PY 2112 Individual Assignment: Experiment Conducted
PY 2112 Individual Assignment: Experiment Conducted
So what is the purpose of the lab report writing exercise?
Ask yourself at every point: “Am I communicating with my reader as clearly as possible?
What is it? It is a presentation of the specific problem under study and describes the research strategy.
What is it for? Its purpose is to give your reader a firm sense of what problem you were trying to solve, and why you chose to investigate it in the manner you did.
It should answer the following questions:
- What is the point of the study? (what problem is it intended to solve?)
- How do the hypothesis and the experimental design relate to the problem?
- How does the study relate to previous work in the area?
- What did you expect to find, and why?
The discussion is the avenue for you to communicate to your reader:
- What you believe you have contributed to the field under research
- How you believe your study has helped to resolve the problem under consideration
- Any additional information that may be relevant to any subsequent attempts to
Replicate your study (such as methodological issues etc).
- What conclusions and theoretical implications you draw from your study.
PY 2112 Individual Assignment: Experiment Conducted – Sample Draft Solution:
In many cases, people tend to have different abilities to memorize things which are either appealing to the senses, whether they are sound, touch, smell, sight or taste. On the other hand, some people can also memorize different effects which are disgusting. However, each person has a different ability to memorize various scenarios. In face recognition, different aspects can be considered. For instance, the race of the faces which a particular participant is subjected to can create different memory abilities. For instance, most people tend to memorize their own races as compared to other races (Meissner & Brigham, 2001) (Wright, Boyd, & Tredoux, 2001). The memory of own race is as a result of perception which these individuals have, especially due to the fact that they spend most of their times interacting with others people from their own race (Chiroro & Valentine, 1995). Moreover, it is also easier to recognize faces that show happiness rather than sadness. In this experiment, E-prime 2.0 software was used to program the experiment and to make the findings one that can be modeled using mathematical expressions from which a conclusion can be drawn.
The main objectives of the study include the following:
- To determine the general effects of own-race bias in Singapore.
- To explore the outcomes on effect of facial emotional expression on the own-race bias.
In order for the experiment to give the desired results, the following hypotheses are formulated:
H1. The experiment expected that the participants from Singapore will portray an own-race bias as afar as remembering the faces of the elements to be studied is concerned. As such, they will show a greater memory recognition for the East Asian faces as compared to the Caucasian faces. This is in relation to the literature written by other scholars.
H2. In line with the research that has been done in the past, it is expected that neutral faces will be remembered less as compared to happy faces.
H3. It is expected that happy East-Asian faces will give a greater recognition as compared to the neutral East-Asians faces. However, there will be a small variation in the recognition of faces happy and neutral faces among the Caucasians.
Signal Detection Theory (SDT) will be used to measure memory recognition.
In this experiment, the members who participated in the study are presented with images of faces which are not familiar to them. The images are provided in the screen of the computer. When they have been presented with the images of the faces, the participants are asked to memorize the pictures. After a short while, the participants are again presented with other images, including the ones they had been subjected to before. The study aims at finding the ability of the person to memorize things based on the number of images they have correctly identified (Baddeley, 2014).
According to Wright, Boyd, & Tredoux (2001) in a study conducted in South Africa and England, it was found that people have a tendency to recognize the faces of those who come from their races. Since the study employed similar techniques and methods in the study, it was easy for the study to arrive at a conclusion that there are own-race bias when it comes to facial recognition. Moreover, the study added to the fact that there were correlations between accuracy and observer confidence when the participant observed a person of from their race (Valentine, Lewis, & Hills, 2016). The own race bias is attributed to the fact that most people tend to associate with people from their own races, hence their perceptions are always geared towards those who come from the same race (Valentine, 2017). In essence, due to this interaction, these individuals can be thought to be experts who have learned the art of remembering the faces from those with whom they interact most of the time.
Meissner & Brigham (2001) also agrees with the fact that people tend to memorize the others who come from their own race. According to their study, Meissner & Brigham explores the various factors to ascertain, for instance, whether the findings can be true, and how reliable the findings can be especially in witness accounts. Moreover, the study also assessed the influence of racial attitudes and interracial contact and how these two add to the ability of a person to memorize what they observed in a crime scene.
Faces that are happy tend to be recognized more easily and even more accurately as compared to faces that are not happy. On the other hand, it is easier for a person to detect an angry person in terms of visual search as compared to one that is happy (Nummenmaa & Calvo, 2015).These can be explained further. For instance, the speed and accuracy of recognizing happy faces results from stimulus types. However, visual search majorly relies on the photographic faces yielded more accurate result for happy face detection.
This experiment used data of 110 participants. Among the participants, there were 78 females (71%) 32 males (29%). Of these participants, 96 were right-handed while 16 were left-handed. However, due to technical problems, for instance, due to the constraints of the study, the data used for the analysis was taken from 68 of the participants. This represents 62 percent of the sample. The mean age of the participants was 21.87 years with a stand deviation of 4.61.
To achieve the purpose of this experiment the study used a 2(Race: East-Asian, Caucasian) X 2(Facial Expression: neutral, happy) within-subjects. Also, Signal detection theory was employed to determine the measure of recognition memory discrimination (d’). The recognition memory discrimination (d’) was made useful in the determination of DV in SPSS.
East-Asian faces. A total of 72 picked from the DFH Database as well as from the CUHK Face Database were used in the experiment. Half of the pictures used were portraited neutral-emotion faces while the other half were portraited happy-emotion faces. The number of pictures of the males and females was the same. The pictures were the taken in a lit-condition environment so that all the features of the face were distinctly visible. The pictures covered the entire face, and was taken in a close-up mode. This mode focused on the face, from the forehead to the chin. The background of the pictures were dark, so that each face appeared as a single object on the screen. The resolution of the images were high and the produced detailed information of the face, including small visible spots and curvature of the skins. Moreover, the photos were enlarged to cover the entire screen of the monitor.
Caucasian faces. Seventy-two images were selected from the Radboud Faces Database. Half of the pictures used were portraited neutral-emotion faces while the other half were portraited happy-emotion faces. The number of pictures of the males and females was the same. The pictures were the taken in a lit-condition environment so that all the features of the face were distinctly visible. The pictures covered the entire face, and was taken in a close-up mode. This mode focused on the face, from the forehead to the chin. The background of the pictures were dark, so that each face appeared as a single object on the screen. The resolution of the images were high and the produced detailed information of the face, including small visible spots and curvature of the skins. Moreover, the photos were enlarged to cover the entire screen of the monitor.