Mining error patterns of engineering studetns´ English reading comprehension

Reading in English is a very import skill in the learning process for engineering students. In order to enhance students´ reading comprehension ability, it is necessary to evaluate reading difficulties in an efficient way. Due to a lack of resources and accurate assessment tools, it remains a challenge for many instructors to identify students´ errors during their English reading process. In order to cope with this problem, this paper applies a data mining technique to identify the students´ error patterns. From the database of students´ errors, students´ error patterns and their association rules were discovered through generalized association rules. By using the techniques proposed in this paper, instructors will be able to acquire important and useful information about students´ English reading comprehension problems in a more efficient way.