Center for Earth Systems Engineering and Management
A collection of scholarly work published by and supporting the Center for Earth Systems Engineering and Management (CESEM) at Arizona State University.
CESEM focuses on "earth systems engineering and management," providing a basis for understanding, designing, and managing the complex integrated built/human/natural systems that increasingly characterize our planet.
Works in this collection are particularly important in linking engineering, technology, and sustainability, and are increasingly intertwined with the work of ASU's Global Institute of Sustainability (GIOS).
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- All Subjects: Essay
- All Subjects: Requirements engineering
Most would agree that telecommunications systems are socially constructed. Since communication tends to involve people, it seems obvious that people should impact the creation of such systems. But it is far less obvious that the specifications for such systems should be noted for their social construction. As marvelous and technical as the system is, we must not forget the important technological artifact known as the specification that came before it. This paper tells the story of the social construction of the IRIDIUM system specification as viewed through the eyes of a popular socio-technical systems (STS) analysis tool. Actor-Network Theory (ANT) is employed to elucidate the culture of the Motorola requirements engineering process while describing some of the primary actors and their lively interactions as they strove diligently to produce the “perfect” specification. Throughout, it will become obvious that just as the kingdom was lost “for want of a nail,” so the IRIDIUM system specification was nearly lost for want of a toolsmith.
Essay scoring is a difficult and contentious business. The problem is exacerbated when there are no “right” answers for the essay prompts. This research developed a simple toolset for essay analysis by integrating a freely available Latent Dirichlet Allocation (LDA) implementation into a homegrown assessment assistant. The complexity of the essay assessment problem is demonstrated and illustrated with a representative collection of open-ended essays. This research also explores the use of “expert vectors” or “keyword essays” for maximizing the utility of LDA with small corpora. While, by itself, LDA appears insufficient for adequately scoring essays, it is quite capable of classifying responses to open-ended essay prompts and providing insight into the responses. This research also reports some trends that might be useful in scoring essays once more data is available. Some observations are made about these insights and a discussion of the use of LDA in qualitative assessment results in proposals that may assist other researchers in developing more complete essay assessment software.