You may never be sure whether you have an effective user experience until you have tested it with users. In this course, you’ll learn how to design user-centered experiments, how to run such experiments, and how to analyze data from these experiments in order to evaluate and validate user experiences. You will work through real-world examples of experiments from the fields of UX, IxD, and HCI, understanding issues in experiment design and analysis. You will analyze multiple data sets using recipes given to you in the R statistical programming language -- no prior programming experience is assumed or required, but you will be required to read, understand, and modify code snippets provided to you. By the end of the course, you will be able to knowledgeably design, run, and analyze your own experiments that give statistical weight to your designs.
教學大綱 - 您將從這門課程中學到什麼
週
1完成時間為 1 小時
Basic Experiment Design Concepts
In this module, you will learn basic concepts relevant to the design and analysis of experiments, including mean comparisons, variance, statistical significance, practical significance, sampling, inclusion and exclusion criteria, and informed consent. You’ll also learn to think of an experiment in terms of usability, its participants, apparatus, procedure, and design & analysis. This module covers lecture videos 1-2.
2 個視頻 （總計 19 分鐘）, 1 個閱讀材料, 1 個測驗
1 個閱讀材料
ALL COURSE MATERIALS10分鐘
1 個練習
Understanding the Basics16分鐘
週
2完成時間為 2 小時
Tests of Proportions
In this module, you will learn how to analyze user preferences (or other tallies) using tests of proportions. You will also get up and running with R and RStudio. Topics covered include independent and dependent variables, variable types, exploratory data analysis, p-values, asymptotic tests, exact tests, one-sample tests, two-sample tests, Chi-Square test, G-test, Fisher’s exact test, binomial test, multinomial test, post hoc tests, and pairwise comparisons. This module covers lecture videos 3-9.
7 個視頻 （總計 41 分鐘）, 2 個測驗
7 個視頻
04. Getting Started with R and RStudio2分鐘
05. Exploring Data and a First Test of Proportions7分鐘
06. Understanding and Reporting Your First Statistical Test5分鐘
07. Exact Tests, Asymptotic Tests, and the Binomial Test2分鐘
08. More One-Sample Tests of Proportions9分鐘
09. Two-Sample Tests of Proportions11分鐘
2 個練習
Understanding Tests of Proportions36分鐘
Doing Tests of Proportions30分鐘
週
3完成時間為 1 小時
The T-Test
In this module, you will learn how to design and analyze a simple website A/B test. Topics include measurement error, independent variables as factors, factor levels, between-subjects factors, within-subjects factors, dependent variables as responses, response types, balanced designs, and how to report a t-test. You will perform your first analysis of variance in the form of an independent-samples t-test. This module covers lecture videos 10-11.
2 個視頻 （總計 25 分鐘）, 2 個測驗
2 個視頻
11. Analyzing a Simple A/B Test with a T-Test10分鐘
2 個練習
Understanding Experiment Designs20分鐘
Doing Independent-Samples T-Tests30分鐘
週
4完成時間為 2 小時
Validity in Design and Analysis
In this module, you will learn about how to ensure that your data is valid through the design of experiments, and that your analyses are valid by understanding and testing for their assumptions. Topics include how to achieve experimental control, confounds, ecological validity, the three assumptions of ANOVA, data distributions, residuals, normality, homoscedasticity, parametric versus nonparametric tests, the Shapiro-Wilk test, the Kolmogorov-Smirnov test, Levene’s test, the Brown-Forsythe test, and the Mann-Whitney U test. This module covers lecture videos 12-15.
4 個視頻 （總計 41 分鐘）, 2 個測驗
4 個視頻
13. Data Assumptions and Distributions14分鐘
14. Testing for ANOVA Assumptions9分鐘
15. Mann-Whitney, a Nonparametric T-Test2分鐘
2 個練習
Understanding Validity24分鐘
Doing Tests of Assumptions30分鐘
週
5完成時間為 1 小時
One-Factor Between-Subjects Experiments
In this module, you will learn about one-factor between-subjects experiments. The experiment examined will be a between-subjects study of task completion time with various programming tools. You will understand and analyze data from two-level factors and three-level factors using the independent-samples t-test, Mann-Whitney U test, one-way ANOVA, and Kruskal-Wallis test. You will learn how to report an F-test. You will also understand omnibus tests and how they relate to post hoc pairwise comparisons with adjustments for multiple comparisons. This module covers lecture videos 16-18.
3 個視頻 （總計 14 分鐘）, 2 個測驗
3 個視頻
17. Analyzing and Reporting a Oneway ANOVA9分鐘
18. Kruskal-Wallis, a Nonparametric Oneway ANOVA3分鐘
2 個練習
Understanding Oneway Designs12分鐘
Doing Oneway ANOVAs30分鐘
週
6完成時間為 2 小時
One-Factor Within-Subjects Experiments
In this module, you will learn about one-factor within-subjects experiments, also known as repeated measures designs. The experiment examined will be a within-subjects study of subjects searching for contacts in a smartphone contacts manager, including the analysis of times, errors, and effort Likert-type scale ratings. You will learn counterbalancing strategies to avoid carryover effects, including full counterbalancing, Latin Squares, and balanced Latin Squares. You will understand and analyze data from two-level factors and three-level factors using the paired-samples t-test, Wilcoxon signed-rank test, oneway repeated measures ANOVA, and Friedman test. This module covers lecture videos 19-23.
5 個視頻 （總計 49 分鐘）, 2 個測驗
5 個視頻
20. Counterbalancing Repeated Measures Factors8分鐘
21. Long-Format and Wide-Format Data Tables3分鐘
22. The Paired T-Test and Wilcoxon Signed-Rank Test14分鐘
23. Analyzing a Repeated Measures ANOVA and Friedman Test15分鐘
2 個練習
Understanding Oneway Repeated Measures Designs20分鐘
Doing Oneway Repeated Measures ANOVAs30分鐘
週
7完成時間為 3 小時
Factorial Experiment Designs
In this module, you will learn about experiments with multiple factors and factorial ANOVAs. The experiment examined will be text entry performance on different smartphone keyboards while sitting, standing, and walking. Topics include mixed factorial designs, interaction effects, factorial ANOVAs, and the Aligned Rank Transform as a nonparametric factorial ANOVA. This module covers lecture videos 24-27.
4 個視頻 （總計 40 分鐘）, 2 個測驗
4 個視頻
25. Understanding Interaction Effects5分鐘
26. Analyzing a Factorial ANOVA12分鐘
27. The ART, a Nonparametric Factorial ANOVA14分鐘
2 個練習
Understanding Factorial Designs20分鐘
Doing Factorial ANOVAs30分鐘
週
8完成時間為 1 小時
Generalizing the Response
In this module, you will learn about analyses for non-normal or non-numeric responses for between-subjects experiments using Generalized Linear Models (GLM). We will revisit three previous experiments and analyze them using generalized models. Topics include a review of response distributions, nominal logistic regression, ordinal logistic regression, and Poisson regression. This module covers lecture videos 28-29.
2 個視頻 （總計 25 分鐘）, 2 個測驗
2 個視頻
29. Analyzing Three Generalized Linear Models18分鐘
2 個練習
Understanding Generalized Linear Models20分鐘
Doing Generalized Linear Models30分鐘
週
9完成時間為 2 小時
The Power of Mixed Effects Models
In this module, you will learn about mixed effects models, specifically Linear Mixed Models (LMM) and Generalized Linear Mixed Models (GLMM). We will revisit our prior experiment on text entry performance on smartphones but this time, keeping every single measurement trial as part of the analysis. The full set of analyses covered in this course will also be reviewed. This module covers lecture videos 30-33.
4 個視頻 （總計 35 分鐘）, 2 個測驗
4 個視頻
31. Analyzing a Linear Mixed Model11分鐘
32. Analyzing a Generalized Linear Mixed Model10分鐘
33. Course in Review2分鐘
2 個練習
Understanding Mixed Effects Models24分鐘
Doing Mixed Effects Models30分鐘
3.6
145 個審閱24%
完成這些課程後已開始新的職業生涯
21%
通過此課程獲得實實在在的工作福利
熱門審閱
This was really useful. The course was well structured and provided excellent real-life examples that are easily transferrable to other scenarios. Keep it up!
Have to watch three times to keep up because it is really hard for people without former experiences... Anyway it is worth it
講師
Scott Klemmer
ProfessorCognitive Science & Computer Science
Jacob O. Wobbrock
ProfessorThe Information School
關於 加州大学圣地亚哥分校
UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.
關於 交互设计 專項課程
您将学习如何使用设计给人们带来欢乐，而不是沮丧。您将学习如何生成的设计理念，快速进行原型设计的技术，以及如何将原型展示给其他利益相关者，例如喜欢你的队友，客户和用户，获得他们的反馈意见。您还将学习视觉设计，感知和认知的原则，达到有效的互动设计效果。
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