Experimental design procedures for model discrimination and for estimation of precise model parameters are usually treated as independent techniques. In order to conciliate the objectives of both experimental design procedures, the present paper proposes the use of experimental design criteria that are based on measures of the information gain when new experiments are carried out. The proposed criterion depends on the volumes of the confidence regions of the model parameters and presents a number of advantageous aspects, such as the conciliation of the usual experimental design objectives and the fact that the obtained criterion values can be easily interpreted in terms of the information eliminated after carrying out additional experiments. Besides, the proposed design criterion can easily accommodate multiobjective experimental design approaches, as shown in the examples.