Retrieves subjects with the lowest meaning accuracy percentages from review statistics, sorted by accuracy from worst to best. Useful for identifying subjects that need extra practice.
Usage
wk_get_mistakes(
n = 5,
reload = FALSE,
percentage_threshold = NULL,
include_reading_accuracy = TRUE
)Arguments
- n
Integer indicating how many subjects to return (default: 5)
- reload
Logical indicating whether to reload subjects data from API (default: FALSE)
- percentage_threshold
Optional numeric threshold to filter subjects with accuracy below this percentage
- include_reading_accuracy
Logical indicating whether to include reading accuracy in results (default: TRUE)
Value
Data frame with columns: subject_id, characters, meanings, level, object_type, meaning_percentage, reading_percentage (if available)
Examples
if (FALSE) { # \dontrun{
# Get 5 worst performing subjects
mistakes <- wk_get_mistakes(5)
print(mistakes)
# Get 10 subjects with less than 60% accuracy
bad_subjects <- wk_get_mistakes(10, percentage_threshold = 60)
# Force reload review statistics
fresh_mistakes <- wk_get_mistakes(5, reload = TRUE)
} # }