Portland State University. Department of Applied Linguistics
Date of Award
Master of Arts (M.A.) in Teaching English to Speakers of Other Languages
1 online resource (vii, 91 pages)
Data-driven learning (DDL), an inductive teaching approach in which students learn through corpus interaction, has gained recent traction as way to teach specialized vocabulary in English for Specific Purposes (ESP) classes. There is little research, however, that addresses how to choose specialized vocabulary for teaching with DDL.
This study addressed this gap in research by exploring the potential of a three-part analytical, corpus-based system for determining vocabulary to teach with DDL for a specific context of language use. This system included (1) identifying words that were significantly more frequent in a specialized expert corpus than in a corpus of general English, (2) narrowing to words that showed patterned differences in use between the specialized corpus and a student corpus, and (3) narrowing further to words with salient enough patterns of usage to teach with DDL. This three-part system was applied to the context of civil engineering in order to find vocabulary words to teach civil engineering students with low-proficiency writing skills at Portland State University.
For the first step in my analytical system, I found 201 words that occurred significantly more frequently in civil engineering practitioner writing than in the Corpus of Contemporary American English and that met requirements for frequency, distribution, and other criteria. I tested the second and third steps on 45 of these words and identified 14 words that showed evidence of needing to be taught and being well suited to DDL.
After reflecting on my process, I found that the analytical system was successful in meeting my goals for finding civil engineering vocabulary for data-driven activities. I also made several observations that may be useful for ESP teachers who are interested in applying this methodology for their classes, the most notable of which were:
1. The system was especially useful for connecting words that are not explicitly civil engineering themed (e.g., encountered or using) to important writing functions that civil engineers perform.
2. Although it provided a systematic basis for vocabulary teaching decisions, the process was generally time-consuming and required complex judgments, which indicated that it may only be worth performing if teachers plan to regularly incorporate DDL vocabulary instruction into their course.
Otto, Philippa Jean, "An Analytical System for Determining Disciplinary Vocabulary for Data-Driven Learning: An Example from Civil Engineering" (2017). Dissertations and Theses. Paper 3472.