The effect of multi-modal learning in Artificial Grammar Learning Task

Streszczenie
The aim of the following study was to answer the question whether multimodal grammar learning would improve classification accuracy as compared with a unimodal learning. To test this hypothesis, an experimental procedure was constructed based on the research conducted by Conway and Christiansen [2006]. Their study regarded modality-specific Artificial Grammar Learning task (AGL). The grammatical sequence that was used in the study presented here was based on an algorithm with a finite number of results. Two additional sets of ungrammatical sequences were generated in a random manner. One of them was used in the learning phase in the control group while the second one, in the classification phase, in both, control and experimental groups. The obtained results showed that participants performed classification task above the chance level. These findings supported the hypothesis, which stated that grammar learning would occur [Conway and Christiansen, 2006; Reber, 1989]. We did not observe any effect regarding the hypothesized accuracy enhancement in a multimodal learning condition.
Autorzy
K. Rączy, Z. Skóra, M. Szul
Kontakt z autorami
raczy.katarzyna@gmail.com
Affiliacje
Uniwersytet Jagielloński
Numer
8/2015
Strony
91–98
DOI
10.4467/20843895RK.14.009.4258
Slowa kluczowe
implicit learning, artificial grammar learning, multimodal learning