Comprehensive Report: Lexico Decision Analysis Experiments and Results

This report presents an analysis of two Lexico Decision experiments. The introduction provides background on the Lexical Decision Task (LDT), explaining its use in psychology and psycholinguistics to measure how quickly individuals classify stimuli as words or non-words. The methods section details the participants, materials, and procedures for two experiments (LD1 and LD2). LD1 explored the effects of related, unrelated, and non-word stimuli on reaction times, while LD2 examined the impact of high-frequency, low-frequency, and non-word stimuli. The hypotheses for each experiment are clearly stated. The results section presents graphs showing reaction times across different conditions. The discussion interprets these results, confirming the hypotheses that related words elicit faster responses than unrelated words (LD1) and that frequently used words are recognized faster than less common words (LD2). The conclusion emphasizes the role of familiarity in cognitive processing, suggesting that the human brain responds faster to familiar stimuli. The report includes a bibliography of cited sources.

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RUNNINGHEAD: Lexico Decision Analysis
REPORT ON ANALYSIS OF LEXICO DECISION EXPERIMENTS
INTRODUCTION
In the quest to establish the flow of knowledge as cognitive humans, there comes by, several if
not numerous propositions trying to explain a theory of flow of knowledge and the variances.
According to Pamela. This is in the line of understanding how knowledge is organized.
Prompting some theorists to suggest that, knowledge is organized according to semantic
networks, an array of nodes representing concepts and links enabling activation among the
nodes. Marek (2009).Eventually this led to need to prove the theories hence breeding LDT-
Lexical Decision Tasks. According to Wikipedia a Lexical decision task is a procedure used in
psychology and psycholinguistics experiments, aiming to basically measure how quick people
are able to classify and identify stimuli as words and nonwords. Narky (2018).
During the experiments. A participant is expected to make a decision on given words over
varying stimuli. This is either categorized under priming experiment where there is a prime word
and a target word, or, under lexical decision experiment where the effect of word frequency in
relation to recognition of the word. The data collected during this experiments is recorded and
used for analysis and interpretation purposes. In our task, we carry out 2 experiments to aid in
determining the validity of our pre-stated hypotheses with an aim of testing how we access and
recognize words so that there is an understanding of how words are organized and retrieved from
the human mental lexicon. O’Grady $ Archibald (2012).
Experiments and outcomes:
LD1_Expt:
Non-word – 4.342564723, Related -1.012456789,Unrelated -2.723451763
LD2_Expt:
High-1.234512231, Low-3.987123231, Non-word-5.452652512

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Lexico Decision Analysis
METHODS
Participant (s): “Name”
Native Languages spoken: “Language”
Materials:
LD1_Expt:
Experiment was a Stimuli relationship (related, unrelated and nonword) task, with conditions
given as (related, unrelated and nonword). In both unrelated and related conditions, there were
20 pairs each and 40 pairs of nonwords conditions. The task had actual English words as prime
words but with different targets.
LD2_Expt:
Experiment was a Stimuli type (high, low and nonword) task, with conditions given as (high, low
and nonword).In the second task, both high and low conditions, there were 20 pairs each and 40
pairs of nonwords conditions. There was use of software for experiment purpose and another for
analysis purposes; Experiment software: Psychopy software; Analysis software-Excel
PROCEDURE
1. LD1_Expt:
It was conducted in psychopy software environment and was recorded in real-time so as to
gather relatively accurate data. It involved 80 pairs of words and nonwords. Here the participant
of the experiment was to be seated in front of a computer and was expected to respond with each
flushing word by pressing a button following each flushing word: 1st a prime word would be
flushed followed by a target word. If the target was English they were to press “F”, if not “J”.
The information was recorded and exported for analysis. Yolanda (2016).
LD2_Expt:
In this lexicon decision experiment, the participant was to open the psychopy software
environment, the participant was seated in front of a computer screen and words were flushed

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Lexico Decision Analysis
one after the other. The participant was to respond by pressing a button “F” if the word was
English and a button “J” if not. All the errors and responses were to be recorded. Hauk et al.
(2012)
HYPOTHESES
As mentioned earlier, the underlying purpose for carrying out our experiments was to establish
whether the assumptions made hold or not. Therefore before carrying out our tasks we stated
assumptions (hypotheses) for our 2 experiments:
LD1_Expt: In a priming experiment, we try to establish whether recognition of words is linked
to related words. I.e. Does a given word simulate a response for another, for instance is it easy to
think of “class” when a prime word “bell” is mentioned than think of kingdom?. In this
experiment we assume that related words trigger fast responses than unrelated ones.
LD2_Expt: In a lexico decision experiment we take the assumption that the frequency at which a
word is often used, affects the rate of response for such a word. I.e. A word that is commonly
used has a fast response compared to that which is rarely used. Therefore in our experiment we
state the hypothesis that the more frequently a word is used, the higher the probability of fast
responses.
RESULTS
Graph for reaction (time in secs) against relationship stimuli
Figure 1: Graph 1- Average LD1_Expt mean: 2.6928243807
Average LD2_Expt mean: 3.5580959887
Graph for reaction (time in secs) against type stimuli

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Lexico Decision Analysis
Figure 2: Graph 2
DISCUSSION
As established from graph1 above, the response rate for unrelated (2.723451763) words is
relatively slower than that of related (1.012456789) words, similarly the response for nonwords
(4.342564723) is slowest. Either, the response rate for frequently used words (high) is relatively
fast (1.234512231) compared to that of less used words (low) that is (3.987123231), whereas the
response rate for a nonword is averagely longer. The results above prove that our hypotheses
hold. I.e.:
LD1_Expt:
This proves that there is a relationship between the prime word and the target word. Whereby, if
the prime word is related to the target word, the response rate is fast. This is supported by the
fact that our cognitive brains have learnt to associate some stimuli to another, thereby through
stimulating the former, the latter undergoes easy reception easily, unlike when there is no
relationship between the two: in this situation the nodes take a while longer to establish a
memory, hence slower response times.
LD2_Expt:
This proves the hypothesis that the more frequently a word is used, the impression is imprinted
in the human memory, thus the next time the response is required, the brain easily recognizes it
as a familiar stimuli, thereby exhibiting fast responses compared to unrelated words and
nonwords. In conclusion, the human semantic nodes and the brain in general is tilted towards
familiarity, therefore we generate fast responses when exposed to familiar stimuli, and in
contrast generate slower responses under unfamiliar stimuli. This is as seen from the results of
our experiments and analysis.

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Lexico Decision Analysis
BIBLIOGRAPHY
O’Grady, W., & Archibald, J. (2015). Contemporary linguistic analysis: An Introduction. (8th
Canadian Ed) Pearson Canada.
Hauk, O., Holden, A., Chen, Y., & Coutcout, C (2012, April 2). The Time Course for Single
Word Reading: Evidence from Fast Behavioral and brain responses. Retrieved from:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3382728/
American Psychology Association. (2014, Nov 6). Lexical Decision Tasks, Semantic Priming,
and Reading. Retrieved from: www.apa.org/pubs/highlights/peeps/issue-33.aspx
Marek, P. (2009, June 12). Lexical Decision. Retrieved from:
www.opl.apa.org/Experiments/AboutLexicalDecision.aspx
CogLab. (2014, May 9), Lexical decision. Retrieved from:
www.coglab.com/lab/lexical_decision.shtml
Science direct. (2017, March 11). Lexical Decision task- an overview| ScienceDirect Topics.
Retrieved from: https://www.sciencedirect.com/topics/neuroscience/lexical-decision-task
Yolanda, W. (2016, November 17). Lexical Decision Tasks. Retrieved from:
www.study.com/academy/lesson/lexical-decision-tasks-definition-example.html