Remove handout

config.yaml

@@ -71,10 +71,10 @@ episodes:
 # Information for Learners
 learners: 
 - reference.md
-- R-handout.Rmd
 
 # Information for Instructors
 instructors: 
+- instructor-notes.md
 
 # Learner Profiles
 profiles: 

index.md

@@ -8,8 +8,10 @@ less time, and with less pain. The lessons below were designed for
 those interested in working with social sciences data in R.
 
 This is an introduction to R designed for participants with no
-programming experience. These lessons can be taught in a day (~ 6
-hours). They start with some basic information about R syntax, the
+programming experience. These lessons can be taught in a half-day,
+full-day, or over a two-day workshop (see
+[Instructor Notes](https://datacarpentry.org/r-socialsci/instructor/instructor-notes.html)).
+They start with some basic information about R syntax, the
 RStudio interface, and move through how to import CSV files, the
 structure of data frames, how to deal with factors, how to add/remove
 rows and columns, how to calculate summary statistics from a data

instructors/instructor-notes.md

@@ -2,7 +2,9 @@
 title: Instructor Notes
 ---
 
-## Dataset
+## Narrative
+
+### Dataset
 
 The data used for this lesson are a slightly cleaned up version of the
 SAFI Survey Results available on GitHub. The original data is on
@@ -11,8 +13,6 @@ SAFI Survey Results available on GitHub. The original data is on
 This lesson uses `SAFI_clean.csv`. The direct download link for the data file is:
 [https://raw.githubusercontent.com/datacarpentry/r-socialsci/main/episodes/data/SAFI_clean.csv](https://raw.githubusercontent.com/datacarpentry/r-socialsci/main/episodes/data/SAFI_clean.csv).
 
-## Narrative
-
 ### Before we start
 
 - The main goal here is to help the learners be comfortable with the RStudio
@@ -23,7 +23,13 @@ This lesson uses `SAFI_clean.csv`. The direct download link for the data file is
   sure that learners are in the correct working directory, and that they create
   a `data` (all lowercase) subfolder.
 
-### Intro to R
+### Introduction to R
+
+- The main goal is to introduce users to the various objects in R, from atomic types
+  to creating your own objects.
+- While this epsiode is foundational, be careful not to get caught in the weeds as the
+  variety of types and operations can be overwhelming for new users, especially before
+  they understand how this fits into their own "workflow."
 
 ### Starting with data
 
@@ -63,6 +69,29 @@ The two main goals for this lessons are:
 - Note that his lesson was community-contributed and remains a work in progress. As such, it could
   benefit from feedback from instructors and/or workshop participants.
 
+## Lesson Plans
+
+The lesson contains much more material than can be taught in a day. Instructors will 
+need to pick an appropriate subset of episodes to use in a standard one day course.
+
+Suggested path for half-day course:
+
+- Before we Start
+- Introduction to R
+- Starting with Data
+
+Suggested path for full-day course:
+
+- Before we Start
+- Introduction to R
+- Starting with Data
+- Data Wranging with dplyr
+- (OPTIONAL) Data Wrangling with tidyr
+- Data Visualisation with ggplot2
+
+For a two-day workshop, it may be possible to cover all of the episodes. Feedback from
+the community on successful lesson plans is always appreciated!
+
 ## Technical Tips and Tricks
 
 Show how to use the 'zoom' button to blow up graphs without constantly resizing