The aim of this study was to examine the validity and feasibility of sentence transcription testing (STT) for the purpose of examining the interplay between verbal working memory and central processing. The general area of interest is to understand working memory as a dynamic system that involves the management and integration of information from several temporal distances. Due to the world-wide conditions at the time this study was conducted (2020), the testing was online and computerized, which severely limited the controllability of the procedure leading to a high amount of exclusions and dubious results. The testing of 17 subjects, 9 females, 8 males with the average age of 30.5 (SD = 9.5) yielded mixed results, excluding gender, impulsivity and age as likely factors for the variance. Following these results, a post hoc analysis was added to interpret if transcription data has validity as a tool for observing effects of interference on memory recall and the task at hand. This analysis did reveal patterns that reinforce the view of language processing as a multimodal task. The type of errors seems to follow tendencies of primacy, recency and availability, as well as proactive and retroactive interference. These tendencies of memory recall seem to work in unison or is a manifestation of syntactic, lexical, and presumably semantic processing and can be used to measure individual differences in language processing and the tendency to linguistically “fill in the gaps”. The variation seen within the sample does make transcription testing appealing for further studies. The main variance within the sample can be described as replacing words with other previously attended to information, and or forgetting words during transcription. These tendencies, might reveal properties about the interaction between executive function (EF) and verbal working memory (V-WM) as a source of individual difference. However, more validation studies are proposed for weaving out factors that might skew the results in this type of testing and modelling.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-201649 |
| Date | January 2021 |
| Creators | Bou Aram, Sinal |
| Publisher | Linköpings universitet, Institutionen för beteendevetenskap och lärande |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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