Comparing same item but before and after result I have a questionnaire for the effectiveness of the implementation of a short course. Respondents need to answer 6 items in part B of my questionnaire with 4-point likert scale (ordinal data). The respondents need to answer same 6 questions before the course and after the course. However, I don't know how to analyze the data in an appropriate way. 
My objective of is to see the level of knowledge and skills the respondent gain before and after the short course. My hypothesis is that there is no relationship between level of knowledge and skills respondent before and after joining the short course.
 A: If the same individuals fill in the questionnaire before and after the course, than your data are dependent. You could model this with a mixed model, using  a random effect for students (since they appear in the data set twice. For example, the $\textsf{R}$ package lme4 could do this as follows:
LMM <- lmer(y ~ x + (1 | student))

Where y could be the sum of responses on the likert items and x some explanatory variable, like age or gender, or whatever is of interest. Note that this model assumes your likert-scale items can be reasonably approximated by a normal distribution. 

There is an issue with your likert items though, as they are not symmetric, because there is no neutral reponse on a 4-scale rating. From Wikipedia:

Well-designed Likert items exhibit both "symmetry" and "balance". Symmetry means that they contain equal numbers of positive and negative positions whose respective distances apart are bilaterally symmetric about the "neutral"/zero value (whether or not that value is presented as a candidate). 

If you haven't collected your data yet, it might be better to change the questions to a 5-scale rating, such that $3$ could be considered neutral.
