Language and Psycholinguistics Method for Research - Essay Example

Lexical Decision Lexical decision is the process of identifying whether a particular set of alphabets are words or non words. Though it might seem a simple task, several people confuse between actual words and similar set of alphabet arrangements when they are asked to give quick responses. Lexical Decision is the process of studying the visual word recognition skills (Harley, 2008). The ability to take quick lexical decision helps us to understand the cognitive mechanism behind reading skills of humans. It also helps us to determine the role of non words in making a person identify a similarly pronounced related word. A fully fledged research was carried out among 28 students in this study. Our results states phonological awareness plays an important role in word reading and the non words arranged similar to the actual words do stimulate the correct word reading extensively. Introduction We all read several words daily, from film posters to the major office documents. The ability to understand words is important in every persons life as it is an important factor affecting ones knowledge. Lexical decision checks the ability of the person to differentiate between words and non words and identify phonological and semantically primed words. There are a series of experiments conducted to test a person’s lexical decision. This results correlated are used for several different purposes from understanding how people with disabilities in hearing and the normal humans intercept words to determining how the people lexical decision ability influences their reading skill. Literature Review Human brain processes millions of words every day. How does it identify the meaning of each different word? Collins and Loftus (1975) stated knowledge is stored and processed in the form of nodes. A semantic network stores millions of nodes. One stimulus arouses several related nodes. For example when a person hears the word "car" he automatically associates it with related nodes like "driver", "road" and "speed" rather than other totally different nodes like "dress" and "television". The experiments carried out by various people like McClelland and Rumelhart (1986) have confirmed this concept of relative nodes awakening. The process is termed as "Priming". The researchers also proposed the Parallel Distributed Processing model to enhance the studies about priming. The concept "Priming" helps us understand the mechanism behind understanding words. Pamela Markek says "a concept is represented by a pattern of activation, rather than by activation of a single node". A person’s brain interprets full word rather than alphabets. For example, "chair" and "chiar" will seem same to them most of the time, unless he is a strict elementary school teacher. Connectionism uses various physiological principles related to neural circuits, and distributed coding. Distributed memory models give solid proof regarding better understanding of semantic priming (Masson, 1995). Though some of the theories are controversial, there is a unanimous opinion that relatives nodes regarding words are triggers by a common link. The early evidence for this node concept organized within a semantic network used experiments which measured the response time necessary to take lexical decisions (Meyer and Schvaneveldt, 1971). Their experiment concluded the response time to relate words were much faster than the response time taken for unrelated words. However, the time differed according to individual capability too as the response time was triggered from each person’s mental database. Gernsbacher and Faust (1991) used ambiguous words in sentences to measure the response time. They concluded people with higher comprehension skills fared better than others in this test. Similarly, the length of the words also slows down the time of the response (Grieco, Betella, Conti, Orioli, and Casco, 2004). Rossell, Bullmore, Williams, and David (2001) proved through their experiment different parts of the brain responds to immediate responses and long delay lexical decision. They used functional magnetic resonance imaging (fMRI) to register the same. Further experiments also proved various areas of the brain are used to retrieve the dominant and subordinate meanings for the same words pertaining to the sentences or situations they are used. Extensive research regarding the link between lexical decision capacity of the normal people and the ones with disability were conducted all through the world. Experiments conducted on open class items and closed class items show the frequency response for both are nearly the same without much difference (Seguit et al., 1982). Collins and Loftus (1975) developed the Quillians theory further to create a complicated concept which can be used for human semantic processing in a computer. The use of phonology is generally underrated in most of our schools and language classes. There is a common misconception that phonological features have little importance on a persons reading skill. But, this was proved wrong by Orden (1987) through his homophone experiment implying the importance of phonological studies. Hypothesis The non words sounding or spelled similar to words play a significant role in awakening the nodes related to the actual word. The study about a person’s capacity in deciphering phonological vs semantic words highlights key points about the cognitive mechanism of reading. Methodology The experiment undertaken by the researchers is inspired by the Meyer and Schvaneveldt (1971) studies. The focus group people have to choose whether the given set of alphabets is words or non words. The experiment measures the time course response activation. There are several non words inserted among the common two letter strings. These non words both stimulate the link related to the common words as well confuse and misguide the users regarding their authenticity or existence. The study helps in understanding the mechanism of interpreting words better and the role non words play in making the brain recognize actual words. 28 students participated in the experiment. The responses they gave were yes and no. The experiment had 50 pair of words. Each word was used 28 times. 16 pairs of not associated words, 7 pairs of associated words, 13 pairs of non words, 7 not word – word combination and 7 pairs of word – not word combination was used. Data Collection The experiment selected the words based on the rules and regulations formed by Nelson, McEvoy and Schreiber (1998).The focus group people were given a set of two letter strings. They should decide whether it is a "word" or a "non word" in the quickest possible time. They should press Y or N keys to indicate their response. The software Superlab helps in extracting the results into the excel sheet without any manual work. Each person has to complete a particular set of trials fulfilling 6 to 12 conditions. This experiment is 2 (Stimuli type: word or non-word) x 2 (Stimuli relationship: related or unrelated). The interstimulus interval and the errors made were also recorded in a separate column. The participants give responses automatically. There is no time to get assistance or prepare further to the test. Their response should not be labored and instant. Instinctive response is important to measure the comprehensive capacity of a person. Data Analysis The data was retrieved from the software Superlab into the Excel sheet. It has total 12 columns. The first one starts with serial number and proceeds to indicate the group the focus group belongs to, their code, block, id, word pair, authenticated data, the response, key pressed, whether it is right or wrong, errors made and the time stimulus. Results The results showed longer words take more interstimulus time to respond and tend to show more errors. Related words like “door – handle” and “knife – fork” tend to get perfect and quick response. Unfamiliar and unrelated words garnered more errors. The phonological awareness or rapid naming did not have any significant differences. However pressing the person to give faster responses from time to time did make them do more errors especially when it comes to non-existing similar sounding words. Retrieving the data was made amazingly simple through the Superlab software. Understanding the usage of the software and feeding data into it was a bit hard in the beginning. But, once the technique was understood it made the process of research much easy. The simple aim of the experiment was to check the influence of non words in identifying actual words. The experiment succeeded well in it. Associated Words 7 Not Associated Words 16 Non Words 13 Not Word - Word 7 Word - Not Word 7 The graphs shows there is steady increase in interstimulus time as the words get unfamiliar and longer. Similarly, the chances to make errors also keep increasing with the uncommon nature of the words. The basic analysis targeted exploring the effect of non word in lexical decision taking time using the interstimulus time as the dependent variable. The researches expected to find the difference between the time in accordance with related words and non-related words. Posthoc tests are used to determine in which interval the relationship between the stimuli and the influence of the non words is very high. This provides clue regarding activating of related nodes in the brain. The research also checks the relationship between similar sounding words and non-words. It implies there is no difference between the influence created by an actual word and a non word sounding or spelling similar. For example words like "knife - fork" are identified easily if they come after both words like "Meat - vegetables" or non words like "Figth - Bite". They still have a common link. However if the actual words occur after several non words people make the mistake of marking the non word as word especially when they are hurried. Determining how frequently a word pair occurs influences the range of its identification significantly. People are quite judgmental in marking familiar words correct even if it’s slightly misspelled for example "cottle" instead of "cattle". Hence, technically non-words take shorter to get rejected than similar looking misspelled words. Homophones with similar sounds also take long time to acquire response. But, they do not create any particular error proving Orden’s theory. Associated words like "knife - fork" were identified in the least response time. The results clearly indicate associated pairs take less time to be identified than non-associated pairs. Similarly non word pairs were likely to get more errors in identification. Word - non-word pairs took the longest response time. Non associated word pairs got identified correctly faster than the word - non-word pair. Comparison with Glushkos Theory Both words and pseudo words are pronounced using same phonological and orthographic knowledge said Glushko (1979). Our experiments also show the same. Words like "music -toxic" "nest - chust". We could easily see that the response time taken for identifying "music - toxic" as non associated words is much higher than the response time taken to identify "nest - chust" as word and non word. Though the same phonological sounds are used, words with similar pronunciation and different meanings confuse the brain, taking a little longer to decipher its meaning. Comparing the results of our experiment with that of Glushkos we could find the results are nearly the same. As Glushko stated "irregular spelling-to-sound correspondences take longer", to get identified. STIMULUS (4, Music - Toxic) 733 STIMULUS (4, Music - Toxic) 743 STIMULUS (4, Music - Toxic) 749 STIMULUS (4, Music - Toxic) 768 STIMULUS (4, Music - Toxic) 774 STIMULUS (16, Nest - Chust) 615 STIMULUS (16, Nest - Chust) 663 STIMULUS (16, Nest - Chust) 701 STIMULUS (16, Nest - Chust) 854 STIMULUS (16, Nest - Chust) 975 Conclusion Lexical decision through Superlab software helped the researchers reach two main conclusions. The mechanism behind the cognitive reading ability depends on the ability of a person to retrieve related data from the semantic networks in the brain. The non words influence the ability of recognizing the related words and stimulating the correlating nodes significantly. Both similar sounding words and non words have the same effect. Concluding from the results gathered in our research we could say both the hypothesis stated above are true. Studies conducted on various adults on Lexical decision (LD) and naming (NAM) predicted there is difference between individual capability of the person. They provided much better understanding of cognitive mechanisms behind reading capability. The results obtained from various experiments done on lexical decision help the psychologists and the scientists constantly in developing better ways to help the reading impaired and the people with reading disability. References 1. Collins, A & Loftus, E. (1975). A Spreading-Activation Theory of Semantic Processing. Vol 6, pp. 407 -428. 2. Gernsbacher, M. A., & Faust, M. E. (1991). The mechanism of suppression: A component of general comprehension skill. Journal of Experimental Psychology: Learning, Memory, and Cognition, 17, 245-262. 3. Glushko, R. (1979). The Organization and Activation of Orthographic Knowledge in Reading Aloud. Journal of Experimental Psychology. Vol 5, pp. 674 - 691. 4. Grieco, A., Bettella, S., Conti, M., Orioli, M., &Casco, C. (2004). The effect of preview eccentricity in a lexical decision task. Visual Cognition, 11, 781-796. 5. Harley, T. (2008). The Psychology of Language: From Data to Theory. 3rd edition. Hove and New York: Psychology Press. 6. Masson, M. E. J. (1995). A distributed memory model of semantic priming. Journal of Experimental Psychology: Learning, Memory, and Cognition, 21, 3-23. 7. McClelland, J. L., Rumelhart, D. E., & Hinton, G. E. (1986). The appeal of parallel distributed processing. In D. E. Rumelhart, J. L. McClelland, & the PDP research group (Vol. Eds.), Parallel distributed processing: Explorations in the microstructure of cognition: Vol. I. (pp. 3- 44). Cambridge, MA: MIT Press. 8. Meyer, D. E., & Schvaneveldt, R. W. (1971). Facilitation in recognizing pairs of words: Evidence of dependence between retrieval operations. Journal of Experimental Psychology, 90, 227-234. 9. Marek, P. (2004). Lexical Decision. Retrieved June 19th from http://opl.apa.org/Experiments/About/AboutLexicalDecision.aspx 10. Nelson, D. L., McEvoy, C. L., & Schreiber, T. A. (1998). The University of South Florida word association, rhyme, and word fragment norms. Retrieved June 19th, 2014 from University of South Florida Free Association Norms Web site: http://w3.usf.edu/FreeAssociation/ 11. Orden, G. (1987). A Rows is a Rose: Spelling, sound and reading. University of California. Vol 15, pp. 181 - 198. 12. Rossell, S. L., Bullmore, E. T., Williams, S. C., & David, A. S. (2001). Brain activation during automatic and controlled processing of semantic relations: A priming experiment using lexical-decision. Neuropsychologia, 39, 1167-1176. 13. Seguit, J., Mehler, J., Frauenfelder, U & Morton, J. (1982). The Word Frequency Effect and Lexical Access. University of Cambridge. Vol 20, pp. 615 - 627. Appendix Words Used Associated Words Not Associated Words Non Words Not Word - Word Word - Not Word door - handle alarm - sofa pilanto - twip quayne - plain nest - chust knife - fork music - toxic grisking - forgest borse - source window - clipple meat - vegetables shower - flour looverton - guisine shreet - speaker stomach - twaice kettle - tea face - zip sharita - bozzle lilm - circle example - swutty fate - destiny leg - fly lart - yarnock cottle - imagine doctor - mactir table - pie control - duck brisking - yarst tream - folder stomach - twaice redbull - vodka cavity - amnesty crotle - mection figth - bite hair - crare prayer - target pilanto - twip aid - clock flapple - trimp moon - case coath - joot photographer - gaffer weaf - shamp guitar - water merlander - dostrate projector - paper plint - deeg nail - ridicule missile - bristle promise - whiteboard Read More