1. Torin Franz & Evan Frick Hanover College

2. Introduction  Stroop (1935)  Asked participants to report the ink color of 100 words  The spelled color did not match the actual color  Asked participants to report the ink color of 100 sets of squares  Took the participants on average a total of 47 seconds longer to identify color of the words  Even when told not to pay attention to the word itself, participants could not ignore what was being spelled

3. Introduction  The way that participants are instructed to respond has an effect on their accuracy  When speed is stressed, accuracy rates go down  When accuracy is stressed, accuracy is comparatively better (Chen & Johnson, 1991)  Automatization-when a task does not require conscious effort to be completed  Sometimes participants do not even realize they are completing the task  Being asked to quickly report the color of the word is difficult due to the fact that the color name interferes in the process (Francis, Neath, & VanHorn, 2008)

4. Automaticity Examples I cnduo't bvleiee taht I culod aulaclty uesdtannrd waht I was rdnaieg. Unisg the icndeblire pweor of the hmuan mnid, aocdcrnig to rseecrah at Cmabrigde Uinervtisy, it dseno't mttaer in waht oderr the lterets in a wrod are, the olny irpoamtnt tihng is taht the frsit and lsat ltteer be in the rhgit pclae.

5. Research Question How correct does the spelling of the words need to be in order to see the effects of automaticity?

6. Hypothesis We expect to find that the more jumbled the words the quicker the reaction time, because it will be harder to identify words that are more jumbled.

7. Method  Participants  Obtained 22 participants through a sign-up sheet  College age students of all levels  No one reported color deficiency

8. Method  Equipment  Gateway Computer, model E4300  Monitor resolution of 1024 by 786 pixels  Internet Explorer 8  Stroop Experiment on CogLab website (Krantz, n.d.)  Written in Java  Spread sheet to record data  Written in Java

9. Method  Stimuli  4 different stimuli  XXXX  Incongruent words  Middle Random Congruent words  All Random Incongruent  25 words in each condition  Shown in the center of the screen  Font size 16  3 different colors possibilities for font color and word spelling  Green, Orange, Purple

10. Method  Procedure  One word displayed at a time  Participants responded to the color of the word  Could respond by striking corresponding key or clicking button at bottom of the screen  There were 25 trials for the 4 conditions  After each condition, participants recorded their average reaction time and accuracy on a separate sheet of paper

11. Results X: 814.89 msec Incon: 1062.61 msec Rand: 846.26 msec Reaction times differed significantly between conditions (F (3, 19)=10.48, p <.001, such that the X condition was the fastest (M =814.89), random was the middle (M=846.26), and incongruent was the slowest (M=1062.61).

12. Accuracy Findings  There was a significant difference of accuracy between conditions (F(3, 19)=4.06, p=.02), such that random was the most accurate (M=.995), X was the middle (M=.98), and Incongruent was the least accurate (M=.97).  Supports our hypothesis because the fast conditions have the best accuracy  There is no speed-accuracy tradeoff  Note: One participants data was taken out- accuracy of.16  Told the researchers that she did the condition wrong and that is why the accuracy was so low

13. Discussion  Our hypothesis was supported by our data  The most jumbled condition (random), had the second fastest reaction time, only behind the X’s (control)  Automatization is less effective when a word is jumbled beyond immediate recognition of an intended word

14. Practical Applications and Limitations  Practical applications  Teachers need to be aware:  as students get older reading is automatized-they can read without thinking  Younger students are so focused on the step-by-step process because reading is not automatized-it is harder to take in the information  Limitations  Used the wrong condition : Middle Congruent  Computers did not work-froze  Did not ask about gender (Van der Elst, Van Boxtel, Van Breukelen, & Jolles, 2006)  Hanover may not be representative of the entire population because of the educational level

16. References Chen, J., & Johnson, M.K. (1991). The Stroop congruency effect is more observable under a speed strategy than an accuracy strategy. Perceptual and Motor Skills, 73(1), 67-76. doi:10.2466/PMS.73.4.67-76 Francis, G., Neath, I., & VanHorn, D. (2008). CogLab 2.0. Belmont, CA: Wadsworth, Cengage Learning Krantz, J. (n.d.). Cognition Laboratory Experiments. Serial Position Effect. Retrieved March 17, 2010, from http://psych.hanover.edu/JavaTest/CLE/Cognition/Cognition.html Stroop, J.R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18(6), 643-662. doi:10.1037/h0054651 Van der Elst, W., Van Boxtel, M., Van Breukelen, G. & Jolles, J. (2006). The Stroop Color-Word Test: Influence of Age, Sex, and Education; and Normative Data for a Large Sample Across the Adult Age Range. Assessment, 13(1), 62-79. doi: 10.1177/1073191105283427