The effect of multi-modal learning in Artificial Grammar Learning Task
cytuj
pobierz pliki
RIS BIB ENDNOTEChoose format
RIS BIB ENDNOTEThe effect of multi-modal learning in Artificial Grammar Learning Task
Publication date: 23.11.2015
Yearbook of Cognitive Science, 2015, Volume 8, pp. 91 - 98
https://doi.org/10.4467/20843895RK.14.009.4258Authors
The effect of multi-modal learning in Artificial Grammar Learning Task
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.
Information: Yearbook of Cognitive Science, 2015, Volume 8, pp. 91 - 98
Article type: Original article
Titles:
The effect of multi-modal learning in Artificial Grammar Learning Task
The effect of multi-modal learning in Artificial Grammar Learning Task
Institute of Psychology, Jagiellonian University in Cracow, ul. Ingardena 6, 30-060 Kraków
Jagiellonian University in Kraków, Gołębia 24, 31-007 Kraków, Poland
Jagiellonian University in Kraków, Gołębia 24, 31-007 Kraków, Poland
Published at: 23.11.2015
Article status: Open
Licence: None
Percentage share of authors:
Article corrections:
-Publication languages:
PolishView count: 2192
Number of downloads: 1386