An example set of categorical learning-engagement trajectories used in
the transitiontrees examples and the “trajectories” vignette.
Each row is one learner, each column a time-step, and each cell the
engagement state at that step. Trailing NAs mark the end of a
trajectory. This wide character matrix is exactly the shape
context_tree() consumes.
Format
A character matrix with 138 rows (learners) and 15 columns
(time-steps). Three states: "Active", "Average",
"Disengaged".
Examples
data(trajectories)
dim(trajectories)
#> [1] 138 15
tree <- context_tree(trajectories)
tree
#> <transitiontrees> 145 nodes, depth <= 5, 3 states [unpruned]
#> alphabet : Active, Average, Disengaged
#> fit on : 136 sequences, 1870 observations
#> smoothing: floor(ymin=0.001, rule=interpolate) min_count = 5
#> (start) n=1870 -> Average (0.43)
#> |-- Active n=658 -> Active (0.70)
#> | |-- Active n=433 -> Active (0.79)
#> | | |-- Active n=316 -> Active (0.84)
#> | | | |-- Active n=240 -> Active (0.87)
#> | | | | |-- Active n=192 -> Active (0.87)
#> | | | | |-- Average n=17 -> Active (0.76)
#> | | | | `-- Disengaged n=7 -> Active (0.71)
#> | | | |-- Average n=37 -> Active (0.59)
#> | | | | |-- Active n=12 -> Active (0.83)
#> | | | | `-- Average n=18 -> Active (0.50)
#> | | | `-- Disengaged n=10 -> Active (0.90)
#> | | | `-- Active n=5 -> Active (0.80)
#> | | |-- Average n=70 -> Active (0.53)
#> | | | |-- Active n=22 -> Active (0.55)
#> | | | | |-- Active n=11 -> Active (0.64)
#> | | | | `-- Average n=10 -> Average (0.50)
#> | | | `-- Average n=37 -> Active (0.49)
#> | | | |-- Active n=15 -> Active (0.53)
#> | | | |-- Average n=15 -> Active (0.47)
#> | | | `-- Disengaged n=7 -> Average (0.57)
#> | | `-- Disengaged n=15 -> Active (0.67)
#> | | |-- Active n=5 -> Active (1.00)
#> | | `-- Average n=7 -> Average (0.57)
#> | |-- Average n=144 -> Active (0.50)
#> | | |-- Active n=53 -> Average (0.55)
#> ... 119 more nodes (use as.data.frame(x) or summary(x))