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Title: Multidimensional Linguistic Analysis of Multiple Undergraduate Writing Samples Collected from Engineering Students in Entry-level Laboratory Courses at Three Universities
This study aims to identify the linguistic feature characteristics of multiple writing assignments completed by engineering undergraduates, including entry-level engineering laboratory reports and writing produced in non-engineering courses. We used Biber’s multidimensional analysis (MDA) method as the analysis tool for the student writing artifacts. MDA is a corpus-analysis methodology that utilizes language processing software to analyze text by parts of speech (e.g. nouns, verbs, prepositions, etc.). MDA typically identifies six “dimensions” of linguistic features that a text may perform in, and each dimension is rated along a continuum. The dimensions used in this study include Dimension 1: Informational vs involved, Dimension 3: Context dependence, Dimension 4: Overt persuasion, and Dimension 5: Abstract vs. non-abstract information. In AY 2019-2020, total of 97 student artifacts (N = 97) were collected. For this analysis, we grouped documents into similar assignment genres: research-papers (n = 45), technical reports and analyses (n = 7) and engineering laboratory reports (n = 35), with individual engineering students represented at least once in the laboratory report and once in another category. Findings showed that engineering lab reports are highly informational, minimally-persuasive, and used deferred elaboration. Students’ research papers in academic writing courses, conversely, were highly involved, highly persuasive, and featured more immediate elaboration on claims and data. The analyses above indicate that students are generally performing as expected in lab report writing in entry-level engineering lab classes, and that this performance is markedly different from their earlier academic writing courses, such as first-year-composition (FYC) and technical communication/writing, indicating that students are not merely “writing like engineers” from their first day at college. However, similarities in context dependence suggest that engineering students must still learn to modulate their languages in writing dramatically depending on the writing assignment. While some students show little growth from one context to another, others are able to change their register or other linguistic/structural features to meet the needs of their audience.  more » « less
Award ID(s):
1915644
PAR ID:
10335499
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
ASEE Annual Conference proceedings
ISSN:
1524-4644
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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