Measuring Formative Learning Behaviors of Introductory Statistical Programming in R via Content Clustering
Understanding student learning is an open problem in the teaching of introductory statistical programming. Formative learning is observed when analyzing the
interaction between the learning environment and the student. This can be operationalized by viewing how students respond to the error messages they receive
while programming. Current California Common Core State Standards: Mathematics
(CA CCSSM) highlight perseverance as an overarching habit of a productive
mathematical thinker. Perseverance can be measured as a type of formative
learning by measuring the time and attempts that students use to correct errors.
The MOBILIZE project promotes statistical programming at the high school level
in the Los Angeles Unied School District while following the CA CCSSM. Logs
of high school student statistical programming during the 2013-2014 school year
were collected along with the errors that occurred. Using these logs, error blocks
were formed that follow a student's interaction with an error message. With the
error blocks we were able to observe perseverance by students on multiple days
of curriculum. Our findings suggest that there was an increase in perseverance,
because students increased in time spent and attempts made to correct an error
as the number of days of programming curriculum increased. Additionally, students who showed more perseverance were more likely to eventually fix an error.
Descriptive variables were explored to provide background for the variation in
student programming errors.