This document outlines the data analysis plan for a usability case study conducted on Amazon.com. It will analyze data from task scenarios where users complete typical shopping tasks on Amazon and are recorded, and from a System Usability Survey (SUS) given to users. Data will include video recordings, observations, screen recordings, and survey results. Analysis will include affinity diagramming to categorize insights and identify issues. Findings will be presented in a research report with charts, spreadsheets and pie charts. The analysis will provide recommendations to improve the usability of Amazon's shopping experience.
The talk discusses and demonstrate techniques for analyzing survey data. Survey data is useful data source to answer a wide range of questions, however, it often requires special analytical techniques to interpret. We'll discuss how to weight data to match known population parameters (such as StatsCan census data) using post-stratification and using the MICE algorithm to deal with missing data. These techniques are commonly used in political polling and social science research. I'll provide example code in R and explain all the steps using data from a survey of Canadians' values.
The talk discusses and demonstrate techniques for analyzing survey data. Survey data is useful data source to answer a wide range of questions, however, it often requires special analytical techniques to interpret. We'll discuss how to weight data to match known population parameters (such as StatsCan census data) using post-stratification and using the MICE algorithm to deal with missing data. These techniques are commonly used in political polling and social science research. I'll provide example code in R and explain all the steps using data from a survey of Canadians' values.
This proposal of work contains details and samples of the user centric design process I follow. I have been trying to find a good graph that represents the process, but at the end I have decided to make my own! ;)
Qualitative Research vs Quantitative Research - a QuestionPro Academic WebinarQuestionPro
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Principles of Health Informatics: Evaluating medical softwareMartin Chapman
Principles of Health Informatics: Evaluating medical software. Last delivered in 2023. All educational material listed or linked to on these pages in relation to King's College London may be provided for reference only, and therefore does not necessarily reflect the current course content.
A Review on Sentimental Analysis of Application ReviewsIJMER
As with rapid evolution of computer technology and smart phones mobile applications
become very important part of our life. It is very difficult for customers to keep track of different
applications reviews so sentimental analysis is used. Sentimental analysis is effective and efficient
evolution of customer’s opinion in real time. Sentimental analysis for applications review is performed
two approaches statistical model based approaches and Natural Language Processing (NLP) based
approaches to create rules. Two schemes used for analyzing the textual comments- aspect level
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produces a more accurate and focused sentiment profile than the simple document-level sentiment
analysis.
NCV 3 Business Practice Hands-On Support Slide Show - Module 6Future Managers
This slide show complements the learner guide NCV 3 Business Practice Hands-On Training by Nickey Cilliers, published by Future Managers Pty Ltd. For more information visit our website www.futuremanagers.net
You could be a professional graphic designer and still make mistakes. There is always the possibility of human error. On the other hand if you’re not a designer, the chances of making some common graphic design mistakes are even higher. Because you don’t know what you don’t know. That’s where this blog comes in. To make your job easier and help you create better designs, we have put together a list of common graphic design mistakes that you need to avoid.
This proposal of work contains details and samples of the user centric design process I follow. I have been trying to find a good graph that represents the process, but at the end I have decided to make my own! ;)
Qualitative Research vs Quantitative Research - a QuestionPro Academic WebinarQuestionPro
Hosted on October 14, 2020, this QuestionPro Academic focused webinar delved into the differences of Qualitative and Quantitative research and how you can achieve this using the QuestionPro research platform. We spoke about Heatmap and Hotspot analysis, card sorting, online focus groups using video discussions and even a beta feature coming soon, LiveCast that uses NLP to build real-time analytics from video survey questions. Our speaker was Dan Fleetwood, the President for Research and Insights at QuestionPro.
Principles of Health Informatics: Evaluating medical softwareMartin Chapman
Principles of Health Informatics: Evaluating medical software. Last delivered in 2023. All educational material listed or linked to on these pages in relation to King's College London may be provided for reference only, and therefore does not necessarily reflect the current course content.
A Review on Sentimental Analysis of Application ReviewsIJMER
As with rapid evolution of computer technology and smart phones mobile applications
become very important part of our life. It is very difficult for customers to keep track of different
applications reviews so sentimental analysis is used. Sentimental analysis is effective and efficient
evolution of customer’s opinion in real time. Sentimental analysis for applications review is performed
two approaches statistical model based approaches and Natural Language Processing (NLP) based
approaches to create rules. Two schemes used for analyzing the textual comments- aspect level
sentimental analysis analyses the text and provide a label on each aspect then scores on multiple
aspects are aggregated and result for reviews shown in graphs. Second scheme is document level
analyses which comprising of adjectives, adverbs and verbs and n-gram feature extraction. I have also
used our SentiWordNet scheme to compute the document-level sentiment for each movie reviewed
and compared the results with results obtained using Alchemy API. The sentiment profile of a movie is
also compared with the document-level sentiment result. The results obtained show that my scheme
produces a more accurate and focused sentiment profile than the simple document-level sentiment
analysis.
NCV 3 Business Practice Hands-On Support Slide Show - Module 6Future Managers
This slide show complements the learner guide NCV 3 Business Practice Hands-On Training by Nickey Cilliers, published by Future Managers Pty Ltd. For more information visit our website www.futuremanagers.net
You could be a professional graphic designer and still make mistakes. There is always the possibility of human error. On the other hand if you’re not a designer, the chances of making some common graphic design mistakes are even higher. Because you don’t know what you don’t know. That’s where this blog comes in. To make your job easier and help you create better designs, we have put together a list of common graphic design mistakes that you need to avoid.
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Can AI do good? at 'offtheCanvas' India HCI preludeAlan Dix
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https://www.alandix.com/academic/talks/offtheCanvas-IndiaHCI2024/
The world is being changed fundamentally by AI and we are constantly faced with newspaper headlines about its harmful effects. However, there is also the potential to both ameliorate theses harms and use the new abilities of AI to transform society for the good. Can you make the difference?
2.
This document is a continuation of the process of planning for and
conducting user research. The following aspects of analysis will be
covered for both Task scenarios and the SUS Survey.
● Data Types
● Specific variables
● Expected numbers of observations
● How data will be analysed
● How findings will be represented (e.g. tables, graphical representations, or other visualizations)
● Collection instruments (e.g. data collection spreadsheets, interview guides, etc.)
Task Scenarios
This method focuses on observing users behaviors and better understanding their decisions by asking a
series of follow up questions. Usability testing has been carried out with five users to gather feedback on
the path to purchase for Amazon.com shoppers. Study participants will be asked to carry out typical tasks
at Amazon.com. Participants will be recorded including their gestures and facial expressions using the site
to shop for an item. Video is then transcribed and any comments made by the participant converted to text.
Data Types:
● Screen recordings of the participants session
● Video recordings of the participant sessions
● Observations of the researcher
Variables:
● Duration of usability test
● Task completion
Number of participants (Observations)
● Three
3. How data will be analysed
Affinity diagramming will be used to categorize insights drawn from the analysis of participant interviews.
● Start playing back the recordings, one user at a time
● Begin noting down insights (one insight per post-it, one color per participant)
● Do the same for notes taken during interviews
● Begin sorting insights into categories and adding the category labels to post its
4.
● Begin grouping similar insights
* For example, an insight that a user could not find a customer support phone number to call and
another that couldn’t find an email address should be grouped together, summarising that all
contact details were difficult to find.
● Adjust for perceived impact if solved
With insights written on post-its, categorised into practical headings and prioritised based on
number of occurrences. The last step is to adjust the priority of insights based on the potential
impact if solved. Feedback collected during testing sessions is used to adjust the priority of
grouped insights and reorder them accordingly.
How findings will be represented
Findings will be represented as a research report document that will include both charts and spreadsheets.
.
6. Computer-operating model
Seven Stages of action
The computer operating model and seven stages of action can be used to analyse the issues
identified based on fundamental categories of interaction.
7. System Usability Survey
This method focuses on observing users behaviors and better understanding their decisions by asking a
series of follow up questions. Usability testing has been carried out with five users to gather feedback on
the path to purchase for Amazon.com shoppers. Study participants will be asked to carry out typical tasks
at Amazon.com. Participants will be recorded including their gestures and facial expressions using the site
to shop for an item. Video is then transcribed and any comments made by the participant converted to text.
Data Types:
● Survey results
Variables:
● Total numbers of corresponding answers given by participants to survey questions
Number of participants (Observations)
● Three
How data will be analysed
Data from surveys will be analysed by considering the correlation between usability test results and survey
results.
How findings will be represented
Findings will be represented as apart of the research report document in the form of pie charts.
.
8. Collection instruments
Google Forms
Follow Up Interview
Questions
1. Overall, how satisfied are you with the ease of completing the tasks in this scenario?
2. Overall, how satisfied are you with the amount of time it took to complete the tasks in this
scenario?
3. Overall, how satisfied are you with searching or browsing for products with Amaon.com?
Data Types:
● Video recordings of the participant sessions
● Observations of the researcher
Variables:
● None
Number of participants (Observations)
● Three
How data will be analysed
● All transcribed discussion will be analysed as part of the Affinity diagramming analysis.
