Workshops

LATIS offers a series of workshops that are free and open to all faculty and graduate students. Join our LATIS Research Workshops Google Group to be the first to learn about workshops. You can view the videos, slides, and materials from past workshops at the LATIS Workshop Materials website.

Fall 2021 Workshops

All workshops are now in a Zoom-based online format, unless otherwise noted.

Sept 24 | 10:00am-noon Introduction to Nvivo  Registration
Oct 1 | 10:00am-noon Designing Experiments & Complex Surveys in Qualtrics
Registration
Oct 8 | 10:00am-noon Introduction to R
Registration

Oct. 15 | 10:00am-2:30pm

Creating Professional Video Recordings for Media Projects - Introduction to LATIS Equipment -- In-person, Rarig Center  Registration
(limited capacity)
Oct. 15 | 10:00am-noon Introduction to Python
Registration
Oct 22 | 10:00am-noon Introduction to Atlas.ti
Registration
Oct. 29 | 10:00am-noon Preparing Figures for Publication
Registration
Nov 5 | 10:00am-noon

Introduction to Web APIs in Python

Registration

Nov 12 | 10:00am-noon

Online Participant Recruitment (Mturk/Prolific participant recruitment)
Registration
Nov 19 | 10:00am-noon Introduction to github
Registration
Dec. 3 | 10:00am-noon Introduction to Web Scraping in Python  Registration
     

Available date

Asynchronous workshops
(Work at your own pace online in Canvas)
 
Opens Oct. 8th Introduction to Survey Sampling
Register to  enroll
Opens Sept. 7th Qualtrics - Tutorials
Register to enroll
Opens Sept. 8th Working with data in R - Tutorials
Register to enroll

 

Workshop Descriptions

Introduction to NVivo

NVivo is a qualitative data management, coding and markup tool, that facilitates powerful querying and exploration of source materials for both mixed methods and qualitative analysis. It integrates well with tools that assist in data collection and can handle a wide variety of source materials. This workshop introduces the basic functions of NVivo, with no prior experience necessary. Licensing is provided for faculty and graduate students of the College of Liberal Arts; others can run the software in trial-mode for two weeks or can be given temporary access to the software for this workshop. 

This workshop will cover

  • Adding your source materials (text, images, audio/video, survey/spreadsheets)
  • Working with concepts (or codes/tags) and their definitions
  • Making annotations and analytical memos
  • Using text queries to speed up coding
  • Finding patterns in the concepts identified in the source materials
  • Importing data from other tools including Qualtrics, OneNote, and Zotero
  • Exporting excerpts and making backups
  • Working in teams

To be successful, you should

  • Be familiar with source materials used in qualitative research (interviews, focus groups, field notes, archival documents, etc.)
  • Be familiar with the types of questions asked in qualitative research
  • Download and install NVivo from z.umn.edu/get NVivo prior to the workshop

 

Designing Experiments & Complex Surveys in Qualtrics

Sometimes figuring out the right bells and whistles for more complex research designs in Qualtrics can be daunting. If you’re looking to build complex surveys or experimental tasks within Qualtrics, this tutorial is for you! We cover how to use some more complex functionality within Qualtrics, such as:

  • using the survey flow to create complex survey designs
  • branching logic
  • embedded data
  • embedded media
  • piped text
  • “loop & merge”
  • integration with MTurk/Prolific, and more! 

To be successful, you should have:

  • Some basic experience with Qualtrics-- either through your own research or by taking our “Introduction to Qualtrics”  Canvas course.

 


Preparing Figures for Publication

Figures and illustrations are essential parts of scientific publication. If you don’t work regularly with image editing software, ensuring your figures both present your work clearly and meet journal-specific standards can feel daunting. In this two hour workshop we will go through the steps of preparing an image for publication using the free browser-based photo editor PhotoPea

Workshop format:

  • BEFORE WORKSHOP: 
    • Nothing!
  • DURING WORKSHOP:
    • In person walkthrough of the skills described in the section below. 

This workshop will cover how to:

  • Set up an image-editing template based on specific print size and resolution requirements
  • Scale, rotate, and crop an image
  • Do basic brightness, contrast, and color adjustments (when appropriate)
  • Add a scale bar to an image
  • Add labels to an image
  • Evaluate a figure for clarity and accessibility
  • Export an image with the proper formatting for publication

To be successful, you should have:

  • A computer you can use during the workshop. A mouse is recommended but not required.
  • No prior experience with image editing necessary

 

Introduction to ATLAS.ti

ATLAS.ti is a qualitative analysis program, used to organize, tag, and analyze a variety of research materials including text, audio, and visual sources. It’s lineage is linguistic and discursive and provides a flexible workbench in which to conduct interpretive research, as well as other types of qualitative inquiry. This workshop introduces the basic functions of ATLAS.ti, with no prior experience necessary. It will be held via Zoom using the trial version of the software installed. (The full version of the software is provided by remote desktop for faculty and graduate students of the College of Liberal Arts, Carlson School of Management and the Humphrey School of Public Affairs.)

This workshop will cover

  • Adding your source materials (text, images, audio/video)
  • Working with codes (i.e. tags/themes/concepts)
  • Making annotations (comments) and analytical memos while linking them to sources
  • Using groups (of sources, codes, etc) to organize and segment materials
  • Performing searches using your codes
  • Exporting excerpts and making backups
  • Working in teams

To be successful, you should

  • Be familiar with source materials used in qualitative research (interviews, focus groups, field notes, archival documents, etc.)
  • Be familiar with the types of questions asked in qualitative research

 

Creating Professional Video Recordings for Media Projects - Introduction to LATIS Equipment

Video is an instantly engaging medium, as long as the presentation is of high enough quality to effectively convey your message without distractions. But how do you get better quality? We will demystify the settings and answer questions like “could I just use my smart phone,” or “why wouldn’t I use everything in auto mode?” This hands-on workshop will guide you through the steps of conducting a stationary interview with one subject to produce a high quality media recording. We will focus on a repeatable camera and lighting setup that can be a versatile approach for many different scenarios. You will be introduced to, and have hands on practice setting up and using the professional equipment available to you in the LATIS checkout center. This workshop will be helpful for those planning on developing media projects as a component of their research output. We’ll practice setting up and using the equipment from 10:00-noon, take a quick, half hour lunch, then talk about planning and tips, and practice interviewing.

This workshop will cover:

  • The basics of setting up camera, tripod, lighting and microphones 
  • The essential items - whether, and how to use auto or manual - for camera and sound
  • Connecting the microphone and setting the audio levels on the camera
  • A quick setup for interview lighting 
  • General tips for successful interviewing on camera

To be successful, you should have:

  • Wear shoes that cover your toes

 

Introduction to R

Introduction to R

R is a popular tool for data analysis and statistical computing, and is a great alternative to tools like SPSS, Stata, or Excel. R is free and designed for reproducible research. This workshop will teach you how to get started using R to explore and clean your data. We will focus on issues social scientists often encounter when using data in R. This workshop will contain asynchronous and synchronous components.  

Workshop format:

  • BEFORE WORKSHOP: Asynchronous materials to review on Canvas (2 sections: 30-40 minutes each)
  • DURING WORKSHOP:
    • Open help session/time to review materials on Zoom
    • Live Demonstration on Zoom
    • Open help session/time to work on activities on Zoom

This workshop will cover how to:

  • Create an R script (syntax/command file) to capture data cleaning steps in a reproducible way
  • Load a comma-delimited spreadsheet (.csv) into R as a dataset
  • View and examine data in R 
  • Check and correct missing values, rename variables, create new variables, and recode values in the data 
  • Save cleaned data file in formats for later use in R or other applications

To be successful, you should have:

  • A familiarity with data used in the social sciences
  • A familiarity with another statistical or data processing tool, such as SPSS, Stata, SAS, or Excel

 

Introduction to Python

Python has seen wide adoption in academic research because it is a powerful but easy-to-learn programming language. In this introductory workshop, participants will gain a better understanding of the benefits and drawbacks of using Python for research computing, learn the basic grammar and syntax of a functional Python program, and explore a couple hands-on exercises that demonstrate how Python can be used to handle data management challenges found in a research environment.

This workshop will cover:

  • Why Python is a good choice for research programming
  • How to interact with the Python interpreter
  • Using the basic building blocks of the Python language to create a non-trivial program
  • Handling data files and the file system
  • Preview of using Pandas to explore data

To be successful, you should have:

  • A working knowledge of computers and basic programming concepts (e.g., meaning of variables, integers vs strings, control structures)
  • A familiarity with manipulating data used in social science research
  • A computer with Internet access

 

MTurk, Prolific, and Online Participant Recruitment 

Over the course of the last decade, online participant recruitment has become increasingly more common (especially during the pandemic!). Amazon Mechanical Turk (MTurk), Prolific, and market research panels are commonly used by social scientists to recruit research participants for online studies. In this workshop, we will not only cover the basics of setting up a study using these online platforms-- we will also discuss methodological considerations for when you are setting up a study that will recruit using one of these platforms.  

More specifically, we will cover: 

  • The ins and outs of setting up a HIT (study) on MTurk/CloudResearch
  • The ins and outs of setting up a study on Prolific.co
  • The basics of conducting longitudinal studies on MTurk and Prolific.co
  • Sampling methods & data quality across different online recruitment platforms
  • The difference in characteristics of participants in online recruitment platforms, and what that means for your research 
  • The cost of different online recruitment platforms

To be successful, you should have:

  • No prior knowledge required, although it will be very helpful to have foundational experience/knowledge with human subjects research methods

 

Introduction to GitHub

GitHub is a web application for hosting, sharing, and tracking digital assets like source code and datasets.  GitHub, and the git family of tools, keep track of changes to your files as you work, and provide easy ways to integrate changes from multiple people.  If you’ve ever found yourself making files named “copy_copy_final” and “copy_copy_real_final”, GitHub is for you.

This workshop will cover how to:

  • Create a repository with the University-provided GitHub.umn.edu website
  • Make changes and add files to your repository
  • Collaborate with team members
  • Use the GitHub desktop tools to track files on your own computer, and back them up to the cloud

To be successful, you should have:

  • A laptop
  • A University of Minnesota Internet ID

 

Introduction to Web APIs in Python

Web APIs (Application Programming Interfaces) provide a way for scholars to efficiently and legally access and download data from web platforms and publications such as Twitter and the New York Times. In this workshop we’ll use Python to query and download data using the NY Times API.

This workshop will cover how to:

  • Use Python 3 in a JupyterLab computing environment
  • Read API documentation to build successful API queries
  • Use the Requests and JSON Python libraries to download data from the NY Times API
  • Use built-in Python functions such as type, len, and dir to explore API data
  • Explore API data in Python using dictionaries

To be successful, you should have:

  • A computer you can use during the workshop, with
  • No prior experience with these tools is necessary, and participants do not need to have any coding skills. 
  • The Introduction to Python workshop on October 15, 2021 is not required, but recommended.

 

Introduction to Web Scraping in Python

The internet is full of information waiting for exploration - from social media, to newspaper comments, to digitized archives. How do you begin gathering this kind of data? This workshop will introduce participants to browser-based tools for web scraping as well as reproducible web scraping methods using Python. We will cover essential legal literacies to ensure you can make informed decisions about when and how to web scrape following legal and ethical best practices.

This workshop will cover how to:

  • View and explore the HTML tree underlying every webpage you see
  • Use a browser extension (Scraper) to systematically copy sections of matching HTML from a single webpage
  • Use Python 3 in a JupyterLab computing environment
  • Use the Requests and BeautifulSoup Python libraries to access HTML data from the web
  • Create variables, lists and loops to work with web data in Python
  • Store and view HTML data in Pandas dataframe format

To be successful, you should have:

  • A computer you can use during the workshop, with the following installed:
  • No prior experience with these tools is necessary, and participants do not need to have any coding skills. 
  • The Introduction to Python workshop on October 15, 2021 is not required, but recommended.

 

Qualtrics Tutorials (Canvas Modules)

Alongside our live “Designing Experiments & Complex Survey in Qualtrics” workshop, we also have asynchronous Canvas courses available for you to take: 

  1. Introduction to Qualtrics 

Are you brand new to using Qualtrics? Or has it been a really long time since you used Qualtrics? Start here to learn the ropes.

  1. Qualtrics Data Integrity & Management

No matter if you are new to Qualtrics or a long-time user, this module is a must for any Qualtrics user who is interested in 1) how to make Qualtrics data more readable and suitable to their needs, 2) best practices for conducting reproducible research within Qualtrics (e.g., sharing and archiving survey information, how to export data reproducibly, etc.).

 

Introduction to Survey Sampling (Canvas Module)

This is an interactive, self-paced Canvas course, designed for those who are either 1) completely new to surveying or 2) have never had formal instruction in survey/sampling design. By the end of course, you should be able to: 

  1. Differentiate between a census and a sample

  2. Describe features and limitations of common sampling methods

  3. Recognize different sources of survey error/bias

  4. Describe how different sources of survey error/bias affects the conclusions you can draw with your survey

This brief, introductory course to sampling is designed to take around 1-3 hours to complete, depending on the material you choose to engage with.

 

Working with Data in R - Tutorials (Canvas Module)

R is a popular tool for data analysis and statistical computing, and is a great alternative to tools like SPSS, Stata, or Excel. R is designed for reproducible research and can be used for many parts of the research process besides statistical analysis. This asynchronous course includes introductory readings, videos, and activities to build on and advance your data skills in R. 

Topics include

  1. Foundations in R: Just starting in R? Welcome! This module will walk you through the basics of R and set the foundation for the more advanced modules below. 
  2. Publication worthy graphs with ggplot2: Learn how to adjust colors, axises, legends, and themes, as well as how to reproducibility save graphs for publication. 
  3. Create a table using dplyr: Learn how to aggregate data and create summaries for tables for publication. 
  4. Reshaping data: Data are not always in the right format for analysis or visualization. Learn how to transform data from wide to long format and back again. 
  5. R Markdown: Combine code, output, and text into readable documents with R Markdown. Learn how to create a basic R markdown document for research. 
  6. Working with Qualtrics data in R: Qualtrics is a popular tool for survey research, but the resulting data often require cleaning before analyzing in R. Learn how to efficiently clean Qualtrics data for use in R, including how to reproducibly remove the multiple headers, save labels, and combine multi-response columns.