The Triple-Decker Model
The book presents the Triple-Decker Model that describes the interactive mechanism among key constituents of English for Specific Purposes Ability (ESPA): language knowledge, strategic competence and background knowledge (nursing knowledge).
First, the model reveals that ESPA constituents can be assigned to three groups according to their roles in determining ESPA in reading: automators (language knowledge and background knowledge) that respond most directly, assistants (the cognitive aspect of strategic competence) that come to assist when automators are insufficient or boggle down, and regulators (the metacognitive aspect of strategic competence) that supervise all cognitive activities. Second, the model demonstrates the effect of strategic competence and background knowledge on ESPA fluctuated with the continuous increase of language knowledge.
The book also demonstrates the use of two innovative analytical techniques: composite scores based on bifactor multidimensional item response theory for scoring ESP reading tests and the multi-layered-moderation analysis (MLMA) for detecting linear and nonlinear moderation relations.
Chapter 3 Methodology
As the purpose of the current study was to investigate the interaction among background knowledge (medical and nursing knowledge), grammatical knowledge and strategic competence in affecting ESPAR (in particular, English for medical and nursing purposes reading ability), a correlational rather than an experimental research design was deemed appropriate (Pearl, 2012). For this purpose, quantitative data were collected non-experimentally (Muijs, 2004) and analyzed using two methods: MIRT and SEM. MIRT analysis was applied to validate each measure and to calibrate and score participants’ original responses, and SEM used to explore the relationships among variables represented by these instruments.
Given the purpose of the study and that English for Specific Purposes Ability for Reading (ESPAR) was manifested by the reading comprehension subtest of the Medical English Test System Level Two (METS-2), the population of interest was confined to all potential test takers of METS-2 in medical colleges in China. To enhance sampling representativeness, the researcher used mixed-method sampling. This involved five steps: 1) deciding the minimum sample size, 2) stratifying the population according to the geographic areas where the majority of METS-2 takers come from each year, 3) selecting colleges with larger number of potential METS-2 takers each year and their willingness to ←63 | 64→participate, 4) determining the grade of students, and 5) sampling individual student participants.
To attain a satisfying level of statistical power for a planned model, it is essential to decide the minimum sample size prior to data collection (McQuitty, 2004). The minimum sample...
You are not authenticated to view the full text of this chapter or article.
This site requires a subscription or purchase to access the full text of books or journals.
Do you have any questions? Contact us.Or login to access all content.