multivariate vs multiple regression

This is something confusing me for a while! Hope someone can help me a bit here.

For example my data is like this (n=130):

dv = as.numeric(-0.167, 0.960, 1.057, -1.128, 0.613)

iv1 = as.numeric(0,1,1,2,0)

iv2 = as.factor("H","L","H","H","L")

now if I run lm(dv ~ iv1*iv2), I assume my data is split into two groups since I have only two levels for iv2 to estimate the interaction term? However, if I run lm(dv ~ iv1) or lm(dv ~ iv2), the coefficients and p-values are different than in the first lm.

Can someone explain why is this, or direct me to a reading material? Thanks a lot!