This paper describes the design of a backchannel feedback corpus and its evaluation, aiming at realizing in-car spoken dialogue systems with high responsiveness. We constructed our corpus by annotating the existing in-car spoken dialogue data with back-channel feedback timing information in an off-line environment. Our corpus can be practically used in developing dialogue systems which can provide verbal back-channel feedbacks. As the results of our evaluation, we confirmed that our proposed design enabled the construction of back-channel feedback corpora with high coherency and naturalness.