Personalizing the Making of Technical Word Lists for Science and Technology Students: A Pedagogic Action Research Study

The challenge of meeting the diverse and specific vocabulary needs of students from different disciplines has been widely discussed in academic research. This paper explores how undergraduate students in science and engineering personalized the process of creating word lists for their academic needs. By using two corpus analysis tools—wordlist and concordance—available through the SketchEngine interface, the students were able to analyze an ad hoc corpus of texts relevant to their fields. Additionally, they assessed the technicality of words using a technicalness scale specifically developed for the purpose of this study. The data for the study consisted of the word lists that the students submitted, along with their notes, and transcriptions of individual student presentations on these word lists. The findings revealed that the students categorized words based on their technicality, considering both the specific context within their academic corpus and the broader meanings that these words could hold outside of their disciplines. In particular, students distinguished words based on their level of specialization and how these terms were understood in other fields. These results underscore the importance of a discipline-specific approach when teaching vocabulary in science and engineering programs. In conclusion, we discuss potential methods for teaching vocabulary to science and technology students, emphasizing the importance of personalized learning and context-based vocabulary development to support academic success.