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.
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