Learning path and learning progression have received extensive attention from broad disciplines. The existing research In the field of learning path is rarely applied in curriculum learning and teaching. Learning progression is usually constructed through observations, interviews but not quantitative analyses. With 726 Grade 8 students' mathematical knowledge in TIMSS-2015 as the research object, this research adopted a newly generated assessment theory - cognitive diagnosis assessment as the research tool and exploited methods such as K-means clustering analysis to construct learning path by combing the relationships among the attributes. We obtained the students' ability theta s for each classified group through the 3PL model in the Item Response Theory (IRT) and constructed the learning progressions based on the theta s and the attribute relationships. From a data-driven approach, this method has provided a new perspective as well as the data support for the construction of the learning paths and the learning progressions.