected; Snowball Sampling Non-Probabilistic — The process of snowball sampling is much like asking your participants to nominate another person with the same trait as them. The User Experience from 30,000ft Evaluation Design and Analysis 15 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Participants Convenience Sampling Non-Probabilistic — The participants are selected just because they are easiest to recruit for the study and the UX’er did not consider selecting participants that are representative of the entire population. Judgmental Sampling Non-Probabilistic — This type of sampling technique is also known as purposive sampling and authoritative sampling. Purposive sampling is used in cases where the specialty of an authority can select a more representative sample that can bring more accurate results than by using other probability sampling techniques. The User Experience from 30,000ft Evaluation Design and Analysis 15 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Evaluation‘++’ Single Group, Post Test; Single Group, Pre-Test and Post-Test; Natural Control Group, Pre-Test and Post-Test; Randomised Control Group, Pre-Test and Post-Test; Within Subjects; but there are Others. The User Experience from 30,000ft Evaluation Design and Analysis 16 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Practical Ethical Procedures The Ethical Process A critical component of good evaluation design because it encourages the UX specialist to focus on the methodology and the analysis techniques to be used within that methodology. The User Experience from 30,000ft Practical Ethical Procedures 17 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Organisations The American Psychological Association’s (APA), ‘Ethical Principles of Psychologists and Code of Conduct’; The United States Public Health Service Act (Title 45, Part 46, Appendix B), ‘Protection of Human Subjects’; The Belmont Report, ‘Ethical Principles and Guidelines for the Protection of Human Subjects of Research’; The Council of International Organisations of Medical Sciences, ‘International Ethical Guidelines for Epidemiological Studies’; and finally The World Medical Association’s, ‘Declaration of Helsinki – Ethical Principles for Medical Research Involving Human Subjects’. The User Experience from 30,000ft Practical Ethical Procedures 18 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up in Brief... About You... Competence: Keep up to date, know your limitations, ask for advice; Integrity: Have no axe to grind, or desired outcome; and Science: Follow the Scientific Method. The User Experience from 30,000ft Practical Ethical Procedures 19 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up in Brief... About Them... Respect: Assess you participants autonomy and capability of self-determination, treat participants as equals, ensure their welfare; Benefits: Maximising benefits and minimising possible harms according to your best judgement, seek advice from your organisations ethics committee; Justice: Research should be undertaken with participants who will benefit from the results of that research; and Trust: Maintain trust, anonymity, confidentiality and privacy, ensure participants fully understand their roles and responsibilities and those of the experimenter. The User Experience from 30,000ft Practical Ethical Procedures 19 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up in Brief... About Us... Responsibility: You have a duty of care, not only to your participants, but also to the community from which they are drawn, and your own community of practice. The User Experience from 30,000ft Practical Ethical Procedures 19 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Discussion Topics Coursework # 3 ‘Voice Loops as Cooperative Aids in Space Shuttle Mission Control’ (10 Marks) – this paper shows just how far UX and the techniques which it inherits from human computer interaction can go. We are mainly concerned with systems and objects which are purely commercial, however, in this case failures in the human interface can have serious consequences for a real-time mission, including the loss of the vehicle. Further, these kind of UX techniques can also be found in other critical interface components such as those controlling nuclear power stations or fly-by-wire aircraft. Jennifer C. Watts, David D. Woods, James M. Corban, Emily S. Patterson, Ronald L. Kerr, and LaDessa C. Hicks., Voice loops as cooperative aids in space shuttle mission control., In Proceedings of the 1996 ACM conference on Computer supported cooperative work, CSCW ’96, pages 48–56, New York, NY, USA, 1996. ACM., ISBN 0-89791-765-0., http://doi.acm.org/10.1145/240080.240188., URL http://doi.acm.org/10.1145/240080.240188. The User Experience from 30,000ft Wrapping Up 20 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Pop Quiz for next (logical) week... 1. What is the scientific method and why is it important? 2. What do we mean by internal and external validity? 3. What is the single most important reason for having a set of ethical procedures? 4. What are the eight key ethical principles (give a brief rationale for each)? 5. Why is conforming to scientific principles key to good ethical designs? The User Experience from 30,000ft Wrapping Up 21 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up To Do for next week... 1. Pop Quiz, Discuss Next Week; and 2. Read your notes! The User Experience from 30,000ft Wrapping Up 22 / 23

Preamble Science and Generalisation Break! Evaluation Design and Analysis Practical Ethical Procedures Wrapping Up Any Questions? Simon Harper 2.44 Kilburn Building 0161 275 0599 (OR x50599) simon.harper@manchester.ac.uk Office Hours: Friday 14:00–18:00 Figure: ‘Moving the Order’ The User Experience from 30,000ft Wrapping Up 23 / 23

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