Speaker
Description
This workshop introduces participants to the workflow of processing, analyzing and visualizing log-data describing respondent interactions with web survey interface collected from the open and popular LimeSurvey survey platform, using the logLime R package (along with other packages: dplyr, ggplot2, ggdensity and gganimate). While discussing this process, participants will discover different types of recorded events and learn how they are related to respondents’ actions. Moreover, we will explore different ways in which log-data can be aggregated to obtain datasets and indicators describing either sequences of events or states at the predefined time points. We will discuss possibilities to use the logLime package with data collected from other sources and prospects for the future development of the package.
Outline:
1. Workflow for survey log-data collection, processing and analyzis (20 min.)
2. Importing log-data into R (10 min.)
3. Diagnosing problems and performing cleaning of the log-data (20 min.)
4. Computing process indicators including: 1) response editing, 2) hovering indices, 3) indicators based on item-level response times, 4) cursor moves indices, 5) survey navigation indices. (25 min.)
5. Coffee break (15 min)
6. Visualizing respondent behaviors with heatmaps, using packages ggplot2 and ggdensity (30 min.)
7. Drawing cursor traces and clicks, using package ggplot2 (20 min.)
8. Animating cursor traces and clicks, using packages ggplot2 and gganimate (10 mins.)
9. Preparing data for analysis using other software, including LogFSM, ProcData or mousetrap R packages (10 min.)
10. Prospects for adaptation to other survey platforms (5 min.)
11. Q&A (15 min.)
If you used AI tools or services to support the preparation of this submission, please state the name and reason for using each of them.
No AI tools/services were used.
Target audience (only for tutorials)
survey researchers and methodologists, specifically researchers, students and practitioners interested in exploring opportunities to collect and use log-data in their own studies
Learning goals (only for tutorials)
- familiarizing participants with the types of log-data that can be collected during online surveys,
- developing the ability to read, clean, transform, analize and visualize log-data from online surveys in R, using packages logLime, dplyr, ggplot2, ggdensity and gganimate
Additional Material or Paper
Materials will be adapted from the logLime package vignettes:
https://github.com/tzoltak/logLime/blob/main/vignettes/using-logLime.Rmd
https://github.com/tzoltak/logLime/blob/main/vignettes/drawing-log-data.Rmd
The extended version of the tutorial was given during the IMPS 2023 conference (https://www.psychometricsociety.org/imps-20234)
The outline of the solution was presented during the ESA RN21 Mid-term conference 2022 at Salamanca (https://www.researchgate.net/publication/368328379_Loglime_Workflow_for_Log-data_Collection_and_Processing#fullTextFileContent)
Prerequisites (only for tutorials)
Basic R knowledge, including simple data frame transformations (preferably with dplyr) and using pipe operator. Familiarity with ggplot2’s way of creating graphs will be helpful. Laptop with R installed will be needed.
| Keywords: Please list up to 5 keywords to help us find the right session for your contribution. | log-data, online surveys, ux, visualization |
|---|---|
| Virtual Option | This submission is for onsite presentation only |
| Video Recording | Video sharing is fine |
| The author(s) agree(s) to take responsibility and be accountable for the contents of the submission and is/are authorized to present it. | Confirm |
| Interested in serving as reviewer? | tomek@zozlak.org |