Advanced Stroop effect Torin Franz & Evan Frick Hanover College Evan

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 Evan

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) Torin

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. Evan

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

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. Torin

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

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 Evan

Method Stimuli 4 different stimuli 25 words in each condition 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 Torin

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 Evan

Results X: 814.89 msec Incon: 1062.61 msec Rand: 846.26 msec Torin 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).

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 Torin

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 Evan

Practical Applications and Limitations 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 Torin

QUESTIONS? questions

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