This study investigates how we can understand students' actual status in C programming exercises from their learning activity logs. In a face-to-face course of C programming exercise, it is hard for a teacher to see who are in trouble from their apperance. It is not always true that typing something means he or she is making some progress. Therefore it is important to identify, or possibly even predict, students having difficulty from their activity patterns. Most of the prior work paid attention to only trial-and-error activities, such as compile results and execution errors. However, it tends to be overlooked that knowledge acquisition process is also worthy of attention. When a student encounters a compile error, they usually read textbooks to seek a solution. It is considered to be useful for the task whether he or she has an ability to find appropriate pages for error resolution. In this paper, we propose a method to predict whether a student can resolve errors or not. Based on students' activity logs collected from our programming environment and e-book system, we conduct experiments to show and discuss the prediction performance.