Spring 2024 Workshops

LATIS offers a series of workshops that are free and open to all faculty, graduate students, and staff. 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.

Workshops are also offered on even more topics from partner departments:

See workshops.umn.edu for a list of current Research and Computing Workshops across the University. 

Spring 2024 LATIS Workshop Schedule

Workshops will be a mix of in-person and online formats. Click on the links below for a detailed description of each workshop. Please note different workshop start times.

Register here for one or more workshops! 

Feb 2 | 9:00am-11:00amAdvanced Topics in NVivoBruininks Hall 131A
Feb 9 | 9:00am-11:00amCreating and Updating Research Databases with SQLBruininks Hall 131A
Feb 14 | 1:00pm-3:00pmQualtrics Tidbits: A love note for future you: Setting up useable survey documentation Online (Zoom)
Feb 21 | 1:00pm-3:00pmQualtrics Tidbits: Best Practices to Ensure Data Quality in QualtricsOnline (Zoom)
(CHANGED DATE) Feb 23 | 9:00am-11:00am Research Tips about Research Trips with LATIS Liberal Arts Engagement Hub
120 Pillsbury Hall
(CHANGED DATE) March 6 | 1:00pm-3:00pmQualtrics Tidbits: Best Practices to Improve Survey AccessibilityOnline (Zoom)
March 13 | 1:00pm-3:00pmQualtrics Tidbits: Best Practices for Creating and Utilizing Qualtrics WorkflowsOnline (Zoom)
March 20 | 1:00pm-3:00pmQualtrics Tidbits: Best Practices for Analyzing Data in QualtricsOnline (Zoom)
March 22 | 9:00am-11:00amSurvey of AI Tools for ResearchBruininks Hall 131A or Online (Hybrid)
March 29 | 9:00am-11:00amAdvanced R: Writing and Formatting R Markdown/QuartoOnline (Zoom)

Register today! 

Asynchronous Workshops

We also offer asynchronous workshops in canvas that you can take at your own pace. Please contact us [email protected] with any questions or trouble enrolling. Click on the links below for a detailed description of each workshop.

Available anytimeIntroduction to Survey SamplingEnroll Now
Available anytimeQualtrics - TutorialsEnroll Now
Available anytimeWorking with data in R - TutorialsEnroll Now
Available anytimeLinux for Research ComputingEnroll Now
Available anytimeManaging Data When You GraduateEnroll Now

Workshop Descriptions

Research Tips about Research Trips with LATIS

Are you planning on going to a museum, archive, or historical collection for your dissertation or thesis research? Planning research trips can feel overwhelming, and it can be difficult to know where to start. In this workshop, you will receive advice for navigating the intricacies of research visits, both domestic and international. This workshop will be in person with the first half as a presentation followed by smaller discussions where participants can ask questions and share advice. Panelists will include Tessa Cicak (LATIS, Ph.D. UMN Anthropology), Pat Briscoe (UMN Research and Innovation Office, Export Controls and International Projects Officer), Mara Taft (Collections Manager Science Museum of Minnesota), and Johnnie Jaeger (UMN Heritage Studies and Public History, Master’s Student). 

This workshop will cover:

  • Emailing curators/collections managers.
  • Planning your trip to make the most out of your time.  
  • Advice on organizing your materials while you’re there.
  • Best practices for collecting and digitizing images, 3D data, and collecting oral history.
  • Things to consider when traveling internationally with equipment and how to bring materials back into the U.S.
  • How to keep your data safe upon your return.
  • Sharing and showcasing your collected materials.

To be successful, you should have:

  • No prior research trip experience is necessary, nor do participants need to have a research trip currently planned. 

 

Advanced Topics in 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. The software is provided for faculty and graduate students of the College of Liberal Arts, College of Education and Human Development and the Humphrey School of Public Affairs. This workshop introduces the advanced functions of NVivo, with basic knowledge of NVivo recommended.

This workshop will cover

  • A brief review of adding and managing source materials and codes
  • Creating classifications & attributes (variables) with demographic data and importing them from Excel
  • Organizing materials into “cases” to facilitate comparison
  • Using “auto-coding” to segment transcripts and other structured text
  • Complex queries with codes and concepts subset by attributes, cases, or sources
  • Running the built-in interrater reliability metrics
  • Importing data from other software including Qualtrics, OneNote, and Zotero
  • Exporting frequencies and code counts to statistical packages

 

To be successful, you should

  • Have a basic understanding of qualitative research methods
  • Be familiar with NVivo’s interface and basic functions

Creating and Updating Research Databases with SQL

In Introduction to SQL and Research Databases (Fall 2023), participants learned about the Structured Query Language (SQL) and how to write queries that create, read, update, or delete data from an existing database (the so-called CRUD operations). In this installment of the research databases series, we will expand upon CRUD operations and start introducing the tools needed to create a database from scratch. Topics covered include: questions to ask when choosing a database technology; describing the fundamental building blocks of schema design; creating an Entity Relationship Diagram (ERD); introducing SQL's Data Definition Language (DDL); and optimizing your database for faster access and computations. Prerequisite: we highly encourage participants to attend Introduction to Research Databases and SQL, or have sufficient knowledge of CRUD operations, prior to attending this session.

This workshop will cover:

  • Basic database design: What are tables, relations, indices, etc.
  • Data Definition Language (DDL): How to create tables, indices, etc.
  • Scripting and SQL: Writing scripts to access, view and manipulate data
  • Intro to optimizing database design and queries

To be successful, you should have: 

  • A laptop to bring to the workshop:
  • Knowledge sufficient to write queries that create, read, update, and delete data in SQL. If you do not already have this knowledge, you can review our Intro to SQL workshop recording; there are also many online resources, such as Codecademy, that walk through the basics of SQL. 

Qualtrics Tidbits: A love note for future you - Setting up useable survey documentation

Metadata, or data that gives information about other data, is essential for reproducible research. This workshop will focus on survey metadata within Qualtrics and its relationship to conducting reproducible research. We will also focus on best practices in Qualtrics to help you ensure data integrity and to make your data management and analysis processes more efficient.

This session is designed to be a 1.5 hour webinar/workshop with 30 minutes for general questions at the end. 

This workshop will cover:

  • How to edit survey metadata in Qualtrics;
  • Best practices for creating, editing, and archiving survey metadata;
  • Tips for improving your data management process in Qualtrics.

To be successful, you should:

  • Have logged into umn.qualtrics.com and activated your account.
  • Have basic experience with Qualtrics – either through your own research or by taking our "Introduction to Qualtrics" Canvas module.

Qualtrics Tidbits: Best Practices to Ensure Data Quality in Qualtrics

How do we ensure that only the people who should be responding to our studies are responding? What are the best ways for making sure our participants are actually paying attention? What's the deal with bots gaining access to studies? How do I set a data plan in place that is reproducible? This workshop will present strategies and tools to maximize the quality of data from online surveys, focusing on methods in Qualtrics. 

This session is designed to be a 1.5 hour webinar/workshop with 30 minutes for general questions at the end. 

This workshop will cover:

  • Strategies to prevent bad actors and bots from taking your online study;
  • Strategies to assess the quality of data after it has been collected online;
  • The upsides and downsides of implementing these strategies.

To be successful, you should:

  • Have logged into umn.qualtrics.com and activated your account.
  • Have basic experience with Qualtrics – either through your own research or by taking our "Introduction to Qualtrics" Canvas module.

Qualtrics Tidbits: Best Practices to Improve Survey Accessibility

When designing and programming Qualtrics surveys, it is critical to consider how everyone in your population of recipients will experience the survey. For example, is the information in your survey able to be perceived by all participants, including those with visual or auditory limitations? Can all participants click on and navigate through the interface of the survey? Is content understandable to all of your participants? 

We will discuss visual and auditory accessibility, technological accessibility, and cognitive accessibility, and how to design content to fit all potential respondents' needs. This workshop will focus on implementing accessibility in Qualtrics, but the general principles will be applicable to all survey tools. 

This session is designed to be a 1.5 hour webinar/workshop with 30 minutes for general questions at the end.

This workshop will cover:

  • How to set up and test your survey with accessibility tools, such as screen readers;
  • Which question types meet accessibility standards and which to avoid;
  • Tips for formatting text, font size, color, and media to maximize accessibility;
  • Tips for developing instructions and text that are understandable to all of your participants. 

To be successful, you should:

  • Have logged into umn.qualtrics.com and activated your account.
  • Have basic experience with Qualtrics – either through your own research or by taking our "Introduction to Qualtrics" Canvas module.

Qualtrics Tidbits: Best Practices for Creating and Utilizing Qualtrics Workflows

Need to send emails to all of your participants after a survey? Want to receive notifications or regular updates about survey completions? Trying to pass information from one survey to another or to a Google doc? Qualtrics has tools, called Workflows, that can handle many of these tasks. This workshop will provide an overview of ways you can use Qualtrics Workflows to automate these survey tasks, and walk through how to set them up. 

This session is designed to be a 1.5 hour webinar/workshop with 30 minutes for general questions at the end.

This workshop will cover:

  • Tips for choosing the best workflow tool for your need;
  • How to automatically send emails to participants or yourself based on survey responses;
  • Passing information from one survey to another within Qualtrics, or between Qualtrics and other online tools;
  • Adding or updating contact information from a survey to a directory in Qualtrics.

To be successful, you should:

  • Have logged into umn.qualtrics.com and activated your account.
  • Have basic experience with Qualtrics – either through your own research or by taking our "Introduction to Qualtrics" Canvas module.

Qualtrics Tidbits: Best Practices for Analyzing Data in Qualtrics

Not everyone who conducts survey research has expertise with statistical software (e.g., R, Stata, SPSS, Python) and/or coding software (e.g., NVivo, Atlas.ti). For those looking for an alternative, Qualtrics’ built-in data analysis tools offer an easy-to-use platform for conducting simple analyses. 

This session is designed to be a 1.5 hour 30 minute webinar/workshop with 30 minutes for general questions at the end.

This workshop will cover:

  • Basic quantitative analysis using Stats iQ;
  • Simple qualitative analysis using Text iQ;
  • Adding and editing data in the Qualtrics “Data & Analysis: Data” section;
  • A brief overview of the “Results” and “Reports” sections;
  • When to use external data analysis software.

 

We don’t plan to go into detail about Crosstabs or Weighting, but we will be ready to answer questions on both sections.

To be successful, you should:

  • Have logged into umn.qualtrics.com and activated your account.
  • Have basic experience with Qualtrics – either through your own research or by taking our "Introduction to Qualtrics" Canvas module.

Survey of AI Tools for Research

As artificial intelligence (AI) and machine learning (ML) continue to evolve and influence research, understanding the scope, potential, and limitations of AI becomes crucial for students, practitioners, and academicians. This workshop is designed to provide a broad survey of the state-of-the-art, to provide an overview of current tools and frameworks, and to discuss questions worth considering when using AI in research. 

Beyond providing an overall survey of the state of AI, this session is aimed at sparking interest and guiding the development of more in-depth workshops on specific tools and methodologies. While ethical considerations will be briefly touched upon, this workshop is neither intended to guide or advocate a specific policy agenda, nor to promote a specific set of tools.

This workshop will cover:

  • An introduction to a range of AI tools, including machine learning frameworks, data analysis tools, with a special focus on generative AI (e.g., ChatGPT, Bard, LLaMA)
  • An overview of the spectrum of methodologies used to fine-tune AI models
  • A discussion of the benefits and challenges of AI in research
  • An open forum to brainstorm and guide the direction of future LATIS Research workshops on using AI in the social sciences and research writ large

To be successful, you should have:

  • A general interest in the application of artificial intelligence and machine learning in research

 

Advanced R: Writing and formatting in R Markdown/Quarto

If you are using R for your statistical analyses, you could be using it to write your dissertation or other custom formatted documents! This presentation will introduce Quarto, an extension of Markdown that allows custom formatting and publishing, and walk through how to use it in RStudio to create beautiful documents. We will walk through an example using formatting for a University of Minnesota dissertation, but the principles can be applied to many different journal templates, reports, or presentations. 

This workshop will cover:

  • The basics of Quarto and how to set up a Quarto document in R
  • Laying out a report structure with a title page, table of contents, abstract, index, and sections. 
  • Formatting tables and figures in R and referencing them in text
  • Using citations and a reference section  
  • A demonstration of how to back up and version everything with git and GitHub

To be successful, you should have:

  • Experience using R for data analysis
  • Familiarity with R markdown for report generation 
  • Updated versions of R and RStudio on your computer

Managing Data When you Graduate (Canvas Modules)

Research and creative work doesn't end with degree completion; however, access to many of the data storage tools and software that have supported that work changes when students become alumni. This asynchronous workshop will help graduate students navigate questions about whether they can take their data and materials with them when they leave the university, and if so, how to do it. This workshop is co-organized by the University Libraries. 

The workshop will cover:
  • The University policies that guide ownership of data
  • Access changes to storage, software, and services that happen upon graduation 
  • Strategies and tips for ensuring data are accessible and understandable long after graduation
 
Schedule a consultation to discuss:
  • How to make a plan to ensure a smooth transition for your data and materials between graduate school and your next endeavor
  • Specific advice and troubleshooting for your own research and situation. 
 
To be successful, you should:
  • Be a graduate student at the University of Minnesota at least a year into your program (it never hurts to plan early!), or who is nearing the end of your program. 
  • Have a research project (part of a dissertation or thesis) that has generated data or materials that you want to keep track of after you leave. This can include collaborative projects that will continue at UMN after graduation.

Introduction to Survey Sampling (Canvas Modules)

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.

 

Qualtrics Tutorials (Canvas Modules)

We have three 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. [Expected time: 1 hour]
     
  2. 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.). [Expected time: 35-45 minutes]
     
  3. 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 the using the survey flow, branching logic, embedded data, embedded media, piped text, “loop & merge”, integration with MTurk/Prolific, and more! In this module, you will watch a video walkthrough from our Fall 2021 workshop. [Expected time: 10-20 minutes for Canvas content; 2 hours of video content]

Working with Data in R - Tutorials (Canvas Modules)

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. 

Linux for Research Computing (Canvas Modules)

This asynchronous course is a gentle introduction to command line programming using Linux. It is designed for CLA researchers and students who need to use high performance computing resources for their work (for example, to run fMRI analyses, parallel computing, or large scale analyses), but have little to no experience with Linux. 

This course guides participants through:

  1. Connecting to the CLA compute cluster
  2. Navigating directory and file structure using the Linux command-line terminal
  3. Creating, modifying, and moving files using the Linux command-line terminal
  4. Submitting an interactive and a batch computing job and understanding when it is beneficial to use one or the other