Academic Vocabulary Use in Doctoral Theses: A Corpus-Based Lexical Analysis of Academic Word List (AWL) in Major Scientific Disciplinary Groups
- Habibullah Pathan
- Rafique Memon
- Shumaila Memon
- Syed Shah
- Aziz Magsi
Abstract
Since the development of academic word list (AWL) by Coxhead (2000), multiple studies have attempted to investigate its effectiveness and relevance of the included academic vocabulary in the texts or corpora of various academic fields, disciplines, subjects and also in multiple academic genres and registers. Similarly, this study also aims at investigating the text coverage of Coxhead’s (2000) AWL in Pakistani doctoral theses of two major scientific disciplinary groups (Biological & health sciences as well as Physical sciences); furthermore the study also analyses the frequency of the AWL word families to extract the most frequent word families in the theses texts. In order to achieve this goal, a pre-built corpus of Pakistani doctoral theses (PAKDTh) (Aziz, 2016) comprises of 200 doctoral theses from two major scientific disciplinary groups was used as textual data. Using concordance software AntConc version 3.4.4 (Anthony, 2016), computer-driven data analysis revealed that in total 8.76% (496839 words) of the text in Pakistani doctoral thesis corpus is covered by the AWL words. Further distributing the analysis per sub-lists, shows that the first three sub-lists of AWL accounted for almost 57% of the whole text coverage. An attempt was made to further analyze the AWL text coverage by considering the frequency of occurrences in terms of word families. The findings showed that among 570- word families of Coxhead’s (2000) AWL, 550-word families with the sum of 96.49% are found to occur more than 10 times in PAKDTh corpus, which are taken as word families used in the corpus. This study concludes that Coxhead’s (2000) AWL is proved effective for the writing of theses. On the basis of the findings, further possible academic implications are discussed in detail.
- Full Text: PDF
- DOI:10.5539/ijel.v8n4p282
Journal Metrics
Google-based Impact Factor (2021): 1.43
h-index (July 2022): 45
i10-index (July 2022): 283
h5-index (2017-2021): 25
h5-median (2017-2021): 37
Index
- Academic Journals Database
- ANVUR (Italian National Agency for the Evaluation of Universities and Research Institutes)
- CNKI Scholar
- CrossRef
- Excellence in Research for Australia (ERA)
- IBZ Online
- JournalTOCs
- Linguistic Bibliography
- Linguistics and Language Behavior Abstracts
- LOCKSS
- MIAR
- MLA International Bibliography
- PKP Open Archives Harvester
- Scilit
- Semantic Scholar
- SHERPA/RoMEO
- UCR Library
Contact
- Diana XuEditorial Assistant
- ijel@ccsenet.org