I have a response dataset for twenty-five questions, which measures three grammar topics. The participants are two different English proficiency groups of intermediate and advanced. So, I want to compare their correct number of answers within each of the three grammar topics. For example, is there any significant difference between the number of correct answers of INT and ADV groups in the questions testing tenses? As can be noticed, I want to compare these two groups' means of correct answers only within these conditions, not across conditions (which would correspond to MANOVA, I guess, in that case).
For purposes of example, the following are the participants' total number of correct answers out of 10 in each condition. The number 5 in the first horizantal line is the total correct number of first intermediate participant.
INT = c(5,6,4,2,1,......); ADV = c(9,7,6,8,8,......)
INT = c(2,3,2,1,4.......); ADV = c(9,9,8,7,5.......)
So, how could I examine their performance to each other in every condition (grammar topic in my case)? Normally, I conducted an analysis using a t-test with three dependent variables (as the number of groups' correct answers in each of the three topics), but I heard that multiple t-tests can yield Type-I error.