PSY 375 Module Two Lab Worksheet Template

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PSY 375 Module Two Lab Worksheet Template Alternative Format Directions : Read the background of the lab simulation and the use the global data sets to complete the following template. Complete this template by replacing the bracketed text with the relevant information. All responses to lab questions should be in your own words or paraphrased. Change Detection Lab Background This lab contains an animated picture depicting a street in Vancouver, Canada, alternating with a light gray background. There are actually two different photographs of the road, one with a full lamp post and one with the light missing from the lamp post. Participants are asked to detect a change between the two photographs. Chances are, a participant will not see anything changing right away, and it should take them a while to spot the change. Once they know what to look for, however, the change is obvious. The picture illustrates change detection (Rensink, 2002) or, more accurately, how difficult it can be to detect change. The basic idea is that people do not store many details of a scene in memory. Rather, the critical factor seems to be attention: In order to see an object change, it is necessary to attend to the object. The animated image illustrates Rensink's flicker paradigm in which an original image is followed by a blank image (a mask) and is then followed by a changed image (and another mask). This is usually referred to as the "flicker" condition, because the images sometimes appear to be flickering. The blank image swamps the local-motion signal that would ordinarily be caused by a change in an object, so attention is not drawn to the change. The presence of the mask prevents automatic detection of change. Change must now be detected by a slower, higher-level process. Basically, someone has to search the scene, object by object, until they happen to find the changed object. Failing to detect that an object has changed has been called change blindness . Researchers think that change blindness is a leading cause of many car accidents. Glancing away from the road and then back is equivalent to seeing a scene, followed by a blank field followed by a changed scene: The change is very difficult to notice, so your car hits another car. Lab Simulation The participant will see two alternating pictures. One picture is outlined in red, and the other is outlined in blue. Sometimes, the pictures will be separated by a gray field; sometimes they won't. The participant’s task is to decide if anything is changing between the two versions of the picture. 1

The experiment includes 16 trials. Half of the trials involve a change in the picture pairs; the other half have no change. Also half of the trials have a mask and half do not. What methods did we employ in this experiment? On each trial of the experiment, two pictures were presented in alternation. On half the trials, the two pictures were identical. On the other half of the trials, the two pictures differed in some way (e.g., an object disappeared from one image). For each kind of pair, either the pictures appeared immediately one after the other (no flicker condition), or a blank gray box appeared in between the pictures (flicker condition). The participant’s task was to report whether the pictures were identical or differed. One independent variable in this experiment was the flicker and no flicker conditions. A second variable was whether the pictures were the same or changed. Two dependent variables were measured: proportion correct judgments and response time. Proportion correct was identifying that the images were the same or different. Response time was the time between the appearance of the stimuli and the time when the observer made a response. What do we predict participants will do? Why? The table below shows the proportion correct, identification of whether the pictures differed or not, and the response time for the observer(s) to make that judgment. The expected pattern of results is that percentage correct is smaller and response time is slower for the flicker condition than for the no flicker condition. In the no flicker condition, the changing object is easy to identify because the change is immediately detected. Likewise, it is easy to tell that no change is occurring. In the flicker condition, these cues are no longer helpful because the intervening gray leads to changes all over the picture. As a result, someone has to search the scene, object by object, until they happen to find the changed object. Failing to detect that an object has changed has been called change blindness . Researchers think that change blindness is a leading cause of many car accidents. Glancing away from the road and then back is equivalent to seeing a scene followed by a blank field followed by a changed scene: The change is very difficult to notice, so your car hits another car. How robust is this effect? Are there limits to this effect? The effect is quite robust, although there are differences across individuals. Interestingly, when someone knows where the change in the image is located, it is very easy to notice the change, and almost impossible to not notice the change. Global Data A participant should find that they make more mistakes and are slower when the flicker paradigm is used compared with when there is no gray field between the two versions of the photos. 2

Means based on data from 75,807 participants Condition Proportion Correct Response Time (milliseconds) No Flicker 0.955 5288.036 Flicker 0.725 8597.268 Standard deviations based on data from 75,807 participants Condition Proportion Correct Response Time (milliseconds) No Flicker 0.089 42345.070 Flicker 0.164 62720.184 Lab Questions ● How does the pattern of the global data relate to the pattern of results predicted? Hint: See the lab introduction, the predicted results that come with the global data, and the text. The observed data exhibited a discernible pattern, which was influenced by the level of dynamism in the displays and the presence or absence of scene changes throughout several trials. The absence of flicker facilitated concentration on a singular alteration, since there was no need to divert one's gaze to see further modifications within the image. ● How does the gray field (the flicker) affect someone’s proportion correct and Response Time (RT)? Why does the gray field tend to negatively affect accuracy and RT? Why are we measuring both RT and accuracy? What does this tell you about how different people approach a task like this? The presence of a gray field resulted in increased response time and decreased accuracy of my responses. The speed at which an individual can discern distinctions between two entities is contingent upon their velocity and precision. This implies that you engage in extensive contemplation of minute details. Various visual solutions are used to address this issue. ● What implications does this experiment on change blindness and flickers have regarding real-world situations? Try to describe a specific sort of real-world situation: What would be the flicker in your example? Ensure that your example is your own, rather than one from course materials. The act of operating a motor vehicle presents a recurring scenario in which the concepts of change awareness and change blindness are relevant. As an individual traverses a certain environment, the surrounding elements undergo a transformation. One prominent illustration of this phenomenon is the manner in which a traffic signal undergoes alteration. The color and speed at which traffic lights transition indicate changes in traffic flow, while the flashing mode may be used. 3

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Simon Effect Lab Background The Simon effect refers to the finding that people are faster and more accurate when responding to stimuli that occur in the same relative location as the response, even though the location information is irrelevant to the actual task (Simon, 1969). Studying the Simon effect gives us insight into a stage of decision making called "response selection." According to information-processing theory, there are three stages of decision making: stimulus identification, response selection, and response execution or the motor stage. Superficially, the Simon effect may seem similar to the Stroop effect. However, it is generally accepted that the interference that occurs in the Stroop effect comes from the stimulus identification, while the interference that occurs in the Simon effect occurs in the response-selection stage. During response selection, a person uses a rule to translate the relevant stimulus dimension, usually shape or color, to the correct left or right response. However, the location dimension of the stimulus (its position on the screen) overlaps with the relevant stimulus dimension (left or right). Because of this, the irrelevant location dimension of the stimulus activates the corresponding response and interferes with making a response to the non-corresponding side. As a result, same-side responses are faster and more accurate than opposite-side responses. In the real world, the Simon effect has important implications. Primarily, it shows that location information cannot be ignored and will affect decision making, even if the user knows that the information is irrelevant. The Simon effect (and related phenomena) must be taken into account in design of human-machine interfaces. Good interfaces display information in ways that match the types of responses people should make. For example, imagine that you are flying a plane, and the left engine has a problem. The indicator for that engine should be to the left of a corresponding indicator for the right engine. If it is the other way around, you may respond incorrectly to the indicator and adjust the wrong engine. That could be problematic. Lab Simulation In this lab, a fixation point is shown and then disappears. After a random amount of time, the participant will be shown a red or green square to the left or right of the fixation dot. Their task is to indicate as quickly as they can whether the square is red or green. If they make a mistake (i.e., report a green square as red) the trial will be repeated. There are a minimum of 100 trials. What methods did we employ in this experiment? On each trial, a red or green square was shown to the left or right of fixation. The participant’s task was to press a key on the left side of the keyboard (or tap a button on the left side of the screen) if the square was green and to press a key on the right side of the keyboard (or tap a button on the right side of the screen) if the square was red. Trials with incorrect responses were repeated. The independent variable in this experiment was the location of the square (left or right). The dependent variable was the time (response time) between the appearance of the square and the key-press. 4

What do we predict participants will do? Why? Although the task requires the participant to attend only to the color of the square, people are almost invariably influenced by the location of the square as well. When the location of the square and the location of the matching key press have the same relative position (e.g., a green square on the left side of the screen), the response time tends to be faster than when they have different relative positions (e.g., a red square on the left side of the screen). The difference between response times is the Simon effect. How robust is this effect? Are there limits to this effect? The Simon effect is generally quite small (tens of milliseconds). Nevertheless, it is found in many different situations. It might seem that such a small effect can hardly be important. However, there are many situations in which a person has to respond to a small flashing light. The Simon effect can be repeated thousands of times a day and lead to more significant durations. Also, there are some special situations in which even a few milliseconds can make a difference. Many emergency situations in aircraft, for example, are indicated by the sudden appearance of a light. A pilot must be able to respond quickly to such an indicator, and accounting for the Simon effect can play an important role in the design of a cockpit. Global Data You should find that the participants were slightly faster when the target appeared on the same side as the response button/key (congruent) than when it appeared on the opposite side of the response button/key (incongruent). Means based on data from 18,889 participants Condition Response Time (milliseconds) Congruent 639.485 Incongruent 692.033 Standard deviations based on data from 18,889 participants Condition Response Time (milliseconds) Congruent 216.565 Incongruent 242.500 Lab Questions ● How does the pattern of the global data set relate to the pattern of results predicted? The variability in response time patterns between trials was attributed to the location of the signal on each side of the screen. The time limit was influenced by the trial data and the orientation of the screen. The speed of responses was found to be much higher on the side of the keyboard where the key was pushed, in comparison to the side where the key was not struck. 5

● Identify the independent and dependent variables in this lab. The location of the signal in reference to the screen served as the independent variable. The measured variable in this study was the duration of time required for the key to activate after its depression. Spatial Cueing Lab Background A "spotlight" is a metaphor that nicely captures many characteristics of the focus of visual attention: It is a "beam" that is moved spatially, that may not be divided, and that enhances the detection of events falling within it. Some of the strongest evidence supporting the unitary concept of attention comes from the luminance-detection paradigm (e.g., Posner, 1980). In such experiments, participants are first cued with the likely spatial location of a target and then respond as rapidly as possible when the target appears at any location in the display. For example, in a typical display, the stimuli are arranged horizontally with a fixation point in the center, which is also the location where the cue appears. The cue is either valid, correctly identifying the spatial location of the target, or invalid, incorrectly identifying the location of the target. Following the presentation of the cue, a single target stimulus is illuminated (usually about 1000 milliseconds after the onset of the cue) and participants respond as soon as they detect the target, regardless of its location. Relative to a neutral cue condition, responses are faster when the target appears in the cued location (a valid trial) and slower when the target appears in a non-cued location (an invalid trial). Demonstrations of these patterns of results occur independently of eye movements. In other words, when an eye tracker verifies that a participant’s eyes are still fixed on the center, their focus of attention can be off to the right, or off to the left. While other interpretations of these findings are possible, they are consistent with the notion of a focused beam of attention that may be moved to distinct spatial locations – incorrectly in the case of an invalid trial and correctly in the case of a valid trial. Lab Simulation In this lab, a fixation point is shown and then disappears. After a random amount of time, the participant will be shown a cue. If the arrow points to the right, 80% of the time the target will appear on the right. If the arrow points to the left, 80% of the time, the target will appear on the left. If no arrow appears, the target is equally likely to appear on the left or right. The participant’s task is to respond as quickly as possible when they see the square appear, regardless of its location. There are 80 trials. During each trial, the participant should try to keep their eyes focused on the center and avoid moving their eyes. What methods did we employ in this experiment? Each trial began with an arrow that pointed to the left or right, or no arrow at all. The arrow was an inconsistent indicator of where the target stimulus would appear. On 80% of the trials with an arrow, the stimulus appeared where the arrow pointed. On trials without the arrow, the stimulus appeared either to the left or right of the display with equal probability. 6

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The target stimulus was a red square. The participant’s task was to respond to the appearance of the red square as quickly as possible. The independent variable was the type of cue used. The cue could be neutral (not an arrow), valid (an arrow that pointed where the target actually appeared), or invalid (an arrow that points opposite to where the target actually appeared). The dependent variable was the response time between the appearance of the target and the participant’s response. What do we predict participants will do? Why? The response time should be fastest for valid cues, slowest for invalid cues, and intermediate for neutral cues. This pattern of results indicates that one effect of attention is to process information more quickly. The valid cue allows the participant to move attentional focus to where the target will appear and respond to the stimulus more quickly. The invalid cue causes the participant to move attention to the incorrect side and thus they process the target more slowly. How robust is this effect? Are there limits to this effect? The effects are not usually very large (less than 100 milliseconds). Nevertheless, they can be used to explore properties of visual attention. For example, the times to make responses are so quick that they happen before eye movements to the stimulus. This indicates that attention can be focused without necessarily moving the eyes. Global Data You should find that the participants were slightly faster when the target appeared on the same side as the response button/key (congruent) than when it appeared on the opposite side of the response button/key (incongruent). Means based on data from 41,228 participants Condition Response Time (milliseconds) Valid 357.993 Neutral 384.966 Invalid 398.422 Standard deviations based on data from 41,228 participants Condition Response Time (milliseconds) Valid 96.919 Neutral 106.145 Invalid 143.865 Lab Questions 7

● Does the global data match the predicted results? If so, how so? If not, why not? The individual data exhibited more variability compared to the aggregate data, and its observed patterns deviated from my initial expectations. The valid reaction time exhibited a much higher rate of speed compared to both the null and wrong response times. Due to my preoccupation with other matters, I failed to see several elements that were assumed or provided within the dataset. The task of comprehending the inputs was challenging due to the presence of distracting elements within the trials. However, deliberately disregarding these elements resulted in an acceleration of the wrong portion of the reaction time. ● If the spotlight model is false, what should the results have looked like, assuming the participant could pay attention to everything on the screen? Enhancing one's ability to attentively observe throughout a trial may significantly improve the likelihood of promptly and accurately responding when an opportunity arises. Upon seeing that the presence of the sign or line on the screen served only to induce confusion, I exerted considerable effort to redirect my attention towards an alternative focal point. ● How could we apply the concept of invalid cues in a specific real-world situation, for example, “faking someone out” while playing a particular sport or game? Feel free to make up your own example or elaborate on one above. What would be the invalid cue in your example? When considering the concept of deceiving or tricking someone in real-life scenarios, the sport of basketball immediately comes to mind. In the context of basketball, the defensive player is aware of the attacking player's intention to maneuver past them. When attempting to anticipate the actions of an offensive player, a defensive player may encounter a situation where the offensive player employs a deceptive maneuver by first executing a rapid movement towards the right, followed by an abrupt change in direction towards the left. 8

Stroop Effect Lab Background When you first learned to tie your shoelaces, you needed to think carefully through each step of the process. Now, you probably do not even think about the steps, but simply initiate a series of movements that proceed without any further influence. When a behavior or skill no longer requires direct interaction, cognitive psychologists say it is automatized . Many behaviors can become automatized: typing, reading, writing, bicycling, piano playing, driving, etc. Automatization is interesting because it is an important part of daily life. We perform a variety of automatized behaviors quickly and effortlessly. In some cases, people report that they do not consciously know how the behavior is performed, they just will it to happen and it does happen. To explore properties of automatized behaviors, cognitive psychologists often put participants in a situation where an automatized response is in conflict with the desired behavior. This allows researchers to test the behind-the-scenes properties of automatized behaviors by noting their influence on more easily measured behaviors. This demonstration explores a well-known example of this type of influence, the Stroop effect. Stroop (1935) noted that participants were slower to properly identify the color of ink when the ink was used to produce color names different from the color of the ink. That is, participants were slower to identify red ink when it spelled the word blue . This is an interesting finding because participants are told to not pay any attention to the word names and simply to report the color of the ink. However, this seems to be a nearly impossible task, as the name of the word seems to interfere with the participants’ ability to report the color of the ink. A common explanation for the Stroop effect is that participants (especially college undergraduates) have automatized the process of reading. Thus, the color names of the words are always processed very quickly, regardless of the color of the ink. On the other hand, identifying colors is not a task that participants have to report on very often and, because it is not automatized, it is slower. The fast and automatic processing of the color name of the word interferes with the reporting of the ink color. Lab Simulation The trial is started by pressing the space bar. A fixation dot will appear in the middle of the window, and the participant should stare at it. A short time later (less than a second) a word (RED, GREEN, or BLUE) will appear on the screen, and the word will be printed in either red, green, or blue colored font. The participant’s task is to classify the color of the font as quickly as possible, regardless of the actual word. After pressing a key to identify the font color, the participant will receive feedback on whether they were correct. If they were incorrect, the trial will be repeated later in the experiment. If the participant finds they are making lots of mistakes, they should slow down or make certain they understood which key goes with which font color. There are at least 48 trials, 24 in which the font colors and word names are different, and 24 in which the font colors and color names match (e.g., the word "RED" in red font color). 9

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What methods did we employ in this experiment? On each trial the participant was shown a word (RED, GREEN, or BLUE) that was printed in either red, green, or blue font color. The participant’s task was to classify, as quickly as possible, the font color, regardless of the word name. The independent variable in this experiment was whether the word name and font color were the same or different. The dependent variable was the response time between the appearance of the stimulus and the participant’s response. Only trials in which the participant made the correct classification were kept. If a trial was incorrect, it was repeated later in the experiment. What do we predict participants will do? Why? The Stroop effect is that people tend to be faster at identifying the font color when the word name and font color are the same and are slower when they are different. How robust is this effect? Are there limits to this effect? Although not large in terms of absolute time, the Stroop effect is very robust. A common explanation for the Stroop effect is that participants (especially college undergraduates) have automatized the process of reading. Thus, the color names of the words are always processed very quickly, regardless of the color of the font. On the other hand, identifying colors is not a task that participants have to report on very often, and, because it is not automatized, it is slower. The fast, and automatic, processing of the color name of the word interferes with the reporting of the font color. Global Data The mean response time (milliseconds) to correctly indicate the font color. Means based on data from 97,785 participants Word and Font Color Mean Response Time (milliseconds) Same 927.014 Different 1109.663 Standard deviations based on data from 97,785 participants Word and Font Color Mean Response Time (milliseconds) Same 303.530 Different 359.161 Lab Questions 10

● Did the global data match the predicted results? If so, how? If not, why not? The anticipated outcome of the research aligned with the actual findings. On many occasions, I erred in my decision-making due to a lack of comprehension of the significance of various hues. Following several unsuccessful efforts, I began to critically evaluate my initial assumptions and engage in more deliberate consideration over the most appropriate key. I had a sense of certainty upon seeing the congruence between the two entities, therefore compensating for the cognitive effort used in discerning the disparity. ● Identify the independent and dependent variables in this demonstration. The correspondence between the word "name" and the color is either congruent or incongruent. The variable in question is the independent variable. The dependent variable in this study was the reaction time, which varied according on changes in color and term. 11

Module Question Consider the role of new research in advancing the field of cognitive psychology. Applying research to new populations or taking a specific research methodology and applying it in a new way are strategies that can be used to develop new research questions and keep the field growing and evolving. As an example, clinical psychologists have applied the Stroop effect to the study of emotion. An emotional Stroop test involves measuring reaction time in naming the font color of words, but words are either emotionally neutral (like tree or plate ) or emotional ( murder or death ). People with certain mental health issues, like major depression, show a more pronounced emotional Stroop effect. ● Can you think of a different way to apply the Stroop test? The stoop test may also be used to assess the congruity between a series of images and their corresponding verbal descriptions. During a standard fruit identification experiment, participants are shown with images of bananas, strawberries, and blueberries and instructed to identify them based on either their corresponding names or colors (specifically, yellow, red, and blue, respectively). For instance, those engaged in the study of geography may use visual aids, such as images, to enhance their recollection of certain locations. However, these visual aids may also be beneficial in facilitating more elementary tasks. Individuals would be required to reassess their beliefs and instead focus on the distinct manners in which two locations exhibit similarities and disparities. 12

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References Posner, M. I. (1980). Orienting of attention. Quarterly Journal of Experimental Psychology, 32 (1), 3–25. https://doi.org/10.1080/00335558008248231 Rensink, R. A. (2002). Change detection. Annual Review of Psychology, 53 (1), 245–277. https://doi.org/10.1146/annurev.psych.53.100901.135125 Simon, J. R. (1969). Reaction toward the source of stimulation. Journal of Experimental Psychology, 81 (1), 174–176. https://doi.org/10.1037/h0027448 Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18 (6), 643–662. https://doi.org/10.1037/h0054651 13

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