case0402: Cognitive Load

In Sleuth3: Data Sets from Ramsey and Schafer's "Statistical Sleuth (3rd Ed)"

Description

Educational researchers randomly assigned 28 ninth-year students in Australia to receive coordinate geometry training in one of two ways: a conventional way and a modified way. After the training, the students were asked to solve a coordinate geometry problem. The time to complete the problem was recorded, but five students in the “conventional” group did not complete the solution in the five minute alloted time.

Usage

case0402

Format

A data frame with 28 observations on the following 3 variables.

Time

the time (in seconds) that the student worked on the problem

Treatment

factor variable with two levels—"Modified" and "Conventional"

Censored

1 if the individual did not complete the problem in 5 minutes, 0 if they did

Source

Ramsey, F.L. and Schafer, D.W. (2013). The Statistical Sleuth: A Course in Methods of Data Analysis (3rd ed), Cengage Learning.

References

Sweller, J., Chandler, P., Tierney, P. and Cooper, M. (1990). Cognitive Load as a Factor in the Structuring of Technical Material, Journal of Experimental Psychology General 119(2): 176–192.

Examples

str(case0402) # level 1 of Treatment is "Conventional" (1st alphabetically)
attach(case0402)  

boxplot(Time ~ Treatment) 
median(Time[Treatment=="Conventional"])-median(Time[Treatment=="Modified"])  
  
wilcox.test(Time ~ Treatment, exact=FALSE, correct=TRUE, 
  alternative="greater")  # Rank-sum test; alternative: group 1 is greater
wilcox.test(Time ~ Treatment, exact=FALSE, correct=TRUE, 
  alternative="two.sided", conf.int=TRUE)  # Use 2-sided to get confidence int.  
        
## DOT PLOTS FOR PRESENTATION 
xTreatment    <- ifelse(Treatment=="Conventional",1,2) # Make numerical values  
myPointCode   <- ifelse(Censored==0,21,24)  
plot(Time ~ jitter(xTreatment,.2),   # Jitter the 1's and 2's for visibility
     ylab="Completion Time (Sec.)",  xlab="Training Method (jittered)",
     main="Test Completion Times from Cognitive Load Experiment",
     axes=FALSE, pch=myPointCode, bg="green", cex=2, xlim=c(.5,2.5) )  
axis(2) # Draw y-axis as usual
axis(1, tick=FALSE,  at=c(1,2),  # Draw x-axis without ticks
  labels=c("Conventional (n=14 Students)","Modified (n=14 Students)") )  
legend(1.5,300, legend=c("Did not Complete in 300 sec","Completed in 300 sec."),
       pch=c(24,21), pt.cex=2, pt.bg="green")  
  
detach(case0402) 

Example output

'data.frame':	28 obs. of  3 variables:
 $ Time     : int  68 70 73 75 77 80 80 132 148 155 ...
 $ Treatment: Factor w/ 2 levels "Conventional",..: 2 2 2 2 2 2 2 2 2 2 ...
 $ Censored : int  0 0 0 0 0 0 0 0 0 0 ...
[1] 129

	Wilcoxon rank sum test with continuity correction

data:  Time by Treatment
W = 164, p-value = 0.001271
alternative hypothesis: true location shift is greater than 0


	Wilcoxon rank sum test with continuity correction

data:  Time by Treatment
W = 164, p-value = 0.002542
alternative hypothesis: true location shift is not equal to 0
95 percent confidence interval:
  57.00007 159.99998
sample estimates:
difference in location 
                    94 

Sleuth3 documentation built on May 2, 2019, 6:41 a.m.