Evaluating young learner's second language vocabulary learning: corpusbased data-driven learning
Introduction
To illustrate how corpus data-driven learning can be applied to the classroom, this paper constructs
a model for teaching vocabulary in primary school English. The purpose of this paper, therefore,
is to understand how to optimize vocabulary acquisition. Specifically, the applicability and
viability of software such as COCA, Sketch Engine and AntConc in vocabulary learning are
formulaically presented one-by-one in the Evaluation section of this paper, after a review of
relevant literature.
The language skill developed was: using corpus to aid learning and understand word meaning.
Due to student confusion, I have found that students are not clear whether to use the word ‘search’
or ‘find’ in many instances. These words have similar meaning but variations in their usage. Search
is the action of looking for; find is the result of the search having concluded. We collaboratively
used COCA, Sketch Engine and AntConc to investigate this. A comparison of how these words
can be found in corpus software is included later in this essay.
Exploratory and discovery learning methods such as these can better stimulate students' interest in
learning, and prioritize a dominant learning position of students, enabling them to take control of
their learning more effectively. The role of teachers has changed from the authority of the
traditional classroom to the architect of learning guide, and learning partner of data-driven
learning. This has narrowed the distance between students and teachers and created a better, more
collaborative and open learning environment. I will use the terms find and search as examples of
how learning occurs.