Is ANOVA applicable for my study?


Here's some info about my study:

Looking into stereotype threat and mapping ability, hypothesising that females will perform less well than males when gender priming is used.
Stereotype threat suggests that people perform less well in conditions whereby they belong to a group that they expect to do less well than another. In this case, owing to the stereotype that males are better at following direction, reading a map etc, than females, when the females are gender primed they may do less well than the males.

Data: I have complete data from around 100 participants. IV being the condition they were part of (1. control 2. positive female stereotype info 3. negative female stereotype info aka positive male) DV being their score. (second iv could be gender?)

Participants had to select from a choice of map images, which one correctly corresponds with a street view image that they had seen. Part 2: participants had to follow directions, then choose the map displaying the correct end location.

All scores have been coded as correct/incorrect, with a total score for each participant being made.

I'm now wondering, how i would go about making a summary score for each condition, (do i even need to?) and whether ANOVA (one or two way?) would be appropriate to compare the mean scores from each condition? Also, how would i investigate the difference in performance between males and females within each condition?

purpose of the study / research question / hypotheses, if possible, provide some background or context for us.

I had been told to use Chi Squared previously by my supervisor, but now other lecturers have told me ANOVA might be better, and ill get marked down for keep asking for help!

Many thanks :D
you are correct that an anova would work here. You have a 3 x 2 Anova model. To be honest, it really depends on what your research questions are.

I am doubtful you will detect an statistically effect size with only 100 people (30-35 per condition, and then 15-18 per gender). That is very slim pickings to make statistical inference from.

Also, I am curious, what exact purpose does the baseline group serve? You have the data now, but in experiments with limited power, I am always loathe to sacrifice some of it away to create a baseline, especially in an ANOVA design (where in the control group does not really have a theoretical purpose in analysis).