Visual Search Task Research Paper

Visual Search Task Research Paper
Student’s Name
Institutional Affiliation
Abstract
The task aims to test how the response time of people was affected by the number of items and color of the item. Researchers examined the response times of a group of people in a visual search task against the color and quantity of items. The participants were students at different levels of university education. The students’ responsibility was to identify an upright orange letter T among blue and orange ones. The researcher recorded their responses and analyzed the data obtained using one way ANOVA with repeated measures in SPSS software. The scholar presented their results in tables and graphs. The findings of the test showed that the particular hypothesis tested did not match.
Key Words: ANOVA, SPSS, visual search, covert attention, preattentive, primary visual cortex, reetrant, target, non-target, distractors, stimuli, and Simon’s effect
Visual Search Task Research Paper
Introduction
Generally, the more crowded a place is, the more difficult it is to spot someone. However, as people move away, one can locate the person in a less crowded area. An increase in the number of items results in an increased length in response times. The recorded data showed that every time the screen displayed more orange and blue T’s in 5,10,15, and 20’s (whether upright or up-side-down), the more each participant spent more time searching for an orange vertical T. The analysis performed was to verify if the response times were affected by color and number of items.
Psychologists suggest through various trials that it’s possible to perform an overt search if items are visibly large enough for identification. The situation is impossible without fixation (Pereira & Castelhano, 2014, p. 2058). Shifts in attention, alias covert attention, enables successful performance of numerous tasks. 3-4 times per second is approximately enough for selecting a new point of fixation. Numerous supporting studies aver that stimuli help in the selection of 4-8 items per fixation. The choice can occur in parallel or many shifts in attention per fixation.
The intended target is what determines the efficiency of a search task. Target refers to the item being searched for while its opposite is known as non-target. Beesley, Vadillo, Pearson, and Shanks (2015) enquired whether learning distractor configuration would confer a benefit on the later visual search. Participants searched for a target (T) among distractors (L) (p. 349). Distinguishing features, such as size, shape, color, orientation, number, etc. are vital in the completion of a search task. For example, red dots among yellow ones on a white paper are easy to spot out for their color. Preferably, if they happen to be bigger than the rest and fewer, a participant would have an easy task for identification. The response to such a job would increase as the number of dots increases. The above attributes are called guiding attributes because they guide attention. Jeremy and Horowitz (2008, p. 3325) came up with a modified list of characteristics and their likelihood to support a search.
The term preattentive is controversially pragmatic in many dimensions. For instance, early works suggested color as an attribute can be preattentive because that would translate to prior color processing, without attention (Castelhano & Heaven, 2010, p. 1286). Recent studies infer that an area such as the primary visual cortex (p.v.c) might previously process a visual stimulus without any display of recognition. For example, find the color blue in this paintwork. Some brain loci processes what color blue looks like before its search without showing care. However, p.v.c. activity might be modulated by attention in a reentrant way. Therefore, the frequent use of ‘preattentive’ is a temporal usage. Besides, O’Hara (2017) asserts that the deployment of recognition and visual processing of an item is preattentive.
Decisively, a combination of many visual search works and attention is practical on computer screens with the hope of similarity to reality. Such artificial stimuli seem less tedious than when the search for original items is active. For example, manually looking for a floor-tiled vacant house to move into in a residential estate is tedious. The emergence of modern technology has led to the birth of numerous specialized search tasks. Corresponding examples include airport security, air traffic control, and body scans in hospitals. Besides, these visual search tasks vary in response time, depending on the number of items designated for search. Airport security personnel may spend a long time on a passenger who has more luggage than one with a backpack.
As mentioned earlier, this study seeks to statistically analyze the variation in response times in visual search for different numbers of items in a survey participated by students. The appropriate hypothesis is:
H0: The response times are not affected by the different colors and quantity of items.
H1: Anything different.
In comparison to Simon’s effect, this experiment focuses on all sides of the response-selection stage. Simon’s outcome defines how stimuli and responses occur on the same side of the brain. If they are adjacent to each other, the reactions are slower or come to a halt. For instance, a left stop sign on the road, indicating right, may result in a driver on the same highway stopping or driving slower than before. The example proves beyond reasonable that stimuli and response are the primary determinants of most reactions in humans. Conversely, visual search uses eye movement to measure the degree of attention given to stimuli.
Questions regarding this experiment may be such as:
1 Is visual search independent of attention or stimuli?
2 Did the number of errors of failing to respond in time increase as the color and quantity of items increased?
3 Did the participants show any significant change in response times throughout the experiment?
4 Were their minds preattentive to color in every scene change?
Methods
Participants
A sample of 23 junior (14) and senior (9) college students took part in the demographic survey conducted before the visual task. Out of the 23, 18 were female while the rest were male. The least racially represented was Native American and Multiracial group with a 4.35%. Eight students trace their ethnic roots to Asian/Pacific Islander, thus forming the mode in ethnic background terms. The ages of the participants ranged between 19 and 45. Accordingly, the survey recorded 18 students as bilingual/multilingual whereas five were not.
Materials
In this psychological experiment, strictly, every participant used the same computer in the school library, unlike the first one where they were even allowed to use their laptops. The experiment website PsyToolkit.com was provided to participants by the course instructor. Mouse, touchpad, and keyboard were offered to engage in the trial for participants to click the link to start visual search task and press spacebar in response to an upright letter T. Participants collected the test-number of search items and the overall time taken through cell phones. Finally, they were prompted to undertake a demographic survey combined with the experiment by using the URL; ...