which non parametric test to use? I'll start with saying I am not an expert in stats and had some basic knowledge of Anova but was now told to use the nonparametric test in my project and I'm lost.
My design:
I have two groups, low and high level of the second language (independent v.)
tested in two conditions: gesture/ no gesture (independent v.)
for a fluency measure(speech rate) at one point in time (dependent v.)
Which would be the appropriate test to run in this case?
 A: If speech rate is ordinal, then Kruskall Wallis can help you in this scenario. Considering each combination of second languange and the two conditions, you can test whether the distribution of these four groups are the same, based on ranks.

The Kruskal-Wallis H test (sometimes also called the "one-way ANOVA on
  ranks") is a rank-based nonparametric test that can be used to
  determine if there are statistically significant differences between
  two or more groups of an independent variable on a continuous or
  ordinal dependent variable. (from spss)

A: One option: you can use an aligned ranks approach.  This is similar in spirit to the Kruskal-Wallis test, but will allow for more complex models. The ARTool  software makes this easy, especially with its implementation in R.
Another approach would be to use an appropriate model for the kind of data you have.  For example, if your dependent variable is ordinal in nature, ordinal regression would be a good solution.
A good implementation of either of these should be able to handle a design analogous to a 2 x 2 mixed model. 
Finally, someone telling you to use nonparametric statistics may not be a very good reason to do so.  You might want to explore the reasoning more.
