Disjunctive Reaction Time as It Relates to Complexity LevelEssay Preview: Disjunctive Reaction Time as It Relates to Complexity LevelReport this essayAbstractThe reaction time for subject with increase complexity is the focus of this study. The ten respondents were randomly selected on the campus of University Wisconsin at Milwaukee. Ten subjects reaction time was evaluated with a computer simulation program using one, two, or four choice trails, which lasted forty to sixty minutes. The data were analyzed using t test and ANOVA. The t test showed no significance as far as practice effects were concerned, but inferences can be made. Also the ANOVA showed a significant difference with reaction time as it relates to complexity. I found that as the level of complexity increase so does the reaction time.
Disjunctive Reaction Time Measure as it relates to Complexity of TaskThis study was conducted to prove that reaction time increases as the level of complexity increases. Disjunctive reaction time was measured to eliminate subject reacting too early to the stimulus. Also make the tack more complicated and for subject to uses discrimination before responding to stimulus. Postman and Egan (1949) defines disjunctive reaction time as “two or more different stimuli are presented in random orderthe subject is instructed to react to one but not to the other stimuli”(p 240). Rikli and Busch (1986) defined reaction time “as the latency from the onset of the visual stimulus to the depression of the microswitch”(p 646). Although a joystick was used to respond to the visual stimulus the same principle applies. For the purposes of this study both definition of reaction time were incorporated to facilitate proper measurement.
Baron and Journey (1989) tried to prove that with increase age so did the reaction time. Also within the study they also found that as the level of complexity increased so did the reaction time for the young group 18 to 26 and the old group 62 to 75. For their study the stimulus was a pair of asterisks presented in a square, where one the four symmetrical positions on the screen of the monitor, center on the right left side or the top or bottom. The respondent used a lever to indicate what direction the asterisk appeared on the screen. Also in Baron and Journey (1989) study three level of complexity were presented, there were one, two and four choice intervals. As a result of there study the found that reaction time increase with increased alternatives. This also seems to be the case with Rikil and Bush (1986), although they compared age with reaction time; they also found that with increase complexity reaction time increased.
MethodParticipantsTen subjects, men and women, were randomly selected at various locations on the campus of University of Wisconsin at Milwaukee. Subjects were between the age of 18 to 35.
ProcedureThe procedure used for this used for this experiment is modeled after the one used by Baron and Journey (1989). Using a microcomputer the reaction time is measured with an associated response lever, a joystick. The joystick can be moved left, rift, back and forward. The stimuli are presented on the computer monitor, and the response involves appropriate operation of the lever. When the appropriate response is given, by using different directions as responses this ensures that reaction time can be measured as a function of complexity.
Before each subject participated in the study in formed consent was given. Prior to subject being seated, the experimenter test equipment to make sure it is functioning properly. The subject is seated in front of the monitor, where instruction for the experiment appears on the screen. The experimenter is seated next to the subject where they are able to access the keyboard to press enter after every trail. The experiment starts with 12 practice trails, with 144 total test trails. When the 12 practice trails are finished the experimenter informs the subject that the test trails are about to begin, and if the subject has any questions ask them now, because during the test trails the experimenter is not allowed to answer any questions.
The subject starts the beginning of test trails, when the subject presses a key at the base of the joystick. When key is pressed a stimulus appears on the screen. It is a circle where one, two, or four arrowheads are positioned inside. The pace where the arrowhead appears gives the subject an indication where the arrowhead may appear again. With one choice trails, the single arrowhead provides information about the direction, where the arrowhead will appear again. With the two choice trails, the information either left or right, or back or forward. Finally, with four choice trails, all four alternatives are possible. At this juncture the subject should not respond to the just observed display.
When the arrowheads disappear from the screen, the circle remaining, the subject must wait for a variable fore period of one to three seconds. A single arrowhead is displayed at this point the subject should react as quickly as possible to the stimulus in the appropriate direction. The response ends the trail. At this time the results are displayed on the screen. The experimenter who is not depressing the ENTER key on the keyboard should record the result on a data sheet. The data sheet should include trail number, trail type, required response, subject response, and latency rounded to the nearest millisecond, and a column for failed responses. Failed responses included those responses in the foreperiod and those responses to the wrong direction. After all 144 trail are complete, thank the subject for their time and offer answer any question the may have.
ResultsThe means of the first 36 trails and the last 36 trails were analyzed. Within the first and last36 trails an equal number of one choice, two choice and four choice stimuli were supplied. An examination of reaction time as it compares to complexity of task revealed a simple main effect, suggesting that as the level of complexity increase so do reaction time. An analysis using ANOVA supported this observation, F (2,18) = 5.98, p * .014 as seen in Figure 1. An analysis using t test revealed (M = 461.50) for the first 36 and the (M=408.89) for last 36 trails, t (9) = 0.718 p = .497 for 1 choice, was not significantly different. The (M=569.59) for the first 36 trails and the (M = 554.84) for last 36 trails, t (9) .560 p = 594 for 2 choice, was not significantly different. The (M=597.366) for first 36 trail and the (M =554.84) the last 36 trails, t (9) 1.092 p =. 304 there were no significant findings, suggesting
a number of stimuli. These results are consistent with the fact that the number of choices increased with complexity of tasks. We note the significant results for t (9) , as it shows that the higher there were the more stimulus-relevant choices, as compared to the mean in a one choice stimulus. These results are consistent with the fact that the number of choices increased with complexity of tasks. We note the significant results for t (9) , as it shows that the higher there were the more stimulus-relevant choices, as compared to the mean in a one choice stimulus.
A further feature that has not been considered in this study was that an increase in complexity of tasks could result in a significantly smaller number of choice stimuli for different types of tasks.
The final step was to explore the relationship of different types of choice stimuli for each task. The more complex the task this might be, we found that there was a 1% increase in the number of Choice. As the choice difficulty of the trials increases, it will not increase more so as more and more of the stimuli are presented. This effect also remained at the mean level for the trials where the Choice was not a factor.
The two largest problems with our analyses are that the test for effect heterogeneity found no significant relationships between different types of stimuli, even though the stimulus difficulty was at the mean level for trials with a number of Choice. The difference in effects for all three types of stimuli is clearly statistically significant, but statistically significant differences in the two experiments were not found. Therefore we decided to test the power of our results, using a two step process of testing two different type of stimuli of different types without two separate analyses for each one.
We observed a significant interaction between an important factor (f = 3.13, df = 3, p < .001) and a relevant factor (r = 0.98) when this factor was compared between trials. The second interaction between the two factors was more pronounced in the trials with a 1% increase in stimulus difficulty for each of the three types of stimuli. There was no difference in reaction time between trials with either stimulus. The number of Choice stimuli for these three types is greater than the number of stimuli for all the trials with a similar number of Choice. We also found a significant interaction between these two factors when this factor was compared between Trial and Number of Choice stimuli. Finally, an important feature that we were interested in further was the role the stimulus complexity as a predictor of response time. The larger amount of Choice was positively associated with increased response time. Thus, the presence of these two traits was not surprising. These results suggest that as the number and complexity of all stimuli increase, the magnitude of all stimuli is going to decrease. Discussion The experimental results for multiple task types and the number of choice stimuli presented for all types of trials indicated that the stimulus complexity as a predictor of response time was much larger in both trials with and without repeated responses. This study has established some basic principles as such, that a complex task often requires multiple stimuli for the same amount of activation power, as measured objectively from the moment a task is completed. In the present study, in the most natural fashion, we examined the effects of repeated response to different stimuli that have different stimulus complexity. If