samplelkt

A dataset containing a small sample of participants
in a memory experiment.

datasets

Computes Logistic Knowledge Tracing ('LKT') which is a general method for tracking human learning in an educational software system. Please see Pavlik, Eglington, and Harrel-Williams (2021) <https://ieeexplore.ieee.org/document/9616435>. 'LKT' is a method to compute features of student data that are used as predictors of subsequent performance. 'LKT' allows great flexibility in the choice of predictive components and features computed for these predictive components. The system is built on top of 'LiblineaR', which enables extremely fast solutions compared to base glm() in R.

Philip I. Pavlik Jr.

Logistic Knowledge Tracing

Luke G. Eglington

samplelkt function

A data frame with 2074 rows and many variables:<dl>
<dt>Anon.Student.Id</dt>
<dd>unique identifier for each student</dd><dt>Duration..sec.</dt>
<dd>unique identifier for each student</dd><dt>KC..Default.</dt>
<dd>unique identifier for each student</dd><dt>Outcome</dt>
<dd>unique identifier for each student</dd>...</dl>

Format

Trial sequences for practice participants. — samplelkt

A data frame with 2074 rows and many variables:<dl>
<dt>Anon.Student.Id</dt>
<dd>unique identifier for each student</dd>

<dt>Duration..sec.</dt>
<dd>unique identifier for each student</dd>

<dt>KC..Default.</dt>
<dd>unique identifier for each student</dd>

<dt>Outcome</dt>
<dd>unique identifier for each student</dd>

...

</dl>

samplelkt: Trial sequences for practice participants.

Description

Usage

Arguments

Format