Proposing an ESL recommender teaching and learning system

This paper proposes an ESL recommender teaching and learning system capable of generating for ESL instructors practical information on problems and questions of grammar their students encounter. Not only does the system assist teachers to identify students' specific difficulties and weaknesses in learning, it can also provide data of recommendation that helps the student to find out his or her weak points in learning and offers improvement recommendations. In general, instructors can easily find out the number of students who have failed their exams, but have trouble identifying their real difficulties in learning. Based on the students' testing records, the system works to identify and find those problems, and then comes up with its suggestions for designing new teaching strategies. Besides, the information so produced can also be helpful for the students themselves to improve their grammar. The experiment in this study is based on real students' testing data, and a detail processing is developed that incorporates the advantages of the clustering technology. The system as here proposed has proved to be impressively effective, its performance having been tracked for one year.

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