Qualtrics for Research Data Collection

• Author: Nelson Roque, PhD
• [email protected]
• Director of the Context Lab at University of Central Florida

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Background

A reproducibility crisis (Ioannidis, 2005; Open Science Collaboration, 2015) has emerged as a threat to the scientific enterprise. Over the last decade I've engaged in learning opportunities to become proficient across topics including data wrangling and modeling of text, image, video, and eye-tracking data, as well as more recently sensor data, and look forward to training the next generation of scientists on code-based methods to apply in their research.

• Ioannidis, John P A. 2005. “Why Most Published Research Findings Are False.” PLoS Medicine 2 (8): e124.doi:10.1371/journal.pmed.0020124.
• Open Science Collaboration. 2015. “Estimating the Reproducibility of Psychological Science.” Science 349 (6251):aac4716–aac4716. doi:10.1126/science.aac4716.

Workshop Format

Qualtrics is a tool frequently used for research data collection through surveys. This workshop will teach survey design tips for reproducible survey research; and data wrangling of Qualtricsdata – the process of cleaning and transforming raw data into data suitable for analysis.

• Location: Zoom, Friday, March 3, 2023 3 p.m. to 4 p.m.
• Format: Live, with recordings available for later viewing.
• Register: Registration open until March 3rd, 2023 - click here to register
• Materials:
  • Data: see data folder of this repository.
    • Sample Survey: see https://ucf.qualtrics.com/jfe/form/SV_9RnmgYsz6coyhca?SOURCE=ucf_workshop_march2023
  • Slides: see slides folder of this repository.
  • Code: see scripts folder of this repository.
  • Sample Qualtrics Surveys: see sample_survey_exports folder of this repository.

Before the Workshop

1. Install R - Download R
2. Install RStudio - Download RStudio
3. Install packages for various analyses

```
install.packages(c('tidyverse', 'devtools', 'readr', 'tidytext', 'textdata',
'topicmodels', 'wordcloud', 'ggwordcloud', 'qualtRics'))
```

Learning Objectives

• Describe various principles, tools and techniques supportive of collecting data on Qualtrics.
• Develop a code-only pipeline to allow reproducibility of data prep and analyses.

Submit your questions

Do you have any questions about the workshop or related content? Submit your questions here