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We are recognizing the value of teaching statistics simultaneously with the programs that will provide plentiful opportunities to our students. However, programs such as R require basic levels of programming that most life science undergraduates do not have. 

Both statistics and programming are hard subjects that present a high intrinsic cognitive load. While presenting the material without any consideration or knowledge of the structure of information may indeed pose a higher extraneous cognitive load, cognitive load theory provides a unique set of instructional designs and procedures that can be applied in the development of lessons that reduces the overall additive effect on the working memory of the students.

I used the framework for instructional design provided by cognitive load theory to design a series of homework assignments to teach R in statistics courses. I tested the effectiveness of these assignments using student grades and surveys. This research is now published at CBE- Life Science Education. 

This research is supported by the Public Scholar Initiative at UBC and the CIRTL network

You can find our event on engaging education for the public good here.