Instructor Notes
General Teaching Approach
This course follows the Carpentries live-coding pedagogy: the instructor types code live while participants follow along. Avoid slides for code — always demonstrate in RStudio.
Key principles: - Start from what they know: Every R operation is introduced alongside its SPSS equivalent. Use SPSS terminology first, then introduce the R term. - Wow first, skills second: Episode 1 is pure motivation. Show impressive things before asking anyone to type. - Sticky notes: Use colored sticky notes (or digital equivalents) for real-time feedback. Green = I’m following. Red = I need help. - Helpers: Aim for 1 helper per 5-8 participants to assist with individual issues without stopping the class.
Session Structure
Session 1 (5-6 hours with breaks)
| Episode | Time | Notes |
|---|---|---|
| 01 - The Case for Switching | 45 min | Instructor demo only, no participant coding. Demo is the UA SIDS
reference-list pull from island-research-reference-data
(see Episode 1 instructor block). Also shows the Xander Bogaerts
capstone HTML as the Friday-afternoon target — rendered version at
episodes/files/xander-bogaerts-report.html and source at
episodes/files/xander-bogaerts-report-template.Rmd. |
| Break | 15 min | |
| 02 - Your First R Session | 90 min | First hands-on. Go slow. Many will struggle with typos. The “Before
you import — set up your workshop folder” subsection is a deliberate
whole-room synchronized moment: project the download links on the
screen, wait for green stickies in the Files pane before typing
read_csv(). |
| Break | 15 min | |
| 03 - Data Manipulation | 90 min | The pipe operator is the key “aha” moment |
| Break | 15 min | |
| 04 - Visualization | 60 min | End on a high — everyone leaves with a beautiful chart |
| Wrap-up + homework brief | 15 min | Project the homework page on the screen. Walk through the four-step assignment out loud. Tell participants the page URL is bookmarked under “For Learners → Homework brief” on the course site so they can open it on any device overnight. Emphasise: 30–60 minutes is enough, do not attempt R Markdown yet (that is Day 2). Bring the script to Day 2 open lab. |
Session 2 (5-6 hours with breaks)
| Episode | Time | Notes |
|---|---|---|
| Review and troubleshooting | 30 min | Address questions from between-session practice |
| 05 - Statistical Analysis | 120 min | Core for survey researchers. The normality-testing section (histogram, Q-Q plot, Shapiro-Wilk, robustness note) maps directly onto the SPSS Explore output most participants will recognise. Take your time. |
| Break | 15 min | |
| 06 - Reproducible Reporting | 60 min | R Markdown is often the biggest “wow” for SPSS users. Ends with the
Xander Bogaerts capstone section that Episode 1’s opening teased — walk
through the template at
episodes/files/xander-bogaerts-report-template.Rmd if it
has landed; otherwise describe its structure using the scaffold in the
episode. |
| Break | 15 min | |
| 07 - Where to Go from Here | 55 min | End with practical next steps. The new UA datasets subsection
(CAS_election_data and island-research-reference-data) is a chance to
live-demo read.csv() straight from a raw GitHub URL — most
SPSS users have never seen data load over HTTPS without a manual
download. |
Per-episode scene transitions
Each episode opens with one atmospheric scene image at the top of the
page (fig/scene_1.jpg through scene_7.jpg) and
a one-line quip caption. The captions do most of the work; instructors
who prefer to start straight from the first heading should feel free to.
For instructors who want a single-beat acknowledgment when arriving at
each new episode, the lines below match the captions in tone and feed
naturally into the episode’s opening content. They are optional.
| Ep | Caption on page | Optional transition line |
|---|---|---|
| 1 | One road costs you a license fee. The other one costs you a learning curve. | (Episode 1 opens with the workshop’s full opening sequence; no separate transition needed.) |
| 2 | The iguana is optional. The coconut water is not. | “We’re at the bar, R is open, the iguana is doing iguana things. Time to type something.” |
| 3 | You can’t cook without ingredients. You can’t wrangle without verbs. | “Three jars on the counter today: filter, select, mutate. Everything else in dplyr is a variation on those three.” |
| 4 | SPSS gives you a chart. ggplot2 gives you a language. | “ggplot is grammar, not buttons. By the end of this episode you’ll be writing sentences.” |
| 5 | Same tests, fewer menus, more crabs. | “The tests you know from SPSS — t-test, ANOVA, chi-square, regression — are all here. The crabs are the new part. Trust the crabs.” |
| 6 | Your supervisor changed the sample. Again. Good thing you only need one button. | “This is the moment R Markdown earns the price of admission. One button, new data in, finished document out.” |
| 7 | You learned the basics. The map has a lot more islands. | “The basics are behind you. The next forty-five minutes are about where to go from here, with islands marked for you to chart.” |
Pick one beat, deliver it, move into the page’s first heading. Do not stack a second sentence on top.
Common Issues
- Installation problems: The pre-course installation clinic should catch most of these. Have a USB drive with R and RStudio installers as backup.
- Typos: SPSS users are not used to typing commands. Expect many syntax errors. Normalize this — “error messages are how R talks to you.”
- Parentheses and quotes: The most common beginner errors. Show how RStudio auto-completes these.
-
Loading packages: Participants will forget
library(). Remind them at the start of each episode.
Local Data Notes
The course uses Dutch Caribbean datasets to keep examples relevant: -
CBS Aruba tourism and CPI data (Excel downloads from cbs.aw) - World
Bank indicators via the WDI package (used in Episode 7
only; Episode 1’s demo was switched to the SIDS reference list below
after the WDI tourism series was found missing for 2019-2023) - CBS
Netherlands BES island data via cbsodataR -
CAS_election_data — Aruba, Curacao, Sint Maarten
election results 1985-2025 (tidy CSV at
github.com/University-of-Aruba/CAS_election_data). Used in Episode 7. -
island-research-reference-data — country reference list
with SIDS, SNIJ, and World Bank classifications (CSV at
github.com/University-of-Aruba/island-research-reference-data). Used in
Episodes 1 and 7. A backup copy is committed at
episodes/data/countries_backup.csv for offline
fallback.
Prepare cleaned versions of these datasets in the
episodes/data/ folder before the course. Test all data
downloads — URLs and APIs can change.
Note on the elections example
The Episode 7 election-data example deliberately groups MEP and AVP
together versus all other parties, rather than singling out one party.
Aruba’s two-party dynamic means filtering on party == "MEP"
(or "AVP") on its own can read as partisan bias in a
publicly distributed course. If extending the example live, default to
the same grouped framing or to all-parties views (e.g. all parties for
the most recent election, or vote share over time). If a participant
asks why we don’t filter to one party, this is the reason worth naming
briefly: it is a small editorial choice that protects the course and the
network’s neutrality.
Train-the-Trainer
This course is designed for replication. If you are adapting it for another island or institution: 1. Replace datasets with locally relevant equivalents 2. Adjust the SPSS operations covered based on your pre-course survey results 3. Keep the “wow first, skills second” structure 4. All materials are CC-BY 4.0 — please attribute the DCDC Network