There is a huge literature around this topic (change/gain scores), and I think the best references come from the biomedical domain, e.g.
Senn, S (2007). Statistical issues in drug development. Wiley (chap. 7 pp. 96-112)
In biomedical research, interesting work has also been done in the study of cross-over trials (esp. in relation to carry-over effects, although I don't know how applicable it is to your study).
From Gain Score t to ANCOVA F (and vice versa), from Knapp & Schaffer, provides an interesting review of ANCOVA vs. t approach (the so-called Lord's Paradox). The simple analysis of change scores is not the recommended way for pre/post design according to Senn in his article Change from baseline and analysis of covariance revisited (Stat. Med. 2006 25(24)). Moreover, using a mixed-effects model (e.g. to account for the correlation between the two time points) is not better because you really need to use the "pre" measurement as a covariate to increase precision (through adjustment).
I also like Ten Difference Score Myths from Edwards, although it focuses on difference scores in a different context.