| delay_factor {CurricularAnalytics} | R Documentation |
Calculate delay factor
Description
A helper function for calculating the delay factor for each node and the total delay factor of a curriculum graph.
Usage
delay_factor(node_list, edge_list)
Arguments
node_list |
Dataframe with an 'id' column for each node and a 'term' column specifying which term the course is to be taken in. |
edge_list |
Dataframe with two columns 'from' and 'to' specifying
directed edges starting at 'from' nodes directed towards 'to' nodes. Entries
must use node ids from |
Details
The delay factor of a course is the longest path the nodes finds itself on.
More formally the delay factor of a node v_k is given by
d_c(v_k)=\underset{i,j,l,m}{max}\left\{\#\left(v_i
\overset{p_l}{\to} v_k \overset{p_m}{\to} v_j
\right)\right\}
The delay factor of an entire curriculum graph G_c is defined as
d(G_c)=\sum_{v_k \in V}d_c(v_k)
Value
A list that contains the following:
bynode |
A dataframe containing the delay factor of each node |
total |
The total delay factor of the curriculum graph |
Author(s)
Daniel Krasnov
References
Heileman, Gregory L, Chaouki T Abdallah, Ahmad Slim, and Michael Hickman. 2018. “Curricular Analytics: A Framework for Quantifying the Impact of Curricular Reforms and Pedagogical Innovations.” arXiv Preprint arXiv:1811.09676.
Examples
edge_list <- data.frame(from = c(1, 3), to = c(3, 4))
node_list <-
data.frame(
id = 1:4,
label = c("MATH 100", "DATA 101", "MATH 101", "MATH 221"),
term = c(1, 1, 2, 2)
)
df_list <- delay_factor(node_list,edge_list)
print(df_list)
# Output:
# $bynode
# id df
# 2 1 3
# 3 2 1
# 4 3 3
# 5 4 3
# $total
# [1] 10