There is increasing evidence that automated writing evaluation (AWE) systems support the teaching and learning of writing in meaningful ways. However, a dearth of research has explored ways that AWE may be integrated within different instructional contexts and examined the associated effects on students’ writing performance. This paper describes the AWE system MI Write and presents results of a mixed-methods study that investigated the integration and implementation of AWE with writing instruction at the middle-school level, examining AWE integration within both a traditional process approach to writing instruction and with strategy instruction based on the Self-Regulated Strategy Development model. Both instructional contexts were evaluated with respect to fostering growth in students’ first-draft writing quality across successive essays as well as students’ and teachers’ experiences and perceptions of teaching and learning with AWE. Multilevel model analyses indicated that during an eight-week intervention students in both instructional contexts exhibited growth in first-draft writing performance and at comparable rates. Qualitative analyses of interview data revealed that AWE’s influence on instruction was similar across contexts; specifically, the introduction of AWE resulted in both instructional contexts taking on characteristics consistent with a framework for deliberate practice.

With growing attention to "intelligent content" and "dynamic delivery" in the advent of connected technologies (i.e., Internet of Things, artificial intelligence agents), component content management and structured authoring skills are becoming increasingly required of technical communicators today. To produce reusable intelligent content, technical communicators need a systematic workflow and common authoring standard. Our experience in industry and in educating technical communicators has led us to seek out resources for understanding existing standards and practicing them with technical communication students. As such, both authors have used the Darwin Information Typing Architecture (DITA) markup standard and experienced what may be a perplexing process in content creation and management. Carlos Evia's book, Creating Intelligent Content with Lightweight DITA , caught our attention as the title suggests an accessible way into learning and applying what has become a widely adopted standard for structured authoring. Understanding that Lightweight DITA (LwDITA) does not aim to replace existing DITA standards, we approach this review not with an intention to examine its viability, but rather a focus on the rhetorical work in structured content authoring and its continuous evolution.

Present Tense would like to congratulate Patricia Fancher for being accepted into The Best of the Journals in Rhetoric & Composition, 2018 (Parlor Press). Patricia’s article, “Composing Artificial Intelligence: Performing Whiteness and Masculinity,” was published in Vol. 6 Iss. 1. Congrats!

The quest to understand the nuances of professional communication using computational tools have continued since, and many researchers in our field have embraced the new interdisciplinary approach now known as data science. Our quick metadata search on the journals and conference proceedings in technical and professional communication (TPC) revealed an increasing number of articles associated with terms commonly used in data science (e.g., big data, content analysis, text mining, sentiment analysis, topic modeling, network analysis) originating from numerous disciplines (e.g., corpus linguistics, computational linguistics, artificial intelligence, statistics, business analytics). Yet, the field of TPC is just beginning to embrace the power of data-driven approaches. This special issue extends Orr’s work by taking a snapshot of current work in data-driven approaches to the study of TPC.

The Writing Mentor TM (WM) application is a Google Docs add-on designed to help students improve their writing in a principled manner and to promote their writing success in postsecondary settings. WM provides automated writing evaluation (AWE) feedback using natural language processing (NLP) methods and linguistic resources. AWE features in WM have been informed by research about postsecondary student writers often classified as developmental (Burstein et al., 2016b), and these features address a breadth of writing sub-constructs (including use of sources, claims, and evidence; topic development; coherence; and knowledge of English conventions). Through an optional entry survey, WM collects self-efficacy data about writing and English language status from users. Tool perceptions are collected from users through an optional exit survey. Informed by language arts models consistent with the Common Core State Standards Initiative and valued by the writing studies community, WM takes initial steps to integrate the reading and writing process by offering a range of textual features, including vocabulary support, intended to help users to understand unfamiliar vocabulary in coursework reading texts. This paper describes WM and provides discussion of descriptive evaluations from an Amazon Mechanical Turk (AMT) usability task situated in WM and from users-in-the-wild data. The paper concludes with a framework for developing writing feedback and analytics technology.

Background: Employing natural language processing and latent semantic analysis, the current work was completed as a constituent part of a larger research project for designing and launching artificial intelligence in the form of deep artificial neural networks. The models were evaluated on a proprietary corpus retrieved from a data warehouse, where it was extracted from MyReviewers, a sophisticated web application purposed for peer review in written communication, which was actively used in several higher education institutions. The corpus of laboratory reports in STEM annotated by instructors and students was used to train the models. Under the Common Rule, research ethics were ensured by protecting the privacy of subjects and maintaining the confidentiality of data, which mandated corpus de-identification.Literature Review: De-identification and pseudonymization of textual data remains an actively studied research question for several decades. Its importance is stipulated by numerous laws and regulations in the United States and internationally with HIPAA Privacy Rule and FERPA.Research Question: Text de-identification requires a significant amount of manual post-processing for eliminating faculty and student names.  This work investigated automated and semi-automated methods for de-identifying student and faculty entities while preserving author names in cited sources and reference lists. It was hypothesized that a natural language processing toolkit and an artificial neural network model with named entity recognition capabilities would facilitate text processing and reduce the amount of manual labor required for post-processing after matching essays to a list of users’ names. The suggested techniques were applied with supplied pre-trained models without additional tagging and training. The goal of the study was to evaluate three approaches and find the most efficient one among those using a users’ list, a named entity recognition toolkit, and an artificial neural network.Research Methodology: The current work studied de-identification of STEM laboratory reports and evaluated the performance of the three techniques: brute forth search with a user lists, named entity recognition with the OpenNLP machine learning toolkit, and NeuroNER, an artificial neural network for named entity recognition built on the TensorFlow platform. The complexity of the given task was determined by the dilemma, where names belonging to students, instructors, or teaching assistants must be removed, while the rest of the names (e.g., authors of referenced papers) must be preserved.Results: The evaluation of the three selected methods demonstrated that automating de-identification of STEM lab reports is not possible in the setting, when named entity recognition methods are employed with pre-trained models. The highest results were achieved by the users’ list technique with 0.79 precision, 0.75 recall, and 0.77 F1 measure, which significantly outweighed OpenNLP with 0.06 precision, 0.14 recall, and 0.09 F1, and NeuroNER with 0.14 precision, 0.56 recall, and 0.23 F1.Discussion: Low performance of OpenNLP and NeuroNER toolkits was explained by the complexity of the task and unattainability of customized models due to imposed time constraints. An approach for masking possible de-identification errors is suggested.Conclusion: Unlike multiple cases described in the related work, de-identification of laboratory reports in STEM remained a non-trivial labor-intensive task. Applied out of the box, a machine learning toolkit and an artificial neural network technique did not enhance performance of the brute forth approach based on user list matching.Directions for Future Research: Customized tagging and training on the STEM corpus were presumed to advance outcomes of machine learning and predominantly artificial intelligence methods. Application of other natural language toolkits may lead to deducing a more effective solution.

This article argues that fake news is only one instantiation of a shift that literacy studies will need to reckon with to understand how people encounter texts on an everyday basis. It argues that looking at the information ecologies in which fake news circulates reveals a shift to the reliance on computational and automated writing systems to circulate texts and amplify their distribution. The article critically synthesizes existing literature and provides key examples of how algorithms and bots were deployed strategically to pollute the media ecology with fake news in the time immediately preceding the 2016 Presidential election in the United States. The argument ultimately raises a series of questions that literacy studies will need to confront given the influence of computation in contemporary information environments, including asking: how can people engage in responsible discourse in the face of rapidly evolving and exploitable technologies?

Phatic refers to the rhetorical function of creating effective communication channels, keeping them open, and establishing ongoing and fruitful relationships, all of which are vital in the age of digital rhetoric, social media, and global intercultural exchange. In this realm, the professional communicator functions less as an originator of new information and more as a space designer, a facilitator of others’ online interactions, a curator of user-generated content, and a communication leader. The phatic function—especially relevant to online interactions such as virtual teamwork, intercultural communication, and user help forums—deserves significant attention as a primary purpose for professional communication.

ABSTRACTTranshumanism that is centered on artificial intelligence shares core features with large-scale data collection and surveillance that commercial and governmental entities pursue: the idea that knowledge is informational in nature, that technologies are value neutral, and that ethical challenges can be framed in technical-procedural terms. In this article, I am mainly concerned with the latter, society-wide, manifestations of these features. Here, criticisms leading to technical-procedural changes in data practices are of limited use because they foster an illusion of foundational headway while leaving questionable assumptions about knowledge and values intact. Because what is closest is hardest to glean, we may more readily discern these assumptions if we see them operating in a milieu that is at once quite different and strikingly familiar. Ancient rhetoric manifests versions of our three factors. Plato's critique of rhetoric, along with aspects of his philosophical methodology, helps us see why we should contest increasingly prevalent views of knowledge and values—and do so before other constructions become unfathomable.

“This analysis suggests that, in order to interrupt the injustices that flourish in Silicon Valley and in tech culture, we must rhetorically and systematically disentangle masculinity and whiteness from intelligence.”

Academic literacy and student diversity: The case for inclusive practice Ursula Wingate (2015) ISBN-13: 978-1783093472. Pp. 208. Genre-based automated writing evaluation for L2 research writing: From design to evaluation and enhancement Elena Cotos (2014) ISBN-13: 978-1137333360. Pp. 302.

This article aims to engage specialists in writing pedagogy, assessment, genre study, and educational technologies in a constructive dialog and joint exploration of automated writing analysis as a potent instantiation of computer-enhanced assessment for learning. It recounts the values of writing pedagogy and, from this perspective, examines legitimate concerns with automated writing analysis. Emphasis is placed on the need to substantiate the construct-driven debate with systematic empirical evidence that would corroborate or refute interpretations, uses, and consequences of automated scoring and feedback tools intended for specific contexts. Such evidence can be obtained by adopting a validity argument framework. To demonstrate an application of this framework, the article presents a novel genre-based approach to automated analysis configured to support research writing and provides examples of validity evidence for using it with novice scholarly writers.

Supported by artificial intelligence (AI), the most advanced Automatic Writing Evaluation (AWE) systems have gained increasing attention for their ability to provide immediate scoring and formative feedback, yet teachers have been hesitant to implement them into their classes because correlations between the grades they assign and the AWE scores have generally been low. This begs the question of where improvements in evaluation may need to be made, and what approaches are available to carry out this improvement. This mixed-method study involved 59 cause and effect essays collected from English language learners enrolled in six different sections of a college level academic writing course and utilized theory proposed by Slater and Mohan (2010) regarding the developmental path of cause. The study compared the results of raters who used this developmental path with the accuracy of AWE scores produced by Criterion, an AWE tool developed by Educational Testing Service (ETS), and the grades reported by teachers. Findings suggested that if Criterion is to be used successfully in the classroom, writing teachers need to take a meaning-based approach to their assessment, which would allow them and their students to understand more fully how language constructs cause and effect. Using the developmental path of cause as an analytical framework for assessment may then help teachers assign grades that are more in sync with AWE scores, which in turn can help students gain more trust in the scores they receive from both their teachers and Criterion.

We often confuse commercial representation with political intervention. For instance, a recent Cheerios advertisement featuring a biracial family provided many people the evidence of a welcomed cultural shift, recognition of a growing acceptance of what might have been taboo and even illegal in the United States a handful of decades ago. We stumble upon another example as we realize that washing down a Chick-fil-A fried chicken sandwich with a 7–11 BigGulp has somehow become not one but two political acts of cultural defiance. While companies aligning themselves explicitly or implicitly for or against cultural politics might seem odd, the frequency of such events demonstrates a noticeable—and increasing—overlap between economic production and political intervention. At the risk of sounding clichéd, these cases remind us that we are what we eat. That said, what “we are” and “what we eat” are both at stake in contemporary culture because technological and media innovation have made that culture more malleable. Jeff Pruchnic's Rhetoric and Ethics in the Cybernetic Age: The Transhuman Condition does not delve directly into these particular events, but the problems the book engages help us better understand and respond to modes of cultural production that we must come to see as increasingly heterogeneous. What is the role of rhetoric in an economy of “just-in-time” accommodation?Tacking widely across cultural, economic, and biological registers, Rhetoric and Ethics in the Cybernetic Age seeks to theorize rhetorical possibility after cybernetics, a field in which every thing seems open to redesign and reinvention. Toward these ends, the book traffics in micro-studies: embryotic stem cell manipulation, a Burkebot, video game effects, stock market algorithms, political redistricting, a collection of shoes, among many more. What links these various items is the extent to which biological, cultural, social phenomena once considered autonomous are now susceptible to direct intervention through and as technological innovation. Pruchnic's central claim in response to this development is simple, albeit counterintuitive: contemporary technologies and media are evidence of an increased humanization of social and technological processes and are not inhuman forces of calculation and computation. This is to say that the proliferation of and increased reliance on information media and technological processes allow contemporary cultural practices to more effectively mimic the complexity and vitality of biological processes. While such a claim might be simply stated, its implications for understanding ethical engagement with technics may be quite profound for humanities study in general and for rhetorical scholarship in particular. Put differently, the implications concern the extent to which epistemological categories have always been shaped by supposedly inhuman forces of techne, which then refigure a host of available responses to changing technological conditions. The position allows us to explore and respond to cultural institutions that have markedly become less concerned with establishing mass markets than with identifying and intensifying market subsets that are fueled, in part, by more efficient methods of demographic research and more effective deployment of marketing techniques.Pruchnic's response to this moment is two-pronged. First—in a task occupying the book's first two chapters—he broadly traces how epistemological and technical domains are becoming conflated in contemporary culture. Second—in a series of case studies through the book's final three chapters—he articulates a version of rhetorical ethics robust enough to respond to such a conflation by engaging in specific analyses of contemporary culture. Taken as a whole, the book offers a theory of rhetorical practice and cultural analysis that moves away from logics of exclusion (classification, division, and separation) and instead emphasizes inclusionary logics that seek to establish and maintain ongoing processes of interaction.In the initial chapters, Pruchnic offers analyses of the conditions of contemporary culture, especially with regard to the ways in which cultural life is steeped in technological advancement. Key to this work is a genealogy that Pruchnic constructs and that he uses to trace how, through technics and media, “forms of knowledge/representation are not based on quantification or calculation but on dynamics processes for maintaining relationships” (13). Pruchnic arrives at this claim by arguing that we are witnessing an increasing overlap between the two previously distinct domains of logos and techne, the former largely encompassing reason and communication—traditional human activities—and the latter the material technologies and what has long thought to be nonhuman mechanics. These chapters propose that the traditional separation between these two domains allowed entire systems of ethical and political practice to be founded and sustained. We need not look too far to witness that these divisions play out explicitly in the university, where liberal arts, social sciences, and hard science are well instituted as distinct lines of inquiry. That these two domains now find themselves to be overlapping and have become less distinct is the cause of a great many of our contemporary “problems,” which include the fracturing of democratic processes and anthropocentric effects such as global climate change and armed unrest. Far from claiming that today is unlike any other, Pruchnic instead maintains that the logic undergirding much of these activities is different in kind only because of the speed and complexity with which these operations are undertaken. In response, he proposes that contemporary culture should be understood and characterized as a “technologic,” that is, as “forms of interaction and engagement that not only find their most explicit manifestation in contemporary technologies but signal the imbrication, or recombination, of techne (formalistic and goal-directed strategies) with logos (both in its sense of human ‘higher reason’ and of the general structuring of human life) that Plato attempted to so carefully separate and the division of which became a touchstone for Western thought” (9).As it combines two terms, the “technologic” helps refigure the many debates and problems we find ourselves a part of. Pruchnic finds a basis for this refiguring through a careful reading of Martin Heidegger's work concerning technology, especially as it pertains to the ontological. Toward this reading, Pruchnic goes on to argue that Heidegger's critique of technology's increasing centrality in human affairs has less force now because it regards contemporary technology as only calculation, reductionism, or standardization. Pruchnic instead revisits Heidegger's ontological approach to historical analysis and proposes that we might consider the developments that Heidegger casts as epochs of self-understanding as a “history of techniques” (71). The turn toward techniques is buoyed, as Pruchnic contends, contra many of the criticisms of Heidegger's conflation of material technologies and conceptual frameworks, by the fact that such a conflation may actually be a strength in reorganizing our capacities for responding to technological innovation. Recasting Heidegger's historical analysis as one that traces techniques eliminates issues of authenticity and emphasizes instead “elements of rhetorical thought and praxis that were largely crowded out by Platonic thought” (64). Rhetoric, considered thusly, then is better understood to be “a vector of forces or practices … premised somewhere between the application of physical force and the immaterial realm of pure reason or judgment” (17). This analysis expands Pruchnic's initial proposal, suggesting that many of our humanistic programs and modes of cultural critique—for which Heidegger serves as the most productive example—that privileged the rational, political actor may now be compelled to contend with affective or “subrational” forces as a necessary part of cultural work.Taking affective force seriously has several consequences. In particular, affective approaches focus on processes over individuals as well as asignification alongside signification. The first among these had follows from and led to a revaluation of the importance of ecological relations. Pruchnic locates our interest in ecology, as it regards our understanding of technologic, in the Macy conferences, a series of interdisciplinary discussions regarding the future of science that took place from 1941 to 1960. While the organizers hoped that they would unify disparate branches of science and theory, the conferences are remembered mostly for their work on cybernetics and artificial intelligence. Pruchnic finds in the Macy conferences two primary imports for rhetorical theory. First is the shift toward considering the ecological interaction between actor and environment. This shift gave rise to accounts of homeostatic processes that treated human and technological interactions as a circulation of agency and not the result of a central human actor controlling a nonhuman environment. Second, the conference revised notions of teleological aims often at the core of instrumental orientations to technology, a switch that especially impacts how telos may be related to technologies whose own “purpose” shares functions with many of our own in that they have changed over time. Together, these two findings have much significance for rhetorical theory and practice, as they undercut the reductive communication models that rhetoric is often charged as facilitating.In addition to outlining the conceptual work done by the conferences, much of which the humanities are only now coming around to appreciate, Pruchnic shows how early cybernetic thinkers drew heavily on rhetorical technique to conceptualize cybernetic theory. Both cybernetics and rhetorical practice invent, develop, and encourage robust and flexible techniques for organizing processes of interaction. Pruchnic focuses on how “techniques” may enable theory to be applied through rhetorical and humanities practice, defining the term as a set of “flexibly responsive practices that are directed toward motivating the performance of a generic action and/or the maintenance of a general equilibrium” (16). “Techniques” as a term and concept allows for the development of a technologic that recognizes, Pruchnic notes, that “the very same advances in, and increasing importance of, technologies and communicational media so apparent in other areas under review in this essay are crucial considerations for any attempt to rethink the contemporary status of economics, let alone labor, in the present moment” (31). Pruchnic's approach both widens the scope of his project, allowing him to include a wide array of interdisciplinary discussions, and it also does the important work of refiguring some of the practices we experience as central to rhetorical work.Pruchnic's understanding of techniques and his alignment with the complexity that subtends cybernetics leads him to outline an ethical response that affirms its imbrication within those same modes of technological production that it seeks to change rather than to adopt a critical practice that seeks its intervention from a position outside. Why this is a crucial pairing is evident in how Pruchnic understands rhetoric's role in contemporary culture: “The fundamental challenge of the present is not so much to discover some radical alternative to contemporary conditions … but to figure out how these same techniques already immensely immanent in contemporary capitalism can be made to produce different outcomes” (38). Such a task is even more pressing when we consider that scientific authority to produce and maintain what counts as fact vies with the demand to prioritize “direct application and intervention as the core goals of scientific research and knowledge production” (25). While Pruchnic often cites the work that science does, by no means is the cybernetic moment restricted to lab coats and electrical circuitry. What is true in science is also true in other realms. For example, the granular redistricting of voting districts preselects the voters charged with voting for certain politicians, and manufacturing is able to produce more specific goods for more specific subsets of markets. Basic business notions of supply and demand have become as complex and intertwined as communication's outdated sender-receiver model.These realizations lead Pruchnic to enter an ongoing conversation regarding the role of humanism in rhetoric and cultural analysis. Pruchnic carefully traces the development of posthumanism (an analysis that I cannot do justice to here), noting a tension in most posthuman thought insofar as it “ends up reinforcing [humanism's] superiority or autonomy, the position of the human as the one who ‘decides’” (50). This tension leads him to posit that “we might have to reconsider humanism as something of a rhetorical strategy rather than a philosophical doctrine” (54) and to propose the “transhuman condition” as a key organizing principle to explain contemporary culture. Working from Julian Huxley's short essay “Transhumanism,” Pruchnic posits that the increase in and proliferation of technological intervention helps displace categories of natural and artificial in favor of the idea of flexible but robust processes. “Transhuman” as a term allows Pruchnic to articulate four connected processes of interaction that characterize our contemporary technologic: transition, which details the ways that the continuing process of defining what is and can be human has accelerated in recent decades; transference, which denotes the ways that functional operations can be shared and joined between previously separated domains (human, nonhuman animals, and technologies); transactional, which refers to common processes and procedures for establishing equilibrium rather than a discrete object to be passed along; and transversal, which describes the unusual connections between separated domains of activity such as nature and culture, logos and techne. These terms are threaded throughout the book as a way to organize the intense intermingling of previously separate domains. Although these operations are distinct enough to warrant separate terms, they become confused, as each relies on the others to articulate its own operation. This, however, may be a strength as well, since the confusion performs something of the complexity that the book seeks to trace.Pruchnic's move to the transhuman as a controlling concept in place of others more commonly used today (e.g., posthumanism, antihumanism) opens an avenue of inquiry in which human activity is marked less by periodization than by processes. This avenue then positions cybernetics not as a distinct break but as an intensification of a technologic that extends far beyond our contemporary moment. Pruchnic closes the general framing of the transhuman condition with the aforementioned “history of techniques.” Our “parametric present” is a condition heralded by the standardization of time through clocks and the development of now fundamental physics, a perspective that challenges that idea that we have only recently broken away from more humanism. What characterizes the “parametric present” has been hinted at throughout this review. The conflation of techne and logos provides a greater capacity for miming biological processes in connection with markets, science, media, and democratic governance by its admission of previously nonhuman technology into our approach to epistemological structures. Such a conflation resists a reduction of technologics to mere quantification or calculation and instead gestures toward contemporary culture as concerned with algorithmically managing associations with granular detail.So, where does rhetoric fit in again?While the initial chapters sketch the broad terms of the conditions of contemporary culture in the cybernetic age, the three final chapters isolate important threads for rhetorical ethics. To start, chapter 3, “Rhetoric and the Age of Intelligent Machines,” offers a specific site in which rhetoric and cybernetic theory converse, revisiting Kenneth Burke's response to cybernetics and information technology to show how rhetoric might be revised with respects to technological innovation and social power. While Burke's anxieties about technology are well documented, Pruchnic finds that offers ways of responding to our technological moment. 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This study examined the impact of different forms of feedback on the writing of a group of 82 adolescent students in secondary English classes. During a 6-week intervention, students were randomly assigned to one of three feedback groups: peer feedback on pen-and-paper drafts, teacher feedback delivered electronically through a course management system, and automated feedback generated through computer-based writing evaluation software. Pre- and post-measures of student writing quality, length, and correctness were analyzed, and survey data explored student perceptions of their experiences. Findings indicate that all students, regardless of which form of feedback they received, wrote longer essays and scored higher on holistic ratings at post test than they did at pretest. Neither language status nor group assignment had a greater or lesser impact on performance on length or holistic quality. However, differences between feedback groups spiked on the proximal measure that examined mastery of particular aspects of the genre being taught. Both peer feedback and teacher feedback delivered electronically had a statistically significant impact on student performance in the genre of open-ended response. The article concludes with a discussion of the implications of these findings for future research and instruction in the secondary context.

The inclusion of peer feedback activities into the academic writing process has become common practice in higher education. However, while research has shown that students perceive many features of peer feedback to be useful, the actual effectiveness of these features in terms of measurable learning outcomes remains unclear. The aim of this study was to investigate the linguistic and review features of peer feedback and how these might influence peers to accept or reject revision advice offered in the context of academic writing among L2 learners. A corpus-based machine learning approach was employed to test three different algorithms (logistic regression, decision tree, and random forests) on three feature models (linguistic, review, and all features) to determine which algorithm offered the best predictive results and to determine which feature model most accurately predicts implementation. The results indicated that random forests is the most effective way of modeling the different features. In addition, the feature model containing all features most accurately predicted implementation. The findings further suggest that directive comments and multiple peer comments on the same topic included in the feedback process seem to influence implementation.

This study examines the potential for computational tools and human raters to classify paragraphs based on positioning. In this study, a corpus of 182 paragraphs was collected from student, argumentative essays. The paragraphs selected were initial, middle, and final paragraphs and their positioning related to introductory, body, and concluding paragraphs. The paragraphs were analyzed by the computational tool Coh-Metrix on a variety of linguistic features with correlates to textual cohesion and lexical sophistication and then modeled using statistical techniques. The paragraphs were also classified by human raters based on paragraph positioning. The performance of the reported model was well above chance and reported an accuracy of classification that was similar to human judgments of paragraph type (66% accuracy for human versus 65% accuracy for our model). The model’s accuracy increased when longer paragraphs that provided more linguistic coverage and paragraphs judged by human raters to be of higher quality were examined. The findings support the notions that paragraph types contain specific linguistic features that allow them to be distinguished from one another. The finding reported in this study should prove beneficial in classroom writing instruction and in automated writing assessment.

A well-known ambiguity in the term ‘argument’ is that of argument as an inferential structure and argument as a kind of dialogue. In the first sense, an argument is a structure with a conclusion supported by one or more grounds, which may or may not be supported by further grounds. Rules for the construction and criteria for the quality of arguments in this sense are a matter of logic. In the second sense, arguments have been studied as a form of dialogical interaction, in which human or artificial agents aim to resolve a conflict of opinion by verbal means. Rules for conducting such dialogues and criteria for their quality are part of dialogue theory. Usually, formal accounts of argumentation dialogues in logic and artificial intelligence presuppose an argument-based logic. That is, the ways in which dialogue participants support and attack claims are modelled as the construction of explicit arguments and counterarguments (in the inferential sense). However, in this paper formal models of argumentation dialogues are discussed that do not presuppose arguments as inferential structures. The motivation for such models is that there are forms of inference that are not most naturally cast in the form of arguments (such as abduction, statistical reasoning and coherence-based reasoning) but that can still be the subject of argumentative dialogue. Some recent work in artificial intelligence is discussed which embeds non-argumentative inference in an argumentative dialogue system, and some general observations are drawn from this discussion.

This interview traces Burns's transition from military officer to professor, provides insight for junior scholars in computers and composition, and seeks connections among military training, artificial intelligence, and teaching with technology.

The teaching and learning of writing was examined in ten diverse K-12 schools in which all of the students in one or more classrooms had individual access to laptop computers. Substantial positive changes were observed in each stage of the writing process, including better access to information sources for planning and pre-writing; easier drafting of papers, especially for students with physical or cognitive disabilities that made handwriting laborious; more access to feedback, both from teachers, who could read printed papers much more quickly than handwritten ones, and, in some schools, by automated writing evaluation programs; more frequent and extensive revision; and greater opportunities to publish final papers or otherwise disseminate them to real audiences.

Analogical reasoning has long been an important tool in the production of scientific knowledge, yet many scientists remain hesitant to fully endorse (or even admit) its use. As the teachers of scientific and technical writers, we have an opportunity and responsibility to teach them to use analogy without their writing becoming “overly inductive,” as Aristotle warned. To that end, I here offer an analysis of an example of the effective use of analogy in Rodney Brooks's “Intelligence Without Representation.” In this article, Brooks provides a model for incorporating these tools into an argument by building four of them into an enthymeme that clearly organizes his argument. This combination of inductive and deductive reasoning helped the article become a very influential piece of scholarship in artificial intelligence research, and it can help our students learn to use analogy in their own writing. Every one who effects persuasion through proof does in fact use either enthymemes or examples: there is no other way. (Aristotle, 1984b Aristotle. 1984b. The rhetoric and the poetics of Aristotle, Edited by: Roberts, W. R. and Bywater, I. New York: The Modern Library. [Google Scholar], p. 26)

When faced with the tasks of reading and writing a complex technical paper, many nonnative scientists and engineers who have a solid background in English grammar and vocabulary lack an adequate knowledge of commonly used structural patterns at the discourse level. In this paper, we propose a novel computer software tool that can assist these people in the understanding and construction of technical papers, by automatically identifying the structure of writing in different fields and disciplines. The system is tested using research article abstracts and is shown to be a fast, accurate, and useful aid in the reading and writing process.

Reviews 113 are able to do so with a useful vocabulary, specific examples, and an assessment of the landscape of rhetorical practice that sets a new pace. Her title, then, "We Are Coming", gains increasing significance. Indeed, African American women are coming onto the rhetorical scene, and this analysis contributes greatly to our ability to take into account in interesting ways what their presence means. JACQUELINE JONES ROYSTER The Ohio State University Lynette Hunter, Critiques of Knowing: Situated Textualities in Science, Computing, and the Arts (London and New York: Routledge, 1999), vi + 239 pp. Critiques of Knowing is a disarmingly accurate title for Lynette Hunter's most recent book, a study of the relevance of rhetoric to critical theories of language in several fields. Standpoint theory, Hunter proposes, integrated with rhetorical understandings of ethos, topos, and audience, can both illuminate, and exemplify the need for a rhetorical critique of "critical and aesthetic discourses for talking about communication, textuality, and the arts" (p. 7). The discussion moves patiently and informatively through discourses about ideology and the nation state, agency, the subject, recent studies of artificial intelligence and computing, hypertext models of literary texts, "scientific" discourse studies and linguistic poetics, feminist critiques of science, and feminist aesthetics. Hunter weaves rhetoric into the methods and languages of these disciplines with subtlety and common sense; readers will find in each chapter an up to date review of current critical theory in the fields reviewed. Another major accomplishment of the study as a whole is a collateral appraisal of the languages and epistemologies, stated and unstated, that each field employs. The comparison is no easy task, particularly since the fields under scrutiny have been prominent advocates of critiquing knowledge, understood as comprehension of the "real" 114 RHETORICA by subjects capable of knowing, and of representing their knowledge in representational, informative texts. This relentless critique of knowledge and language in recent theory, Hunter asserts, has resulted in a barrage of pluralisms and relativisms, each with its own canonical ideology. Hunter teases out different versions of an "essentialist-relativist" standoff that has emerged again and again among recent ideological constructions of plurality (pp. 6-7). In characterizing many of these problems Hunter is not alone; she will find readers welcoming her positions. What makes her discussion original and especially valuable is the way in which she brings to this impasse several richly drawn definitions of rhetoric. Because of its historical and conceptual self awareness as "inexorably different to the real world" in any literal or scientific sense, rhetoric can help construct an analysis of stance which will position the discourses of the disciplines historically, politically, and socially (p. 6). The prospect that rhetoric may be able to integrate and amplify a number of critical discourses about language that are currently bogged down in confessing their own impossibility and meaninglessness is a welcome vision. Hunter's exposition of the ethical and epistemological adjustments rhetoric could provide to contemporary critical discourses is also an anatomy of the past and present wealth that resides in rhetorical studies that continue to be marginalized by so many fields. The chapters are arranged by discipline: contemporary studies of the ideologies of nation-states, studies of artificial intelligence and computing applications within the humanities, hypertext methodologies, feminist critiques of science, and feminist critiques of aesthetics. Hunter's analysis establishes an important parallelism: a lack of rhetorical self awareness has hampered the discussion of the subject and of agency, of intelligence and knowledge, of the ethics of critical discourses visa -vis their contexts and audiences. Hunter defines her overall goal as "a critique of critical and aesthetic discourses for talking about communication, textuality, and the arts" (p. 7). The essentialistrelativist standoff that Hunter seeks to redress has locked many branches of discourse studies, including linguistics, artificial intelligence, computing, rhetoric and poetics, into methodologies that, somewhat oddly, base social and political tolerance for all Reviews 115 discursive practices upon scientific models of neutral description and quantitative analysis. Somehow, according to many of these models, discourses are produced by "the culture" or by "language". Alternatively, we find accusations of "essentialism" or "enlightenment humanism" hurled at any and all references to the subject, to agency, to an ethnic...

The paper surveys studies of the process model for understanding writing, focusing in particular on problem-solving strategies in the writing process. It then presents a case study of the use of issue trees-a hierarchal network of goals not unlike the decision trees used in management science and artificial intelligence-to guide the writing process of the second author as he wrote a technical report. A good issue tree shows the relationships between various pieces of information: which information is central and which is supportive or incidental. Issue trees offer engineers a visual view of their writing plan. By building a hierarchal issue tree to illustrate the logical links of the proposed writing task, the engineer can put an overlay of "technology" on the task of writing-an overlay that may "trick" the unwilling writer into writing, and writing well.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>

Research Article| November 01 1991 Rhetoric and Artificial Intelligence Lynette Hunter Lynette Hunter School of English, The University of Leeds, Leeds LS2 9JT, England. Search for other works by this author on: This Site PubMed Google Scholar Rhetorica (1991) 9 (4): 317–340. https://doi.org/10.1525/rh.1991.9.4.317 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn Email Tools Icon Tools Cite Icon Cite Search Site Citation Lynette Hunter; Rhetoric and Artificial Intelligence. Rhetorica 1 November 1991; 9 (4): 317–340. doi: https://doi.org/10.1525/rh.1991.9.4.317 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentRhetorica Search This content is only available via PDF. Copyright 1991, The International Society for the History of Rhetoric1991 Article PDF first page preview Close Modal You do not currently have access to this content.

The widespread use of irony in academic writing raises issues not considered in most psychological, linguistic, or literary approaches to irony: How is irony signalled in a written text? What are the constraints of politeness within academic discourse that govern the use and interpretation of irony? This essay considers the interpretation of one kind of irony—ironic quotation—in a controversy between linguists and artificial intelligence researchers. Irony in these published exchanges is then compared to irony in conference discussions and unpublished papers in linguistics and to irony in other disciplines. Although the analysis follows psychological and linguistic accounts of irony as echoic mention in which the same words can be reused with a different intention, it begins with the rhetorical relation of the quoting writer, the quoted writer, and the reader as members of disciplinary communities. The instances of irony that are considered both define these relations and assume them as a basis for interpretation. This analysis suggests that the study of irony can serve as a means of understanding disciplines and of examining our own taken-for-granted assumptions as academic writers.

Reviews of several electronic dictionaries are presented. As part of the review process, to determine how up-to-date these dictionaries are, the reviewer chose 50 words (such as artificial intelligence, backplane, digital switching, graded-index fiber, and virtual circuit) that he believed should be in a recent dictionary, even though a writing/publishing cycle could take up to 3 years. Then the dictionaries were checked against this list to arrive at a Current Factor for each.

The current job market favors young technical writers who are skilled in the way of the computer both as a subject of writing and as a production tool. In the technical writing classroom students can be exposed to this important technology through assignments that include computerized instruction, word processing, text analysis, artificial intelligence, and communications.

An expert system is an application of artificial intelligence which requires the transfer of knowledge from human to machine. The acquisition of this knowledge from experienced practitioners (domain experts) is typically inefficient. Problems associated with the subjective reporting of knowledge must be overcome. To do this, a structured rather than unstructured interviewing approach can be used by knowledge engineers. Open, closed, and probing questions as well as direction responses should be used, together with a general-to-specific technique. The goal of the knowledge acquisition interview is to obtain complete, accurate, and reliable knowledge for the expert system.

The following treatise surveys the issues and approaches for designing a computer system capable of reading, understanding, and writing technical reports. Recent progress in computer science and artificial intelligence research is used to specify the nature of the modules in the system. The processing of a sample text is observed during the phases of reading and writing a report on the origin of sunspots. The author advances some proposals for correlating syntax and semantics of English from a procedural standpoint. The discussion is illustrated with structural diagrams.

Evolving from principles observed in telecommunications and servomechanisms, cybernetics is now a broad interdisciplinary science that embraces all biological and environmental activities, including human thought and social organization. Cybernetics provides the unifying basis for various scientific techniques used in business management today, but computer-aided administration and factory automation are only a start. Eventually, comprehensive systems of artificial intelligence will function at the highest level to direct, not merely manage, the total operation of industry, even the administration of society itself. Clearly, there will be marked impact on human communication, especially in scientific and technical publications for marketing and training.

This case study examines how collaboration between a writing centre manager and an educational developer created new opportunities to advance writing pedagogy at a mid-sized Canadian university. Initially born from our university’s response to generative artificial intelligence, our effort both responds to perceived threats to the future of writing studies and attempts to preserve our work through new opportunities. Collaboration between writing centres and faculty development is under-represented in the literature, yet we have found the marginality of the third space to be a productive one from which to grow our campus’ writing community from “under the curriculum” (Hunt, 2006, p. 371). In this paper, we present three examples of collaborations between a writing centre manager and an educational developer—creating a community of practice, facilitating workshops for graduate students, and presenting to our university’s Senate. The outcomes of our reflections offer perspectives on AI and writing pedagogy, highlight the importance of cross-unit partnerships, and illustrate how third space professionals can offer critical writing-related perspectives to institutions where formal writing programs do not exist—ultimately helping make visible the often decentralized work of writing studies professionals in Canada.