Applied Research Methods — Quantitative
HCI Undergraduate: n/a
HCI Graduate: 05-822
This mini (6-week) course is for Ph.D. students who are conducting empirical quantitative research. The course is especially but not exclusively designed for those interested in any aspect of technology (social aspects, design, impact, evaluation, etc). The mini will be taught as a workshop with discussion and hands-on exercises and homework each week. Topics in the course will include: experimental design, questionnaires and surveys, social network analysis, inferential statistics often used in conjunction with quantitative analysis or mixed methods (ANOVA, regression, factor analysis) using JMP, and writing quantitative papers. In the past, student projects have included studies of online communities, lab studies of attention and distraction, and studies using archival data from organizations. Students will write a research proposal or a short paper. The intent of the course is not to compete with students’ regular research; often, topics are chosen in conjunction with students’ advisors.
This course does not teach HCI professional methods such as contextual inquiry and design that are covered in Introduction to HCI Methods and in various design courses. This course also does not cover advanced statistical and computational analyses such as text mining. The statistics introduced will help students learn how to explore quantitative data, how to organize and prepare data for statistical analysis and modeling, how to apply the methods using the JMP graphical statistical package, and instruct on how to describe statistical tests and use graphs.
Semester Offered and Units
Graduate: 6 units