Fostering the Inferencing of Second Language Vocabulary through Data-Driven Learning

Abstract

Abstract This study aims to investigate how scaffolding a data-driven learning approach (DDL) can facilitate the inferencing of word aspects, namely meaning, part of speech and grammatical function (M, PoS, GF) for intermediate Arab university learners in an online second language vocabulary (SLV) classroom. Diverse studies have shed light on the value and the effectiveness of using DDL in the improvement of language skills, such as writing, reading and speaking, or language aspects, such as vocabulary and grammar. However, there are no studies that focus specifically on how DDL can be scaffolded to facilitate the learners’ inferencing process of the aforementioned word aspects in online classrooms. A design-based research approach was utilised to implement this study. It involved multiple iterations of online DDL sessions. Sessions were evaluated by the researcher and the teacher. There were three iterations: one of them was a pilot, which aimed to test principles adapted from the literature and data collection tools in practice; the second iteration aimed to provide the preliminary design principles that will use for guiding the second phase; the third iteration aimed to further revise the suggested principles based on actual practice to demonstrate a cohesive and final version of the tested design principles. All the iterations were implemented in an online institution and there were about 10 participants in each iteration. They were aged between 21 and 23.