Abstract:

How can one better use modern CALL resources to help language learners to build up a larger target language (TL) vocabulary quickly? A major need that quickly becomes apparent at the intersection of the fields of second language vocabulary acquisition (SLVA) and computer-assisted language learning (CALL) is the lack of sufficient research with respect to their most advantageous integration for language learning. The depth of lexical processing taxonomy presented here seeks to integrate the research studies that exist into a clear and effective approach that uses insights and innovations of both fields to create a user-friendly system for more rapid vocabulary acquisition and activation. Because of the proliferation of language-learning programs and websites, it becomes important to help define which most essential vocabulary and reading strategies should be included in those programs and websites. When designing programs and websites, the three major parameters of subjective enjoyment, objective effectiveness, and technological efficiency should all be considered. This article compares various studies to suggest how many of the features and functions of CALL tools can be used at the most appropriate stages of lexical processing and acquisition to make vocabulary learning smoother, quicker, and more effective. It helps to fill a noticeable gap by providing a clear, step-by-step taxonomy of 40 vocabulary learning strategies (VLSs), simplified into an eight-fold scale of major cognitive phases for ease of instruction and use in classes. These strategies are channeled through a logical depth of lexical processing (DLP) scale, which can help promote both learners' receptive and productive vocabulary development, whether using traditional text-based or CALL-enhanced methods. The ultimate goal is to find practical ways to use a research-based DLP scale and VLS taxonomy to improve the teaching and monitoring of essential phases of vocabulary learning, either in traditional classes or in CALL learning environments.

Author: John Paul Loucky