You need to look at your part correlation. The squared part correlation explains how much % your only significant predictor explains of the variance of 14.4% your full model explains. You can delete the information skill and recompute or you can keep it. You have to give the table in the result section . You need tolerance and VIF values also to decide about multicollinearity.
Have you checked for multicolineraity among predictor variables ? You can perform it in SPSS. Just tick the "colinarity diagnosis" option at the "Statistics" button. Then you can refine the predictor variables. Its up to you to decide the level of R square value depending on the scenario.