set_coef: Set Coefficients for BKT Model

In BKT: Bayesian Knowledge Tracing Model

Set Coefficients for BKT Model

Description

This function sets or initializes the parameters of a Bayesian Knowledge Tracing (BKT) model. The user can manually specify the values for different parameters associated with specific skills.

Usage

set_coef(object, values)

Arguments

object	An object of the BKT model. This is the model for which the parameters will be set or initialized.
values	A list containing the skill names and their corresponding BKT parameters. Each skill should have its own list of parameters. The parameters can include 'prior', 'learns', 'forgets', 'guesses', and 'slips'. Example structure: list("skill_name" = list("learns" = ..., "guesses" = ...)).

Details

This function allows users to manually specify or update the parameters of a BKT model for different skills. The values should be provided as a named list, with each skill having its own sublist of BKT parameters. The function performs checks to ensure that the provided parameters are valid in terms of type, length, and existence.

Value

The updated BKT model object with the newly set coefficients.

Examples

# Initialize a BKT model
model <- bkt(seed = 42)

# Set custom parameters for a specific skill
model <- set_coef(model, list(
  "Plot non-terminating improper fraction" = list("prior" = 0.5, "learns" = 0.2)
))

# Fit the model with fixed parameters
result <- fit(model,
  forgets = TRUE,
  data_path = "ct.csv",
  skills = "Plot non-terminating improper fraction",
  fixed = list("Plot non-terminating improper fraction" = list("prior" = TRUE))
)

BKT documentation built on April 4, 2025, 12:20 a.m.