We have been teaching R in biosciences for the last many years (at least 6). 
The key approach we took is:

  1.  A taste and see workshop is ineffective and inefficient. Isolated sparks 
die.
  2.  It has to be embedded throughout – students need to see it as a key tool 
and as something they need to invest in learning.
  3.  It is taught enthusiastically with a view to the goal of enabling 
students to do bioscience effecttively.

So we moved across the board to doing all analysis in R, building in practicals 
that collected data that was relatively easy to process with R but harder with 
Excel or by hand, and to ensure that we flagged up to students where they would 
be using this in later levels to do the things they really were interested in.
We use a combination of approaches – on one side is the purely technical use. 
How to plot a graph, wrangle data, manage a data rich project etc.
On the other side is the analytical side which includes statistical theory and 
experimental design.  Tools we use:

  1.  Video led workshops -students work through a prerecorded workshop with 
TA/Instructors on hand to deal with problems and push students a bit further.
  2.  Live coding in lectures – talk through as code is written to e.g. build 
datasets, or repeat an analysis many times to create a t-distribution etc.
  3.  An expectation that this is the way it is done. Showing the code – 
notebooks/annotated scripts are preferred to miscellaneous console histories. 
This year I will be introducing the concepts of version control at a much 
earlier stage, previously only those doing the specialist bioinformatics 
projects were introduced to it but we have made a choice to make our data 
analysis workflows and recording more rigorous (as we have with lab journals in 
the wet lab.)
Happy to chat through and share our experiences. Don’t expect all (or even the 
majority) the students to like it in the first year or so but then when they 
want to do more advanced projects they discover they have the tools and skills 
to do so. And then they are very grateful in future years. They may only need 
it for their final year project, but that is not the time to be learning it 
from scratch (Cognitive Load and all that).

..d



From: [email protected] <[email protected]>
Sent: 23 August 2020 17:10
To: discuss <[email protected]>
Subject: Re: [cp-discuss] Re: Use of code in teaching undergraduates

To follow up on more of Ignasi's question, I believe it's a very good idea.  It 
will require more work preparing lessons and likely some "flipping" so that the 
students come prepared with at least a rudimentary knowledge of the language 
but as always, once the work is done updating to reuse is less work.
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