Data-driven learning of phrasal verbs in English speaking : looking at intermediate level Chinese learners' attitudes and inferencing strategies

Abstract

The study compares the attitudes of and inferencing strategies used by intermediate Chinese EFL learners on two types of data-driven learning. It aims to find out which type of data-driven learning is more positively perceived and whether intermediate Chinese EFL learners are receptive to the application of data-driven learning in learning figurative phrasal verbs in speaking. It also aims to examine the inferencing strategies used by learners when they are analysing the concordance output and examine the relationship between strategies used and learners’ attitudes towards DDL. 46 university students were equally divided into hard DDL and soft DDL group, based on their Gaokao score of English, major, year of study and gender. The two groups received the same teaching of phrasal verbs and activities, except for the treatment. Students’ think-aloud data, interview, and questionnaires were collected. The results revealed that students from both groups have positive attitudes towards DDL, with soft DDL group in general expressed more favourable response towards their figurative phrasal verbs learning in speaking, especially in learning the meanings. Both groups of students used evaluating strategies and meaning-focused strategies the most, with students from soft DDL group used them more often. A weak correlation exists between students’ use of inferencing strategies and attitudes in using DDL to learn the meaning of phrasal verbs. In summary, the difference between hard and soft DDL resulted the difference in their attitudes and strategy uses.