Assessing serial recall as a measure of artificial grammar learning
2024

Measuring Learning of Artificial Grammar with Visual Recall

Sample size: 65 publication 10 minutes Evidence: moderate

Author Information

Author(s): Holly E. Jenkins, Ysanne de Graaf, Faye Smith, Nick Riches, Benjamin Wilson

Primary Institution: University of Oxford

Hypothesis

Can serial visual recall effectively measure the learning of complex artificial grammar?

Conclusion

The study found no evidence of artificial grammar learning in the Visual Serial Recall task, but did replicate learning effects in reflection-based measures.

Supporting Evidence

  • Participants showed no significant learning in the Visual Recall task.
  • Learning effects were observed in the Grammaticality Judgement and Sequence Completion tasks.
  • Methodological factors may have influenced the effectiveness of the Visual Recall task.

Takeaway

The researchers wanted to see if people could remember patterns in a sequence of shapes without thinking about the rules, but they found that this method didn't work as well as they hoped.

Methodology

Two experiments were conducted using a visual serial recall task alongside reflection-based grammaticality judgement and sequence completion tasks.

Limitations

The Visual Recall task may not effectively measure learning of more variable relationships due to methodological factors.

Participant Demographics

Participants included native English speakers, with 22 adults in Experiment 1 and 43 in Experiment 2, aged around 30 years.

Statistical Information

P-Value

p<0.001

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.3389/fpsyg.2024.1497201

Want to read the original?

Access the complete publication on the publisher's website

View Original Publication