generate_activity: Clean and merge MAP, Khan, and item difficulty data.

In kimjam/khanELO: Utlizes MAP data and Khan Academy data to update items and students using ELO Rating System

Description

Clean and merge MAP, Khan, and item difficulty data.

Usage

generate_activity(map, khan_exers, khan_states, colnames = c("studentid",
  "testritscore", "teststartdate"), numeric_sid = TRUE,
  estimate_type = "tree", inhouse_path = NA, verbose = TRUE)

Arguments

map	Dataframe containing student MAP test data provided by NWEA. Looks like dataframe found in data(sample_map_data)
khan_exers	Dataframe containing student data for Khan Academy excises. Looks like dataframe found in data(simulated_khanmath)
khan_states	Dataframe containing student state change data for Khan Academy exercises. Looks like dataframe found in data(simulated_khanstate)
colnames	vector of map colnames that contain studentid, rit score, and test date. Default is c('studentid', 'testritscore', 'teststartdate')
numeric_sid	Conditional indicating whether studentid is numeric or not. Default is TRUE
estimate_type	String to indicate which type (NWEA, tree, inhouse) of Khan item estimate to use. Defaults to tree (more coverage than nwea). If 'inhouse' is chosen, user must provide filepath to csv of inhouse estimates containing exercise title and estimated difficulty. Can be created using update_diff() function.
inhouse_path	filepath indicating where inhouse estimates are kept
verbose	Default is TRUE to print status updates.

Value

Returns list of dataframes. Each dataframe will contain a student's Khan Activity as well as his / her MAP test history.

kimjam/khanELO documentation built on May 20, 2019, 9:40 a.m.