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Going beyond our means: A proposal for improving psycholinguistic methods
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Abstract:
Psycholinguistics is the research of language in the mind: The architecture of storing the different components of language in our memory, and the ways we access that knowledge when processing and producing language. Psycholinguists usually conduct quantitative experimental research in which certain standards of experimental design, data collection, analysis and presentation are preferred. Established methods are used to create and report research that will be published, in the hopes of advancing our knowledge. We often rely on existing methodologies and do not scrutinize the assumptions underlying those methodologies. When examined and addressed, our research can become better, more replicable, and have better validity. This two-tiered dissertation proposes three separate ways to improve psycholinguistic designs and analyses: 1) multi-measure designs, allowing for the collection of converging data from several sources; 2) incorporating qualitative data in quantitative designs – providing for tests of assumptions, converging evidence, and fine-grained information about quantitative data; 3) going beyond averaged data – averaging data over participants and stimuli is common practice in empirical research, but averaging can obscures individual differences and important trends in the data. I conduct three separate studies, the first two studies using questionnaires, response time measures, ERP data, unsupervised learning algorithms and qualitative responses to investigate individual differences in the processing of underinformative ‘some’ scalar implicatures (e.g. Some cats are mammals). The third study uses acceptability judgements, response-time measures, eye-tracking data and qualitative responses to examine the depth of processing in comparative illusion sentences (e.g. More people have been to Russia than I have). The methodologies, analyses and findings of these three studies demonstrate how the proposed methodological improvements can be implemented. Moreover, I illustrate that by following such steps psycholinguists can collect data that are more reliable and uncover behavioral patterns and individual differences that would otherwise remain obscured.
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Keyword:
comparative illusions; ERP; eye-tracking; individual differences; Language processing; multi-measure design; qualitative data; scalar implicatures; unsupervised learning algorithms
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URL: http://hdl.handle.net/2142/112970
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