Co-creation is a form of collaboration in which partners share, improve and blend ideas together to develop a creative product. It helps to share ideas and solve problems in a creative manner. Several co-creativity research works have focused on generating creative artifacts, but there is a limited amount of research in analyzing creative collaborations. Creative collaboration can be evaluated through examining interaction dynamics such as cognitive states, behavior, and the number of ideas generated. This dissertation conducted two different collaborative experiments to add a new contribution to human-human co-creation by modeling and quantifying co-creativity using divergent and convergent thinking modes. The first study conducted 15 collaborative users' studies of a turn-based collaborative drawing task using a shared canvas to extract different patterns of creative collaboration. In the second study, we conducted 21 dyadic user studies of a turn-based collaborative drawing task to quantify and extract several co-creation patterns and compare co-creativity of users. The results of both studies showed significant differences of creative thinking between high and low creative performances. High co-creativity group shows balanced divergent and convergent thinking comparing to other works. The interaction dynamics of different creativity levels were also different in term of the number of ideas and objects created and modified. The work can be applied to different co-creation applications, and can be the starting point toward designing a computational creative thinking model in the future.