srl: Self-regulated learning scores simulated by a large language...
In latents: Multilevel Latent Profile, Class and Transition Models

srl	R Documentation

Self-regulated learning scores simulated by a large language model

Description

Scores on five constructs of the Motivated Strategies for Learning Questionnaire (MSLQ) for 300 simulated respondents. Each score is the mean of the construct's Likert items, on a scale from 1 to 7. The responses were generated by a large language model (GPT), not collected from students: they come from a study of how language models answer psychological surveys, and are used here because they are a well-structured, openly shareable cross-sectional example. They should not be read as evidence about students.

Usage

srl

Format

A data frame with 300 rows and 5 columns:

cognitive_strategies: cognitive strategy use
intrinsic_value: intrinsic value of the course
self_efficacy: self-efficacy
self_regulation: self-regulation
test_anxiety: test anxiety

Details

The five constructs are strongly correlated (about 0.8, except test anxiety), which makes the data a good illustration of how the choice of covariance structure shapes a latent profile analysis.

Source

The SRL_GPT data of the psychnets package, with descriptive column names. Saqr, M. (2025). Delving into the psychology of machines: Exploring the structure of self-regulated learning via LLM-generated survey responses. Computers in Human Behavior, 173, 108769. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.chb.2025.108769")}