Adopt redesigned version of the lesson

.github/ISSUE_TEMPLATE/pilot_workshop_feedback.yml

@@ -0,0 +1,107 @@
+name: Pilot Workshop Feedback
+description: Share feedback from a pilot workshop of this lesson.
+title: "[Pilot workshop feedback]: "
+labels: ["type:discussion"]
+body:
+  - type: markdown
+    attributes:
+      value: |
+        Thank you for teaching this lesson and sharing feedback! 
+        Please answer the questions below, 
+        and note that feedback submitted with this form will be publicly visible.
+  - type: textarea
+    id: workshop
+    attributes:
+      label: 1. Workshop details
+      description: |
+        Tell us about the pilot workshop. 
+        When and where did it take place? Who hosted it? Who were the Instructors? 
+        How many Learners were there? What the background of the Learners e.g. their career stage, domain, prior knowledge of the lesson topic, etc?
+    validations:
+      required: true
+  - type: markdown
+    attributes:
+      value: |
+        ## Instructor Feedback
+  - type: textarea
+    id: instructor-up
+    attributes:
+      label: 2. What did the Instructors find worked well when teaching the lesson? 
+      description: |
+        What was good about the content and/or the design of the lesson?
+    validations:
+      required: true
+  - type: textarea
+    id: instructor-down
+    attributes:
+      label: 3. What did the Instructors find that could be improved in the lesson?
+    validations:
+      required: true
+  - type: textarea
+    id: instructor-other
+    attributes:
+      label: 4. Do the Instructors have any other feedback on the lesson?
+  - type: dropdown
+    id: time
+    attributes:
+      label: 5. Were the Instructors able to teach the whole lesson in the time available?
+      options:
+        - "Not sure"
+        - "Yes"
+        - "No"
+    validations:
+      required: true
+  - type: input
+    id: time-details
+    attributes:
+      label: 6. Tell us more about the lesson duration
+      description: |
+        If the Instructors were not able to teach the complete lesson in the time available, how much time did they have and how far through the lesson did they get? What content, if any, did they skip when teaching the lesson?
+        If they were able to teach the whole lesson, how much time did it take?
+        If an episode-by-episode breakdown of the time taken was recorded, please share it here.
+  - type: dropdown  
+    id: relative-evaluation
+    attributes:
+      label: 7. If the Instructors have also taught the official version of the _Data Analysis and Visualization with R for Ecologists_ lesson, how do they think this redesigned version compares to it?
+      options:
+        - "This version is no better or worse than the current official version."
+        - "This version is an improvement on the current version."
+        - "This version is worse than the current version."
+  - type: markdown
+    attributes:
+      value: |
+        ## Learner Feedback
+  - type: textarea
+    id: learner-feedback
+    attributes:
+      label: 8. Please share any feedback collected from Learners during the lesson pilot.
+      description: |
+        Feel free to exclude any feedback that is specific to the Instructors, venue, etc, or about other lessons taught at the workshop.
+  - type: markdown
+    attributes:
+      value: |
+        ## SQL databases and R
+        This lesson does not include content teaching interaction with relational databases from R.
+  - type: textarea
+    id: sql-feedback
+    attributes:
+      label: 9. How did the Instructors feel that this absence affected the overall usefulness of the lesson?
+  - type: dropdown  
+    id: sql-likert
+    attributes:
+      label: 10. How important do you think it is that content about R and databases be added back into this redesigned lesson?
+      options:
+        - "Very important"
+        - "Important"
+        - "Neutral"
+        - "Unimportant"
+        - "Very unimportant"
+  - type: markdown
+    attributes:
+      value: |
+        ## Conclusion
+  - type: textarea
+    id: other
+    attributes:
+      label: 11. Is there anything else you would like to tell us?
+

.gitignore

@@ -56,3 +56,4 @@ img/R-ecology-*.png
 code-handout.R
 # output from linkchecker
 link_res.csv
+!episodes/data

README.md

@@ -3,50 +3,29 @@
 [![Slack Status](https://img.shields.io/badge/Slack_Channel-DC_Ecology_R-E01563.svg)](https://carpentries.slack.com/messages/C9X9EC405)
 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3264888.svg)](https://doi.org/10.5281/zenodo.3264888)
 
-# Data carpentry: R for data analysis and visualization of Ecological Data
-
-**[This lesson will be replaced with a redesigned version on 8th July 2024](https://carpentries.org/blog/2024/03/dc-r-ecology-adoption/). If you plan to teach this lesson before that date, we recommend that you consider using the redesigned version instead. Feedback on the new version of the lesson and your experience teaching it is very welcome as issues on [the source repository](https://github.com/datacarpentry/R-ecology-lesson-alternative/).**
-
----
+# _Data Carpentry: R for data analysis and visualization of Ecological Data_
 
 This is an introduction to R designed for participants with no programming
 experience. It can be taught in 3/4 of a day (approximately 6 hours).
-The lesson starts with some basic information about syntax for the R programming
-language, the RStudio interface, and moves through to specific programming tasks,
-such as importing CSV files, the structure of data frame objects in R, dealing
-with categorical variables (i.e. factors), basic data manipulation
-(adding/removing rows and columns), and finishing with calculating summary
-statistics and a brief introduction to plotting.
-There is also a lesson on how to use databases from R that is intended to be
-taught after the SQL lesson, and ideally at the end of a Data Carpentry workshop.
+It is a redesigned version of [the original Data Carpentry lesson](https://doi.org/10.5281/zenodo.12684301). 
+
+The initial effort towards this redesign was done by [Michael Culshaw-Maurer](https://github.com/MCMaurer) in another repository in The Carpentries Incubator: https://github.com/carpentries-incubator/R-ecology-lesson (now archived). See Michael's notes while preparing the redesign in [the update_plans.md file](https://github.com/carpentries-incubator/R-ecology-lesson/blob/main/update_plan.md) of that repository.
+
+The lesson starts with information about the R programming language and the RStudio interface. It then moves to loading in data and exploring how to visualise it with ggplot2. The next episode takes learners through an exploration of data frames and some common data cleaning operations, before discussing vectors and factors. The final episode introduces the flow of data in R, and how to combine operations to select, filter, and mutate a data frame.
+
+## Providing feedback on this lesson
+
+If you teach this redesigned lesson, please [open an issue](https://github.com/datacarpentry/R-ecology-lesson/issues/new) on this repository to share your experience. 
 
 ## Prerequisites
 
 The lesson assumes no prior knowledge of R or RStudio.
 Learners should have R and RStudio installed on their computers. They will also
 need to be able to install R packages from CRAN, create directories, and
 download files.
-See [the lesson website](https://datacarpentry.org/R-ecology-lesson/index.html)
+See [the lesson website](https://datacarpentry.org/R-ecology-lesson/index.html#setup)
 for instructions on installing R, RStudio, and the required R packages.
 
-## Topics
-
-- [Before we start](https://datacarpentry.org/R-ecology-lesson/00-before-we-start.html)
-- [Introduction to R](https://datacarpentry.org/R-ecology-lesson/01-intro-to-r.html)
-- [Starting with data](https://datacarpentry.org/R-ecology-lesson/02-starting-with-data.html)
-- [Manipulating, analyzing and exporting data with `tidyverse`](https://datacarpentry.org/R-ecology-lesson/03-dplyr.html)
-- [Data visualization with `ggplot2`](https://datacarpentry.org/R-ecology-lesson/04-visualization-ggplot2.html)
-- [SQL databases and R](https://datacarpentry.org/R-ecology-lesson/05-r-and-databases.html)
-
-## Code handout
-
-There is a [code handout](https://datacarpentry.org/R-ecology-lesson/code-handout.R)
-that is intended to be distributed to the participants.
-This file includes some of the examples used during teaching and the titles of
-the section. It provides a guide that the participants can fill in as the lesson
-progresses. Participants can also source code from this file to avoid typos in
-more complex examples.
-
 ## Contributing
 
 Contributions to the content and development of these lesson are very welcome!
@@ -60,21 +39,9 @@ maintainers, or come chat with us on the
 If you don't already have a Slack account with the Carpentries, you can
 [create one](https://slack-invite.carpentries.org/).
 
-- Tobias Busch
-- Ana Costa Conrado
-- François Michonneau
-- Maneesha Sane
-- Brian Seok
-- Ashwin Srinath
-
-## Citation
-
-Please cite as
-
-> François Michonneau, Tracy Teal, Auriel Fournier, Brian Seok, Adam Obeng,
-> Aleksandra Natalia Pawlik, … Ye Li. (2019, July 1).
-> datacarpentry/R-ecology-lesson: Data Carpentry: Data Analysis and
-> Visualization in R for Ecologists, June 2019 (Version v2019.06.1). Zenodo.
-> [http://doi.org/10.5281/zenodo.3264888](http://doi.org/10.5281/zenodo.3264888)
+## Maintainers
 
+* [Nikki Gentle](https://github.com/gentlelab2016)
+* [Doug Joubert](https://github.com/doujouDC)
+* [Elif Dede Yildirim](https://github.com/elifdy)
 

config.yaml

@@ -11,29 +11,29 @@
 carpentry: 'dc'
 
 # Overall title for pages.
-title: 'Data Analysis and Visualisation in R for Ecologists'
+title: 'Data Analysis and Visualization in R for Ecologists'
 
 # Date the lesson was created (YYYY-MM-DD, this is empty by default)
 created: '2015-04-02'
 
 # Comma-separated list of keywords for the lesson
-keywords: 'software, data, lesson, The Carpentries'
+keywords: 'ggplot2, tidyverse, data-visualization, data-visualisation, data-wrangling, data-carpentry, R'
 
 # Life cycle stage of the lesson
 # possible values: pre-alpha, alpha, beta, stable
 life_cycle: 'stable'
 
-# License of the lesson materials (recommended CC-BY 4.0)
+# License of the lesson
 license: 'CC-BY 4.0'
 
 # Link to the source repository for this lesson
-source: 'https://github.com/datacarpentry/R-ecology-lesson'
+source: 'https://github.com/datacarpentry/R-ecology-lesson-alternative'
 
 # Default branch of your lesson
 branch: 'main'
 
 # Who to contact if there are any issues
-contact: 'curriculum@carpentries.org'
+contact: 'team@carpentries.org'
 
 # Navigation ------------------------------------------------
 #
@@ -58,29 +58,24 @@ contact: '[email protected]'
 # - another-learner.md
 
 # Order of episodes in your lesson
-episodes: 
-- 00-before-we-start.Rmd
-- 01-intro-to-r.Rmd
-- 02-starting-with-data.Rmd
-- 03-dplyr.Rmd
-- 04-visualization-ggplot2.Rmd
-- 05-r-and-databases.Rmd
+episodes:
+- introduction-r-rstudio.Rmd
+- visualizing-ggplot.Rmd
+- how-r-thinks-about-data.Rmd
+- working-with-data.Rmd
 
 # Information for Learners
-learners: 
+learners:
 - reference.md
 
 # Information for Instructors
-instructors: 
+instructors:
 - instructor-notes.md
 
 # Learner Profiles
-profiles: 
+profiles:
 
 # Customisation ---------------------------------------------
 #
 # This space below is where custom yaml items (e.g. pinning
 # sandpaper and varnish versions) should live
-
-
-url: 'https://datacarpentry.github.io/R-ecology-lesson'