Veri güdümlü öğrenme yaklaşımının dil öğrenimi üzerine etkileri: Türkiye'deki yabancı dil öğrencileri üzerine bir çalışma

The Data-Driven Learning (DDL) approach is relatively new in the area of active and discovery-style learning. Proposed by Johns (1991a), this approach emphasizes inductive acquisition as the learners analyze language use and patterns of specific items in a corpus. The methodology of the DDL approach gives the learner direct access to data so that the learners create their own meanings and uses. Students are in control of their learning and must be given appropriate skills to carry out their language investigation (Koo, 2006).The general aim of this study is to better understand effects of Data-driven (DDL) on language achievement of Turkish EFL learners. The specific purpose of this study is to look closely at whether this approach has a marked effect on the learning of language items presented in the materials, and on the learners? ability to transfer context observation skills to similar language tasks. DDL was evaluated in two respects. First, the learning effect of DDL was measured using experimental research design with pre- and post-tests. The experimental group worked on concordance-based materials, whereas the control group was given corresponding non-concordance teaching units focusing on almost the same language items. The results showed that DDL has a marked effect on the learning of language items presented in the materials, but not on the learners? ability to transfer context observation skills to similar language tasks. Second, the learners? attitudes towards DDL materials were elicited using a questionnaire in the form of an agreement scale. In general, DDL materials were rated highly, particularly as a means of drawing attention to words in context.Key words: active and discovery learning, corpus, language achievement, teacher-student interaction, data-driven learning, attitudes, inductive learning