Scale scores on five self-regulated learning (SRL) constructs for 1,000 responses generated by ChatGPT to a validated SRL questionnaire. Part of a larger dataset comparing LLM-generated responses to human norms across seven large language models.
Format
A data frame with 1,000 rows and 5 columns:
- CSU
Numeric. Comprehension and Study Understanding scale mean.
- IV
Numeric. Intrinsic Value scale mean.
- SE
Numeric. Self-Efficacy scale mean.
- SR
Numeric. Self-Regulation scale mean.
- TA
Numeric. Task Avoidance scale mean.
Source
Vogelsmeier, L.V.D.E., Oliveira, E., Misiejuk, K., Lopez-Pernas, S., & 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. doi:10.1016/j.chb.2025.108769
Examples
net <- build_network(chatgpt_srl, method = "glasso",
params = list(gamma = 0.5))
net
#> Partial Correlation Network (EBICglasso) [undirected]
#> Sample size: 1000
#>
#> Weight matrix:
#> CSU IV SE SR TA
#> CSU 0 0 0 0 0
#> IV 0 0 0 0 0
#> SE 0 0 0 0 0
#> SR 0 0 0 0 0
#> TA 0 0 0 0 0
#>
#> Predictability (R²):
#> CSU 0.000
#> IV 0.000
#> SE 0.000
#> SR 0.000
#> TA 0.000
#>
#> Gamma: 0.50 | Lambda: 0.0517