PTADisc: A Cross-Course Dataset Supporting Personalized Learning in Cold-Start Scenarios

The focus of our work is on diagnostic tasks in personalized learning, such as cognitive diagnosis and knowledge tracing. The goal of these tasks is to assess students' latent proficiency on knowledge concepts through analyzing their historical learning records. However, existing research has been limited to single-course scenarios; cross-course studies have not been explored due to a lack of dataset. We address this issue by constructing PTADisc, a Diverse, Immense, Student-centered dataset that emphasizes its sufficient Cross-course information for personalized learning. PTADisc includes 74 courses, 1, 530, 100 students, 4, 054 concepts, 225, 615 problems, and over 680 million student response logs.