A personalized task recommendation system for vocabulary learning based on readability and diversity

Vocabulary learning is the foundation of language acquisition for second language learners. To assist language learners’ vocabulary learning, this research investigated a personalized task recommendation system based on readability and diversity. A word learning theory, the involvement load hypothesis, has also been applied as the theoretical framework of the system to facilitate task recommendation. Ten Chinese learners of English were invited to participate in the research and used the system for vocabulary learning for around two weeks. These students were all intermediate learners. The participants’ learning experience, outcomes, motivation and attitude were measured respectively using questionnaires, pretests, posttests, and interviews. The results showed that the participants were very satisfied with the learning experience, and positive learning outcomes and attitudes were observed. Many students stated that they would love to keep using the proposed recommendation system for future language learning. It is also suggested that the wide use of this system will benefit many self-access language learners. Copyright © 2019 Springer Nature Switzerland AG.