In this scenario, we need to identify the type of research design based on the number and levels of factors under consideration. First, let's consider Factor A, which is the level of noise. This factor has three levels: high, medium, and low noise.
Next, we look at Factor B, which is the level of caffeine intake. This factor has two levels: no caffeine and high caffeine intake.
In this kind of design, each participant is exposed to only one condition of each factor, meaning a participant is not repeatedly measured under various levels of noise and caffeine. Hence, this is a between-subjects design.
Combining the information about the number of factors and their levels, we can say the design is a factorial. A factorial design allows us to examine the effect of more than one factor and see how these factors might interact with each other.
In this case, we have two factors (noise and caffeine) with three and two levels each. Hence, this type of design is typically referred to as a factorial design with a notation that shows how many levels each factor has.
Therefore, we have a 3x2 between-subjects, factorial design (option C).
This means that the same subjects aren't used in all the treatments and there are three levels for noise and two levels for caffeine, resulting in a total of six possible conditions that a participant could be assigned to.