POLS 631: Research Methods

Course Description

This course is an introduction to the quantitative analysis of politics. While qualitative analysis is equally as important, time limitations permit this course to focus only on quantitative methods. The division between qualitative and quantitative research is perhaps less interesting and imperative than many scholars would have you believe. This course does not focus on quantitative analysis because it is superior, more difficult, more systematic, or more “scientific.” Instead, it is really more of a way to provide students with “intellectual self-defense” in a world where many phenomena, including political phenomena, are commonly reduced to numbers. It is, as I will often reiterate during the course of the semester, like learning another language. Its rules and structure are somewhat rigid like grammar and syntax. However, like with words, statistics can be used to manipulate and evoke responses that one might not otherwise get. Consequently, like politics, quantitative research is about power. The best way to make power less arbitrary is to educate the mass public, so this is your democratic education.

This is a required course in the Masters in Public Administration and the Masters in Political Sciences.

This course is an elective for the Masters in Communication Studies and Masters in Social Science.

Course Modality

Hybrid -- with a face-to-face or online synchronous option. (Many graduate students who began Fall 2020 did not move to Chico, so the synchronous online option is to accommodate these students’ situations).

The hybrid component is managed as a flipped classroom. Students will be required to attend the once a week face-to-face or online synchronous sessions, which will be held simultaneously.

Classroom participation will be facilitated through group work and a “lab” component

The weekly in-class, synchronous labs will introduce students to “coding” with the use of the free, open source statistical software, R Studio. Students who have a Chromebook or iPad may access the statistical software via R Studio Cloud.

Course Design

The course is organized with weekly course “folders” with action items and learning outcomes for each week.

All the readings/videos/web links for the week are located in each weekly folder -- with the exception of the course text - although I provide a copy of the first few weeks so student have time to obtain the most reasonable copies.

Sample Blackboard Organization

Student Engagement

Student engagement with the course material is facilitated by weekly assignments that require students to apply what they have learned by completing the reading, videos, and the in-class laboratory exercises.

Student-instructor interaction occurs during the lab time, which is approximately one-half of the weekly class period

Student-student interaction is facilitated through lessons during the class period that engage students in pairs or groups to develop their statistical analysis and interpretation skills. See example interactive class lesson.

Students interact asynchronously with each other and the instructor and TA on the Slack platform.

Welcome/introduction activities include posting bios on Slack and responding to each other’s bios. See image posted on the proceeding “Technology & Tools” slide.

Sample Interactive Class Lesson

Assessment of Student Learning

Course Student Learning Outcomes

Upon successful completion of this course, students will be able to:

Identify the appropriate statistic for a given situation.

Calculate appropriate statistics using statistical programs—e.g., R Studio and Survey Documentation and Analysis (SDA).

Produce and explain graphs, tables, and infographics of the results of their statistical analyses.

Write an empirical research paper explaining the results of their statistical analyses.

Collaborate, produce, and present a video /audio recording of the results their statistical analyses.

Explain the results of statistical analyses to the general public.

Sample Assignment

Opportunities for Active Learning

During the semester, students complete a scaffolded, applied project which culminates in a research paper that includes a data, methods & analysis section.

Furthermore, students present the results of their research publicly during the final two weeks of the semester.

On the right are two example slides from a student presentation in spring 2021. The student used R Studio to build a “sense of community” scale, using the 2018 National Survey of Health Attitudes.

Here is a link to a Chico State Today article about a student who utilized the National Asian American Survey in the class, and went on to present his research to a CSU-wide conference (for which he won an award). This experience aided in making his applications to PhD programs competitive. The student also served as a teaching assistant for the course in fall 2020.

Elements of Experiential Learning & Connections to the Professional Field

Students regularly engage with public policy reports and public policy data.

For example, they read, interpret, and model the interpretations presented in the most recent, timely reports from the Public Policy Institute of California.

Elements of Equity, Diversity & Inclusion

Much of the examples of analysis in which students engage during the class session “lab” time involves identifying race/class/gender inequities.

The class incorporates a focus upon “inclusive sources of data” such as the Just Data Lab at Princeton University, The COVID Racial Data Tracker, or survey research that includes under researched populations - such as the National Asian American Survey (NAAS) or the Latino Immigrant National Election Study (LINES).

Elements of Climate Change and Resilience & Environmental Justice

Several of the weekly lessons focus upon reports from the Water Policy Center at the Public Policy Institute of California.

Students engage with both the report, the data, and each other about the inequitable impacts of water shortages, etc.

Technology & Tools

Students can interact asynchronously with the Pronto app.

Students will learn how to “code” basic statistical analyses using R Studio.

Students will produce shared content via Google Slides and Google Docs, including audio and video for interactive in-class lessons.

Accessibility & UDL

Course materials (in addition to the course text, which is available in print and electronic formats) are compliant with Blackboard Ally.

Students can engage with each other in a variety of formats, including leaving text “chats,” voicemails, or videos on the Slack platform, that encourages asynchronous collaboration.

Weekly course materials illustrate the main topics through print, video, & audio formats. All video and audio is closed captioned.

Training in Course Design

Go Virtual, Summer 2020

A collaboration between myself and a lecturer, Eileen Morris, grew out of the Go Virtual Institute. We co-created an applied research project across three sections of POLS classes in fall 2020 and four sections of POLS classes in spring 2021 - involving over 200 students in group presentations, culminating in public, virtual conferences in December and May, respectively. In this collaboration, we applied our knowledge gained from Go Virtual in using Google Slides, audio, video and collaboration open source apps. Here is a link to the conference program from fall 2020 (see page 7-11 of the pdf).

AEL Institute, Summer 2021

I am in the process of designing an interactive “template” to use for every class period, whereby students share the results of their analyses and how they got there. Prior to this institute, students engaged in these exercises on their own, or in the pre-pandemic era, there was often spontaneous collaboration in the “lab” classroom time. By applying the knowledge, skills and ideas I obtained in the AEL Institute, I endeavor to spread these benefits both more equitably and to the online environment.

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