## 3 Methodology
### Data Processing and Analysis  
This study uses AntConc 3.5.9 [40], a popular corpus software widely used in many corpus-based studies, to conduct data processing and analysis. The procedure can be divided into three major steps: (1) remove the overlapping parts between word classification criteria; (2) explore the composition of the off-list words; and (3) calculate word types proportion and lexical coverage of each word classification criteria. Detailed descriptions are given as follows. (1) Remove the overlapping parts between word classification criteria  
After expanding and compiling the function word list [24] and CEFR A2 and B1 level word lists, the researcher discovered overlapping words between each word list. If the overlapping words cannot be effectively removed, then these words will be classified repeatedly and cause errors and inaccuracy in detecting the difficulty level of the target corpus. Before the initiation of the process, it was assumed that if an overlapping word exists in both two different difficulty level word lists, then the word should be classified into the lower (i.e., easier) difficulty level word list. For example, if \"the\" exists on the function word list and CEFR A2 level word list simultaneously, then \"the\" should belong to the function word list. Under the above condition, the researcher input the CEFR A2 level word list into AntConc 3.5.9 and then input the function word list and set it as \"a stoplist\" to remove the function words that occurred in the CEFR A2 level word list. Through this process, the CEFR A2 level word list removed 118 overlapping words and decreased its word types to 3692. Similarly, the researcher input the CEFR B1 level word list into the corpus software and then input the word list that integrated the function word list and CEFR A2 level word list and set it as \"a stoplist\" to remove the function words and CEFR A2 level words that occurred in the CEFR B1 level word list. From this process, the CEFR B1 level word list removed 116 overlapping words and decreased its word types to 5865. The purpose of this series of filtering processes is to precisely distribute the words to proper difficulty level word lists to avoid bias in the analytical results. (2) Explore the composition of the off-list words  
After the function words, CEFR A2 level words and CEFR B1 level words are excluded; the remaining words are classified as off-list words. The function words can be recognized as grammar words, and CEFR A2 and B1 level words can be recognized as English for general purpose (EGP) words (i.e., everyday English) with high frequent usage in Anglophone countries [25]. The off-list words should be fully investigated, because these words may cover EGP-oriented words with a higher difficulty level or words that are for military purposes. Because MOEPT is designed for testing cadets' English competency in military contexts, the researcher hypothesizes that the off-list words should cover many military-purpose words (e.g., terminologies, technical words, and acronyms). In order to address the off-list words, the researcher followed prior studies (e.g., [33; 41]) and the words' meanings and usages to conduct the vocabulary taxonomy qualitatively. Three raters (including the researcher) conducted classification tasks based on each off-list word's literal meanings and functions in the test items. After the words' classifications among the off-list words are confirmed, each classification's statistical data can also be calculated. (3) Calculate word types proportion and lexical coverage of each word classification criterion  
In order to detect the difficulty level, the calculation of the proportion of different word classification criteria have to be implemented from two aspects: word types proportion and lexical coverage. Word types proportion represents the lexical composition of the target corpus; in addition, lexical coverage, as Nation [35] mentioned, indicates the proportion of tokens (i.e., running words).