Abstract
Language makes human communication possible. Apart from everyday applications, language can provide insights into individuals’ thinking and reasoning. Machine-based analyses of text are becoming widespread in business applications, but their utility in learning contexts are a neglected area of research. Therefore, the goal of the present work is to explore machine-assisted approaches to aid in the analysis of students’ written compositions. A method for extracting common topics from written text is applied to 78 student papers on technology and ethics. The primary tool for analysis is the Latent Dirichlet Allocation algorithm. The results suggest that this machine-based topic extraction method is effective and supports a promising prospect for enhancing classroom learning and instruction. The method may also prove beneficial in other applied applications, like those in clinical and counseling practice.
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Highlights
When Latent Dirichlet Allocation (LDA) was applied to the Non-Ethics content of the Social Impact Analysis (SIA) papers, five prominent topics corresponded to the topics that students often chose to focus on in their papers: Topic 1: company organization and stakeholders; Topic 2: technical aspects of hydraulic fracking; Topic 3: technical aspects of solar energy roadways; Topic 4: artificial intelligence technology; Topic 5: electric vehicle technology
Representative topics were as follows: Topic 1: environmental concerns associated with oil fracking; Topic 2: general ethical themes related to public health, safety, the environment, and engineering NSPE code; Topic 3: human benefits of technology and ethical theory of utilitarianism; Topic 4: human benefits associated with solar highways; Topic 5: ethical issues associated with autonomous vehicles
Note: Topic 1: environmental concerns associated with oil fracking; Topic 2: general ethical themes related to public health, safety, the environment, and engineering NSPE code; Topic 3: human benefits of technology and ethical theory of utilitarianism; Topic 4: human benefits associated with solar highways; Topic 5: ethical issues associated with autonomous vehicles
Summary
At home and at work, are accomplished through language. Our first premise in the present work is that apart from the practical applications of language in everyday interactions, the language that an individual uses may reveal deeper aspects of the person. “Language is the outward manifestation of the spirit of people: their language is their spirit, and their spirit is their language; it is difficult to imagine any two things more identical" (in Salzmann, 2004:42). The linguist, Edward Sapir, believed that "language and our thought-grooves are inextricably interwoven, [and] are, in a sense, one and the same" (in Salzmann, 2004:43). In psychological research, Pennebaker and King (1999) proposed that “the way people talk about themselves reveals important information about them” In psychological research, Pennebaker and King (1999) proposed that “the way people talk about themselves reveals important information about them” (p. 1297). Chung & Pennebaker (2008)
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