Change blindness is a strange phenomenon which occurs when a visual change in the environment goes unnoticed by the observer, even if the change is large or obvious. This can be particularly dangerous in times when vision and ability to react to changes around us is imperative to our safety, such as when driving. An occurrence of change blindness while driving could cause an accident if it is not detected fast enough. There are many contributors to detection of change which have been studied by previous researchers including the importance of the object changed, how focused the observer is, and how the change comes about.
In this study we focused on two other factors that can influence change blindness and sought to determine whether distractions or the kind of change present would effect how fast a change was found. There have been many studies which demonstrated change blindness occurring when a visual disruptor is present, however unlike previous researchers Simons, Franconeri, and Reimer (2000) decided to conduct a study to demonstrate that change blindness also occurred when gradual changes were made without a disruptor.
The study included 80 participants (no gender information given), while no age information was given ach participant in the experimental groups received either course credit or $6-7 for participation in the study and so may be around college aged. In each of the experimental groups participants were assigned to either the gradual condition, disruption condition, or a guessing condition in which participants were asked to guess which change would take place.
Participants were then asked to search for changes in photos of natural scenes presented on a computer screen, successful detection of change was counted if the mouse-click response was within 0. 98cm (35 pixels) to the closest changed pixel of the picture. Participants in Experiment 1 searched for additions and deletion, those in Experiment 2 searched for color changes, and participants in the control group were exposed to both photo sets. Simons et al. 2000) found that while participants in the gradual and disruption condition of Experiment 1 detected about the same amount of additions and deletions, this was not the case for Experiment 2 where the disruption condition detected color changes better than those in the gradual condition.
Furthermore, color changes were detected less often than addition and deletion changes. Researchers believed the differences between the gradual and isruption conditions may have come about because we may use different strategies when searching for gradual changes than when looking across a disruption.
One thing I think Simons et al. ‘s (2000) study did not take into account was the possibility that participants in the gradual and disruption condition could guess the change. While their measure of success was the distance away from the closest altered pixel there is no way to determine whether the participants did not just randomly click on the screen and happen to be within that area of success. Similar to Simons et al. (2000), Fletcher-Watson, Collis, Findlay, nd Leekam (2009) conducted a study in which the used addition, deletion, and color changes in flickering pictures.
However unlike previous studies, researchers used naturalistic pictures to compare children and adult participants. Fletcher- Watson et al. (2009) wanted to determine whether change blindness was present in children and to see if any age-related trends in the ability to detect change existed. Participants included 94 children (50. 9% male) ranging in age from 6 to 12 years old and 20 adults (50% male) from ages 19 to 22 years old. Each participants vision was tested to guarantee it would not ffect their ability to see the changes.
Participants were then asked to search for a change between images flashing back and forth on the screen and describe what change had occurred, researchers recorded whether each participant correctly identified the change or not. Fletcher-Watson et al. (2009) found that change detection improved in each age group as they got older and that overall color changes were easiest to spot for all groups. Furthermore, researchers found that there was a greater detection for items of central interest and attributed this result to high-interest items drawing more attention than marginal interest items.
So any change to these central interest objects would have been more easily seen by the participant because their attention was already drawn to the object. One improvement researchers could make to the study would be making the speed of the flickering pictures appropriate for both children and adults. Fletcher-Watson et al. (1997) based the speed off of what would work best for children however they should have determined whether the speed of the flickering pictures affected adults differently.
Unlike previous studies, including Simons et al. 2000) and Fletcher-Watson et al. (2009), which used flickering still photos, he study conducted by Levin and Simons (1997) utilized motion pictures to demonstrate change blindness. Researchers wanted to investigate whether change blindness occurred not only with trivial objects in pictures but also with objects at the center of a viewer’s attention in moving pictures. Participants included 60 students (no gender breakdown given) who attended Cornell and received candy or course credit in exchange for participation.
Participants in Experiment 1 were asked to watch a video which contained a change after each editing cut and were then asked what changes, if any, they had noticed. Following this they watched the video a second time and were instructed to find the change after each cut. In Experiment 2A five participants at a time watched eight short videos where the actor was switched out with a similar looking person during a scene cut and then were asked to write a description of what they watched.
Those who did not mention a change in actors were asked if they noticed the switch. Experiment 2B was set up in the same way as Experiment 2A, however participants in this experiment watched eight additional videos with no changes, for a total of 16 videos, and were warned to pay attention for he change and record whether or not one was present. Levin and Simons (1997) found that only one participant noticed any changes in the first viewing and that detection only improved to an average of two changes noticed during the second viewing.
Additionally, in Experiment 2A only a third of participants reported a change, however detection improved greatly in Experiment 2B with an average of only one mistake made for each participant. According the Levin and Simons (1997) those who successfully saw the changes in the videos before being told about them may have intentionally encoded a property of he object right before the change and so noticed the switch more easily than the other participants. The only thing that may have effected their findings was the difference in procedures between Experiment 1 and Experiments 2A and 2B.
The participants in Experiments 2A and 2B watched the videos in a group and opposed to by themselves like in Experiment 1, the addition of extra people around them could have acted as a distraction and affected their attention to the video. In the following study we investigated the influence type of change had on how long participants took to detect change. However, nlike previous studies we also determined whether having a distraction present also had an impact on ability to detect change.
The distraction we tested in this study was the presence or absence of music. It is hypothesized that participants will take longer to find the addition or deletion of an object in a picture than any color changes or position changes made. Furthermore, participants in the music listening condition will take longer to identify the change present in the picture due to them being distracted by other stimuli, in this case music, and so they do not have the attention necessary to notice the changes in pictures as quickly.
