Book Review| February 01 2017 Review: Scientists as Prophets: A Rhetorical Genealogy Lynda Walsh, Scientists as Prophets: A Rhetorical Genealogy. New York: Oxford University Press, 2013. pp. 264. ISBN: 978-01-99-85709-8 (HB) Thomas M. Lessl Thomas M. Lessl Thomas M. Lessl Department of Communication Studies University of Georgia 625 Caldwell Hall Athens, GA 30602 USA tlessl@uga.edu Search for other works by this author on: This Site PubMed Google Scholar Rhetorica (2017) 35 (1): 118–120. https://doi.org/10.1525/rh.2017.35.1.118 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Cite Icon Cite Search Site Citation Thomas M. Lessl; Review: Scientists as Prophets: A Rhetorical Genealogy. Rhetorica 1 February 2017; 35 (1): 118–120. doi: https://doi.org/10.1525/rh.2017.35.1.118 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. © 2017 by The International Society for the History of Rhetoric. All rights reserved. Please direct all requests for permission to photocopy or reproduce article content through the University of California Press's Reprints and Permissions web page, http://www.ucpress.edu/journals.php?p=reprints.2017 Article PDF first page preview Close Modal You do not currently have access to this content.

Book Review| February 01 2017 Review: La sociabilité épistolaire chez Cicéron Jacques-Emmanuel Bernard, La sociabilité épistolaire chez Cicéron, Paris: Honoré Champion, 2013. 641 pp. ISBN 978-2-7453-2591-4 Marcos Martinho Marcos Martinho Marcos Martinho rua Peixoto Gomide, 601, ap. 132 CEP: 01409-001 Sao Paulo / SP Brasil marcos.martinho@usp.br Search for other works by this author on: This Site PubMed Google Scholar Rhetorica (2017) 35 (1): 112–116. https://doi.org/10.1525/rh.2017.35.1.112 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Cite Icon Cite Search Site Citation Marcos Martinho; Review: La sociabilité épistolaire chez Cicéron. Rhetorica 1 February 2017; 35 (1): 112–116. doi: https://doi.org/10.1525/rh.2017.35.1.112 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. © 2017 by The International Society for the History of Rhetoric. All rights reserved. Please direct all requests for permission to photocopy or reproduce article content through the University of California Press's Reprints and Permissions web page, http://www.ucpress.edu/journals.php?p=reprints.2017 Article PDF first page preview Close Modal You do not currently have access to this content.

Book Review| February 01 2017 Review: The Genres of Rhetorical Speeches in Greek and Roman Antiquity Cristina Pepe, The Genres of Rhetorical Speeches in Greek and Roman Antiquity. International Studies in the History of Rhetoric 5. Leiden and Boston: Brill, 2013. xviii + 618 pp., ISBN: 978-90-04-24984-4 Mike Edwards Mike Edwards Mike Edwards Department of Humanities University of Roehampton Erasmus House Roehampton Ln, London SW15 5PU United Kingdom Mike.Edwards@roehampton.ac.uk Search for other works by this author on: This Site PubMed Google Scholar Rhetorica (2017) 35 (1): 110–112. https://doi.org/10.1525/rh.2017.35.1.110 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Cite Icon Cite Search Site Citation Mike Edwards; Review: The Genres of Rhetorical Speeches in Greek and Roman Antiquity. Rhetorica 1 February 2017; 35 (1): 110–112. doi: https://doi.org/10.1525/rh.2017.35.1.110 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. © 2017 by The International Society for the History of Rhetoric. All rights reserved. Please direct all requests for permission to photocopy or reproduce article content through the University of California Press's Reprints and Permissions web page, http://www.ucpress.edu/journals.php?p=reprints.2017 Article PDF first page preview Close Modal You do not currently have access to this content.

The review of work on ancient Roman rhetoric that follows below is the first of what I hope will become a regular feature in Advances in the History of Rhetoric—comprehensive reviews of scholarship in a given area. Subjects for these reviews and author-reviewers can be proposed to the editor or invited by the editor. Proposals from senior scholars working in collaboration with graduate students are especially welcome.

This is a review of the book  Writing Your Master’s Thesis: From A to Zen  by Lynn P. Nygaard.

Although writing centers in Germany are among the oldest and fastest growing outside of North America, scholarship produced within them remains largely unknown outside national borders due to challenges inherent in translingual research. This article helps remedy this gap by rendering accessible debates in ‘writing studies’ (‘Schreibwissenschaft’) in German-speaking countries, where a number of projects are underway to define the field at this moment of its maturation. By focusing on one such initiative in Germany, Stephanie Dreyfürst and Nadja Sennewald’s edited collection Schreiben: Grundlagentexte zur Theorie, Didaktik und Beratung (Writing: Foundational Texts on Theory, Pedagogy, and Consultations) (2014), I use the monograph as a case study for investigating larger scholarly conversations about the state of writing studies in the region. In doing so, I propose a new genre for transnational research—the translingual review. More thickly descriptive than the book review, the translingual review situates the edited or authored monograph within local disciplinary and institutional contexts. This particular translingual review adopts a comparative framework, examining how German-language scholarship extends Anglo-American research in innovative ways, particularly in its uses of writing process research.

• Background: Researchers have been working towards better understanding differences in professional disciplinary writing (e.g., Ewer & Latorre, 1969; Hu & Cao, 2015; Hyland, 2002; Hyland & Tse, 2007) for decades. Recently, research has taken important steps towards understanding disciplinary variation in student writing. Much of this research is corpus-based and focuses on lexico-grammatical features in student writing as captured in the British Academic Written English (BAWE) corpus and the Michigan Corpus of Upper-level Student Papers (MICUSP). The present study extends this work by analyzing lexical and cohesion differences among disciplines in MICUSP. Critically, we analyze not only linguistic differences in macro-disciplines (science and engineering), but also in micro-disciplines within these macro-disciplines (biology, physics, industrial engineering, and mechanical engineering).\n• Literature Review: Hardy and Römer (2013) used a multidimensional analysis to investigate linguistic differences across four macro-disciplines represented in MICUSP. Durrant (2014, in press) analyzed vocabulary in texts produced by student writers in the BAWE corpus by discipline and level (year) and disciplinary differences in lexical bundles. Ward (2007) examined lexical differences within micro-disciplines of a single discipline.\n• Research Questions: The research questions that guide this study are as follows:\n1. Are there significant lexical and cohesive differences between science and engineering student writing? 2. Are there significant lexical and cohesive differences between micro-disciplines within science and engineering student writing?\n• Research Methodology: To address the research questions, student-produced science and engineering texts from MICUSP were analyzed with regard to lexical sophistication and textual features of cohesion. Specifically, 22 indices of lexical sophistication calculated by the Tool for the Automatic Analysis of Lexical Sophistication (TAALES; Kyle & Crossley, 2015) and 38 cohesion indices calculated by the Tool for the Automatic Analysis of Cohesion (TAACO; Crossley, Kyle, & McNamara, 2016) were used. These features were then compared both across science and engineering texts (addressing Research Question 1) and across micro-disciplines within science and engineering (biology and physics, industrial and mechanical engineering) using discriminate function analyses (DFA).\n• Results: The DFAs revealed significant linguistic differences, not only between student writing in the two macro-disciplines but also between the micro-disciplines. Differences in classification accuracy based on students’ years of study hovered at about 10%. An analysis of accuracies of classification by paper type found they were similar for larger and smaller sample sizes, providing some indication that paper type was not a confounding variable in classification accuracy.\n• Discussion: The findings provide strong support that macro-disciplinary and micro-disciplinary differences exist in student writing in these MICUSP samples and that these differences are likely not related to student level or paper type. These findings have important implications for understanding disciplinary differences. First, they confirm previous research that found the vocabulary used by different macro-disciplines to be “strikingly diverse” (Durrant, 2015), but they also show a remarkable diversity of cohesion features. The findings suggest that the common understanding of the STEM disciplines as “close” bears reconsideration in linguistic terms. Second, the lexical and cohesion differences between micro-disciplines are large enough and consistent enough to suggest that each micro-discipline can be thought of as containing a unique linguistic profile of features. Third, the differences discerned in the NLP analysis are evident at least as early as the final year of undergraduate study, suggesting that students at this level already have a solid understanding of the conventions of the disciplines of which they are aspiring to be members. Moreover, the differences are relatively homogeneous across levels, which confirms findings by Durrant (2015) but, importantly, extends these findings to include cohesion markers.\n• Conclusions: The findings from this study provide evidence that macro-disciplinary and micro-disciplinary differences at the linguistic level exist in student writing, not only in lexical use but also in text cohesion. A number of pedagogical applications of writing analytics are proposed based on the reported findings from TAALES and TAACO. Further studies using different corpora (e.g., BAWE) or purpose assembled corpora are suggested to address limitations in the size and range of text types found within MICUSP. This study also points the way toward studies of disciplinary differences using NLP approaches that capture data which goes beyond the lexical and cohesive features of text, including the use of part-of-speech tags, syntactic parsing, indices related to syntactic complexity and similarity, rhetorical features, or more advanced cohesion metrics (latent semantic analysis, latent Dirichlet allocation, Word2Vec approaches).

Aim: This research note narrates existing and continuing potential crossover between the digital humanities and writing studies. I identify synergies between the two fields’ methodologies and categorize current research in terms of four permutations, or “valences,” of the phrase “writing analytics.” These valences include analytics of writing , writing of analytics , writing as analytics , and analytics as writing . I bring recent work in the two fields together under these common labels, with the goal of building strategic alliances between them rather than to delimit or be comprehensive. I offer the valences as one heuristic for establishing connections and distinctions between two fields engaged in complementary work without firm or definitive discursive borders. Writing analytics might provide a disciplinary ground that incorporates and coheres work from these different domains. I further hope to locate the areas in which my current research in digital humanities, grounded in archival studies, might most shape writing analytics. Problem Formation: Digital humanities and writing studies are two fields in which scholars are performing massive data analysis research projects, including those in which data are writing or metadata that accompanies writing. There is an emerging environment in the Modern Language Association friendly to crossover between the humanities and writing studies, especially in work that involves digital methods and media. Writing analytics accordingly hopes to find common disciplinary ground with digital humanities, with the goal of benefitting from and contributing to conversations about the ethical application of digital methods to its research questions. Recent work to bridge digital humanities and writing studies more broadly has unfortunately focused more on territorial and usability concerns than on identifying resonances between the fields’ methodological and ethical commitments. Information Collection: I draw from a history of meta-academic literature in digital humanities and writing studies to review their shared methodological commitments, particularly in literature that recognizes and responds to pushback against the fields’ ostensible use of extra-disciplinary methods. I then turn to current research in both fields that uses and critiques computational techniques, which is most relevant to writing analytics’ articulated focus on massive data analysis. I provide a more detailed explanation, drawing from my categorization of this work, of the conversations in digital humanities surrounding the digital archives that enable data analysis. Conclusions: A review of past and current research in digital humanities and writing studies reveals shared attention to techniques for tokenizing texts at different scales for analysis, which is made possible by the curation of large corpora. Both fields are writing new genres to compose this analysis. In these genres, both fields emphasize process in their provisional work, which is sociocognitively repurposed in different rhetorical contexts. Finally, both fields recognize that the analytical methods they employ are themselves modes of composition and argumentation. An ethics of data transformation present in digital humanities, however, is largely absent from writing studies. This ethics comes to digital humanities from the influence of textual studies and archival studies. Further research in writing analytics might benefit from reframing writing corpora as archives—what Paul Fyfe (2017) calls a shift from “data mining” to “data archaeology”—in its analyses. This is especially true for analyses of text, which in particular foreground writing and analysis of writing as acts of transformation. Directions for Further Research: I recommend that future efforts to find crossover between digital humanities and writing studies do so by identifying their common values rather than trying to co-opt language and spaces or engaging in broad definitional work. I further provide a set of guiding principles that writing analytics might follow in order to pursue research that draws upon and contributes to both digital humanities and writing studies. These research projects might consider and account for the silences of writing corpora—unseen versions of documents, and documents’ elements not described in structured data—while attending to the silences that these efforts might in turn (re)produce.

Background: A shift of focus has been marked in recent years in the development of automated essay scoring systems (AES) passing from merely assigning a holistic score to an essay to providing constructive feedback over it. Despite all the major advances in the domain, many objections persist concerning their credibility and readiness to replace human scoring in high-stakes writing assessments. The purpose of this study is to shed light on how to build a relatively simple AES system based on five baseline writing features. The study shows that the proposed AES system compares very well with other state-of-the-art systems despite its obvious limitations. Literature Review: In 2012, ASAP (Automated Student Assessment Prize) launched a demonstration to benchmark the performance of state-of-the-art AES systems using eight hand-graded essay datasets originating from state writing assessments. These datasets are still used today to measure the accuracy of new AES systems. Recently, Zupanc and Bosnic (2017) developed and evaluated another state-of-the-art AES system, called SAGE, which enclosed new semantic and consistency features and provided for the first time an automatic semantic feedback. SAGE’s agreement level between machine and human scores for ASAP dataset #8 (the dataset also of interest in this study) was measured and had a quadratic weighted kappa of 0.81, while it ranged for 10 other state-of-the-art systems between 0.60 and 0.73 (Chen et al., 2012; Shermis, 2014). Finally, this section discusses the limitations of AES, which come mainly from its omission to assess higher-order thinking skills that all writing constructs are ultimately designed to assess. Research Questions: The research questions that guide this study are as follows: RQ1: What is the power of the writing analytics tool’s five-variable model (spelling accuracy, grammatical accuracy, semantic similarity, connectivity, lexical diversity) to predict the holistic scores of Grade 10 narrative essays (ASAP dataset #8)? RQ2: What is the agreement level between the computer rater based on the regression model obtained in RQ1 and the human raters who scored the 723 narrative essays written by Grade 10 students (ASAP dataset #8)? Methodology: ASAP dataset #8 was used to train the predictive model of the writing analytics tool introduced in this study. Each essay was graded by two teachers. In case of disagreement between the two raters, the scoring was resolved by a third rater. Basically, essay scores were the weighted sums of four rubric scores. A multiple linear regression analysis was conducted to determine the extent to which a five-variable model (selected from a set of 86 writing features) was effective to predict essay scores. Results: The regression model in this study accounted for 57% of the essay score variability. The correlation (Pearson), the percentage of perfect matches, the percentage of adjacent matches (±2), and the quadratic weighted kappa between the resolved scores and predicted essay scores were 0.76, 10%, 49%, and 0.73, respectively. The results were measured on an integer scale of resolved essay scores between 10-60. Discussion: When measuring the accuracy of an AES system, it is important to take into account several metrics to better understand how predicted essay scores are distributed along the distribution of human scores. Using average ranking over correlation, exact/adjacent agreement, quadratic weighted kappa, and distributional characteristics such as standard deviation and mean, this study’s regression model ranks 4th out of 10 AES systems. Despite its relatively good rank, the predictions of the proposed AES system remain imprecise and do not even look optimal to identify poor-quality essays (binary condition) smaller than or equal to a 65% threshold (71% precision and 92% recall). Conclusions: This study sheds light on the implementation process and the evaluation of a new simple AES system comparable to the state of the art and reveals that the generally obscure state-of-the-art AES system is most likely concerned only with shallow assessment of text production features. Consequently, the authors advocate greater transparency in the development and publication of AES systems. In addition, the relationship between the explanation of essay score variability and the inter-rater agreement level should be further investigated to better represent the changes in terms of level of agreement when a new variable is added to a regression model. This study should also be replicated at a larger scale in several different writing settings for more robust results.

Aim: This research note focuses on some of the consequences of big data as an emerging methodology. Its purpose is to provide a brief literature review of the method’s development and some of the critical questions researchers should consider as they move forward. Salvo (2012) contends that big data as a form of design of communication itself “is necessarily a rhetorically-based field” (p. 38). With big data as an up and coming methodology (McNely, 2012; Salvo, 2012), using caution in its application is a necessity for scholars. Not only should researchers seek out the unseen and untapped applications of big data, but they should learn its limitations as well (Spinuzzi, 2009). You adopt a methodology, you adopt its flaws. Problem Formation: This section identifies a gap in the field as it relates to some of the consequences of applying big data as a methodology and seeing it as a rhetorical tool. As big data gains steam in the field of humanities, some are sure to question what they see as a flaw: the act of quantifying language. This argument is not new nor is its rebuttal. Harris (1954) discusses the distributional structure of language with each part of a sentence acting as co-occurents, each in a particular position, and each with a relationship to the other co-occurents (p. 146). Salvo (2012) argues that the combination of these new methodologies and technologies “knits together invention, arrangement, style, memory, and delivery in ways that challenge conceptions of print based literacy and textuality” (p. 39). While big data itself has several rhetorical methodologies embedded within, deciding which one to use depends on the amount of data and how it’s aggregated. • Information Collection: As described above, this research note functions primarily as a brief review of literature. This section focuses on how writing analytics developed from content analysis in mass communications and shifted into latent semantic analysis assisted by computer technology. Riffe, Lacy, & Fico (1995) offer a clear explanation of content analysis, which was developed with comparably small data sets in mind: “Usually, but not always, content analysis involves drawing representative samples of content, training coders to use the category rules developed to measure or reflect differences in content, and measuring reliability (agreement or stability over time) of coders applying the rules” (p. 2). Finding a representative sample of content was once a more feasible methodology, but in the digital age that amount of content exponentially increases every day. Conclusions: As latent semantic analysis is an extension of quantitative content analysis (and vice versa)—and knowing that an adopted methodology carries adopted flaws—it makes sense to turn to some of the concerns voiced by mass communication scholars in order to understand limitations. While quantitative content analysis grew in popularity in mass communication, so did the refining of its methods. Reporting the reliability of a study adds credibility to the study itself, and when a human coder is involved, the reporting of this intercoder reliability becomes imperative (Hayes & Krippendorf, 2007; Krippendorf, 2008, 2011). While intercoder reliability measures the degree to which coders agree, researchers should also be keenly aware of the theory and valence informing their study, which impacts their coders, which ultimately impacts the results of the study itself. Directions for Further Research: As the field of writing studies begins to adopt big data methodologies, researchers must continue to challenge and question their applications, implementations, and implications, turning to familiar questions from our own fields. Big data is exciting and new, but it’s not the methodology to explain it all. It’s just as rhetorical as every other methodology—it’s just better at hiding it.

Background: This study focuses on construct representation and inter-reader agreement and reliability in ePortfolio assessment of 1,315 writing portfolios. These portfolios were submitted by undergraduates enrolled in required writing seminars at the University of Pennsylvania (Penn) in the fall of 2014.  Penn is an Ivy League university with a diverse student population, half of whom identify as students of color. Over half of Penn’s students are women, 12% are international, and 12% are first-generation college students. The students’ portfolios are scored by the instructor and an outside reader drawn from a writing-in-the-disciplines faculty who represent 24 disciplines. The portfolios are the product of a shared curriculum that uses formative assessment and a program-wide multiple-trait rubric. The study contributes to scholarship on the inter-reader reliability and validity of multiple-trait portfolio assessments as well as to recent discussions about reconceptualizing evidence in ePortfolio assessment.  Research Questions: Four questions guided our study: What levels of interrater agreement and reliability can be achieved when assessing complex writing performances that a) contain several different documents to be assessed; b) use a construct-based, multi-trait rubric; c) are designed for formative assessment rather than testing; and d) are rated by a multidisciplinary writing faculty?   What can be learned from assessing agreement and reliability of individual traits? How might these measurements contribute to curriculum design, teacher development, and student learning? How might these findings contribute to research on fairness, reliability, and validity; rubrics; and multidisciplinary writing assessment? Literature Review: There is a long history of empirical work exploring the reliability of scoring highly controlled timed writings, particularly by test measurement specialists. However, until quite recently, there have been few instances of applying empirical assessment techniques to writing portfolios.  Developed by writing theorists, writing portfolios contain multiple documents and genres and are produced and assessed under conditions significantly different from those of timed essay measurement. Interrater reliability can be affected by the different approaches to reading texts depending on the background, training, and goals of the rater. While a few writing theorists question the use of rubrics, most quantitatively based scholarship points to their effectiveness for portfolio assessment and calls into question the meaningfulness of single score holistic grading, whether impressionistic or rubric-based. Increasing attention is being paid to multi-trait rubrics, including, in the field of writing portfolio assessment, the use of robust writing constructs based on psychometrics alongside the more conventional cognitive traits assessed in writing studies, and rubrics that can identify areas of opportunity as well as unfairness in relation to the background of the student or the assessor. Scholars in the emergent field of empirical portfolio assessment in writing advocate the use of reliability as a means to identify fairness and validity and to create great opportunities for portfolios to advance student learning and professional development of faculty.  They also note that while the writing assessment community has paid attention to the work of test measurement practitioners, the reverse has not been the case, and that conversations and collaborations between the two communities are long overdue. Methodology: We used two methods of calculating interrater agreement: absolute and adjacent percentages, and Cohen’s Unweighted Kappa, which calculates the extent to which interrater agreement is an effect of chance or expected outcome. For interrater reliability, we used the Pearson product-moment correlation coefficient. We used SPSS to produce all of the calculations in this study.  Results: Interrater agreement and reliability rates of portfolio scores landed in the medium range of statistical significance.  Combined absolute and adjacent percentages of interrater reliability were above the 90% range recommended; however, absolute agreement was below the 70% ideal.  Furthermore, Cohen’s Unweighted Kappa rates were statistically significant but very low, which may be due to “kappa paradox.” Discussion: The study suggests that a formative, rubric-based approach to ePortfolio assessment that uses disciplinarily diverse raters can achieve medium-level rates of interrater agreement and reliability. It raises the question of the extent to which absolute agreement is a desirable or even relevant goal for authentic feedback processes of a complex set of documents, and in which the aim is to advance student learning. At the same time, our findings point to how agreement and reliability measures can significantly contribute to our assessment process, teacher training, and curriculum. Finally, the study highlights potential concerns about construct validity and rater training.  Conclusion: This study contributes to the emergent field of empirical writing portfolio assessment that calls into question the prevailing standard of reliability built upon timed essay measurement rather than the measurement, conditions, and objectives of complex writing performances.  It also contributes to recent research on multi-trait and discipline-based portfolio assessment.  We point to several directions for further research:  conducting “talk aloud” and recorded sessions with raters to obtain qualitative data on areas of disagreement; expanding the number of constructs assessed; increasing the range and granularity of the numeric scoring scale; and investigating traits that are receiving low interrater reliability scores. We also ask whether absolute agreement might be more useful for writing portfolio assessment than reliability and point to the potential “kappa paradox,” borrowed from the field of medicine, which examines interrater reliability in assessment of rare cases. Kappa paradox might be useful in assessing types of portfolios that are less frequently encountered by faculty readers. These, combined with the identification of jagged profiles and student demographics, hold considerable potential for rethinking how to work with and assess students from a range of backgrounds, preparation, and abilities.  Finally, our findings contribute to a growing effort to understand the role of rater background, particularly disciplinarity, in shaping writing assessment. The goals of our assessment process are to ensure that we are measuring what we intend to measure, specifically those things that students have an equal chance at achieving and that advance student learning.  Our findings suggest that interrater agreement and reliability measures, if thoughtfully approached, will contribute significantly to each of these goals.

Background: While it is commonly recognized that almost every work and research discipline utilize their own taxonomy, the language used within a specific discipline may also vary depending on numerous factors, including the desired effect of the information being communicated and the intended audience. Different audiences are reached through publication of information, including research results, in different types of publication outlets such as newspapers, newsletters, magazines, websites, and journals. Prior research has shown that students, both undergraduate and graduate, as well as faculty may have a difficult time locating information in different publication outlet types (e.g., magazines, newspapers, journals). The type of publication may affect the ease of understanding and also the confidence placed in the acquired information. A text analytics tool for classifying the source of research as a newsletter (used as a substitute for newspaper articles), a magazine, or an academic journal article has been developed to assist students, faculty, and researchers in identifying the likely source type of information and classifying their own writings with respect to these possible publication outlet types.  Literature Review: Literature on information literacy is discussed as this forms the motivation for the reported research. Additionally, prior research on using text mining and text analytics is examined to better understand the methodology employed, including a review of the original Scale of Theoretical and Applied Research system, adapted for the current research. Research Questions: The primary research question is: Can a text mining and text analytics approach accurately determine the most probable publication source type with respect to being from a newsletter, magazine, or journal? Methodology: A text mining and text analytics algorithm, STAR’ (System for Text Analytics-based Ranking), was developed from a previously researched text mining tool, STAR (Scale of Theoretical and Applied Research), that was used to classify the research type of articles between theoretical and applied research. The new text mining method, STAR’, analyzes the language used in manuscripts to determine the type of publication. This method first mines all words from corresponding publication source types to determine a keyword corpus. The corpus is then used in a text analytics process to classify full newsletters, magazine articles, and journal articles with respect to their publication source. All newsletters, magazine articles, and journal articles are from the library and information sciences (LIS) domain. Results: The STAR’ text analytics method was evaluated as a proof of concept on a specific LIS organizational newsletter, as well as articles from a single LIS magazine and a single LIS journal. STAR’ was able to classify the newsletters, magazine articles, and journal articles with 100% accuracy. Random samples from another similar LIS newsletter and a different LIS journal were also evaluated to examine the robustness of the STAR’ method in the initial proof of concept. Following the positive results of the proof of concept, additional journal, magazine, and newsletter articles were used to evaluate the generalizability of STAR’. The second-round results were very positive for differentiating journals and newsletters from other publication types, but revealed potential issues for distinguishing magazine articles from other types of publications. Discussion: STAR’ demonstrates that the language used for transferring information within a specific discipline does differ significantly depending on the intended recipients of the research knowledge. Further work is needed to examine language usage specific to magazine articles. Conclusions: The STAR’ method may be used by students and faculty to identify the likely source of research or discipline-specific information. This may improve trust in the reliability of information due to different levels of rigor applied to different types of publications. Additionally, the STAR’ classifications may be used by students, faculty, or researchers to determine the most appropriate type of outlet and correspondingly the most appropriate type of audience for the reported information in their own manuscripts, thereby improving the chance for successful sharing of information to appropriate audiences who will deem the information to be reliable, through publication in the most relevant outlet type.

Background: Attention Deficit Hyperactivity Disorder (ADHD) is a mental health disorder. People diagnosed with ADHD are often inattentive (have difficulty focusing on a task for a considerable period), overly impulsive (make rash decisions), and are hyperactive (move excessively, often at inappropriate times). ADHD is often diagnosed through psychiatric assessments with additional input from physical/neurological evaluations. Written Language Disorder (WLD) is a learning disorder. People diagnosed with WLD often make multiple spelling, grammar, and punctuation mistakes, have sentences that lack cohesion and topic flow, and have trouble completing written assignments. Typically, WLD is also diagnosed through psychological educational assessments with additional input from physical/neurological evaluation. Literature Review: Previous research has shown a link between ADHD and writing difficulties. Students with ADHD have an increased likelihood of having writing difficulties, and rarely is there a presence of writing difficulties without ADHD or another mental health disorder. However, the presence of writing difficulties does not necessarily indicate the presence of a WLD. There are other physical and behavioral factors of ADHD that can contribute to a student having a WLD as well. Therefore, a statistical association between these factors (in conjunction with written performance) and WLD must first be established. Research Question: To determine the statistical association between WLD and physical and behavioral aspects of ADHD that indicate writing difficulties, this research reviewed methodologies from the literature pertaining to contemporary diagnoses of writing difficulties in ADHD students, and reveal diagnostic methods that explicitly associate the presence of WLD with these writing difficulties among students with ADHD. The results demonstrate the association between writing difficulties and WLD as it pertains to ADHD students using an integrated computational model employed on data from a systematic review. These results will be validated in a future study that will employ the integrated computational model to measure WLD among students with ADHD. Methodology: To measure the association of WLD among students with ADHD, the authors created a novel computational model that integrates the outcomes of common screening methods for WLD (physical questionnaire, behavioral questionnaire, and written performance tasks) with common screening methods for ADHD (physical questionnaire, behavioral questionnaire, adult self-reporting scales, and reaction-based continuous performance tasks (CPTs)). The outcomes of these screening methods were fed into an artificial neural network (ANN ) first, to ‘artificially learn’ about measuring the prevalence of WLD among ADHD students and second, to adjust the prevalence value based on information from different screening methods. This can be considered as the priming of the ANN. The ANN model was then tested with data from previous studies about ADHD students who had writing difficulties. The ANN model was also tested with data from students without ADHD or WLD, to serve as control. Results: The results show that physical, behavioral, and written performance attributes of ADHD students have a high correlation with WLD (r = 0.72 to 0.80) in comparison to control students (r = 0.30 to 0.20), substantiating the link between WLD and ADHD. It should be noted that due to lack of female participation, most studies in the literature only employed and reported on the relationship between WLD and ADHD for male participants. Discussion and Conclusion: By testing ADHD students and control students against the WLD criteria, the study shows a strong correlation between WLD and ADHD. There are limitations to the results’ accuracy in terms of a) sample size (average n=88, mean age = 19, 8 studies used for a meta-analysis), b) analysis (original study reviewing ADHD factors first, WLD factors second), and c) causation (the study only reviews prevalence of WLD in ADHD students, not causation). A clinical trial will validate the data and address some of these limitations in a future phase of the research. A computational causal model will be introduced in the discussion portion to illustrate how causation between writing metrics and WLD as it pertains to ADHD can be achieved. These results open the door to advancing pedagogical techniques in education, where students afflicted with ADHD and/or WLD could not only receive assistance for the behavioral aspects of their disorder, but also expect assistance for the learning aspects of their disorder, empowering them to succeed in their studies.

Chapter 1 be especially important to undergraduate science students, whose confidence in their own abilities as writers may have been damaged by experiences with writing in the classroom during their schooling (Choi et al., 2010;Shanahan, 2004).Several of the scientists and mathematicians in this study discuss damaging experiences with school and English teachers in particular.The anxious mathematics student, sitting in a writing class, who reads this comment by a successful applied mathematician, What's interesting is I did mathematics, I think, because I found English so difficult . . .I failed . . . on English and I was fine on mathematics.I was top in maths but I was desperate in English.I can remember the essay.The title was "Your House."Now as a mathematician . . .I've got to write about my house.What is my house?And I went to numbers straight away.It's got five windows, it's got one door-this is age 10 or 11.I knew it was a disaster when I wrote it.But I was incapable of doing anything better-Timothy, Chapter 3. may recognise a similar incident of their own, and may never have realised that the successful science or mathematics professor in their writing classroom may have experienced this kind of setback.Reading of

Chapter 1 be especially important to undergraduate science students, whose confidence in their own abilities as writers may have been damaged by experiences with writing in the classroom during their schooling (Choi et al., 2010;Shanahan, 2004).Several of the scientists and mathematicians in this study discuss damaging experiences with school and English teachers in particular.The anxious mathematics student, sitting in a writing class, who reads this comment by a successful applied mathematician, What's interesting is I did mathematics, I think, because I found English so difficult . . .I failed . . . on English and I was fine on mathematics.I was top in maths but I was desperate in English.I can remember the essay.The title was "Your House."Now as a mathematician . . .I've got to write about my house.What is my house?And I went to numbers straight away.It's got five windows, it's got one door-this is age 10 or 11.I knew it was a disaster when I wrote it.But I was incapable of doing anything better-Timothy, Chapter 3. may recognise a similar incident of their own, and may never have realised that the successful science or mathematics professor in their writing classroom may have experienced this kind of setback.Reading of

Chapter 1 be especially important to undergraduate science students, whose confidence in their own abilities as writers may have been damaged by experiences with writing in the classroom during their schooling (Choi et al., 2010;Shanahan, 2004).Several of the scientists and mathematicians in this study discuss damaging experiences with school and English teachers in particular.The anxious mathematics student, sitting in a writing class, who reads this comment by a successful applied mathematician, What's interesting is I did mathematics, I think, because I found English so difficult . . .I failed . . . on English and I was fine on mathematics.I was top in maths but I was desperate in English.I can remember the essay.The title was "Your House."Now as a mathematician . . .I've got to write about my house.What is my house?And I went to numbers straight away.It's got five windows, it's got one door-this is age 10 or 11.I knew it was a disaster when I wrote it.But I was incapable of doing anything better-Timothy, Chapter 3. may recognise a similar incident of their own, and may never have realised that the successful science or mathematics professor in their writing classroom may have experienced this kind of setback.Reading of

Chapter 1 be especially important to undergraduate science students, whose confidence in their own abilities as writers may have been damaged by experiences with writing in the classroom during their schooling (Choi et al., 2010;Shanahan, 2004).Several of the scientists and mathematicians in this study discuss damaging experiences with school and English teachers in particular.The anxious mathematics student, sitting in a writing class, who reads this comment by a successful applied mathematician, What's interesting is I did mathematics, I think, because I found English so difficult . . .I failed . . . on English and I was fine on mathematics.I was top in maths but I was desperate in English.I can remember the essay.The title was "Your House."Now as a mathematician . . .I've got to write about my house.What is my house?And I went to numbers straight away.It's got five windows, it's got one door-this is age 10 or 11.I knew it was a disaster when I wrote it.But I was incapable of doing anything better-Timothy, Chapter 3. may recognise a similar incident of their own, and may never have realised that the successful science or mathematics professor in their writing classroom may have experienced this kind of setback.Reading of

Chapter 1 be especially important to undergraduate science students, whose confidence in their own abilities as writers may have been damaged by experiences with writing in the classroom during their schooling (Choi et al., 2010;Shanahan, 2004).Several of the scientists and mathematicians in this study discuss damaging experiences with school and English teachers in particular.The anxious mathematics student, sitting in a writing class, who reads this comment by a successful applied mathematician, What's interesting is I did mathematics, I think, because I found English so difficult . . .I failed . . . on English and I was fine on mathematics.I was top in maths but I was desperate in English.I can remember the essay.The title was "Your House."Now as a mathematician . . .I've got to write about my house.What is my house?And I went to numbers straight away.It's got five windows, it's got one door-this is age 10 or 11.I knew it was a disaster when I wrote it.But I was incapable of doing anything better-Timothy, Chapter 3. may recognise a similar incident of their own, and may never have realised that the successful science or mathematics professor in their writing classroom may have experienced this kind of setback.Reading of

The books reviewed here share the theme of women “making it†in the world of rhetoric and composition academe. The reviewers first critically summarize each of the three collections; then narratively synthesize their personal experiences with four prominent themes across these collections: knowing, balance, mentoring, and change. This four-part woven analysis, shows and tells tales from women about what has been lurking in the academy’s closet and what still needs to change.

Abstract After a decade of working in writing centers as a tutor and administrator, I have experienced and witnessed many challenging consultations. A particularly vexing type of consultation occurs when tutors work with advanced students writing in unfamiliar disciplines and genres. In this article, I consider whether the reading method employed during such consultations supports or detracts from tutors’ efforts to offer helpful advice. Specifically, I ask: When and how should writing tutors read students’ drafts to best support and engage them? How do the specific needs of student writers factor into selecting the best reading method? To respond to these questions, I first describe the results of a review of 70 well-known universities’ writing center websites, which reveals that the majority of centers require tutors to read students’ writing for the first time during consultations. Next, I posit some limitations of during-consultation reading models and argue that the read-ahead model may better meet the needs of some student-writer populations. To provide a framework for the read-ahead model, I illustrate strategies that may be implemented to prepare tutors for consultations, drawing on research-based techniques that a more-senior director and I used at a private doctoral-granting university as we established the first writing center on the campus. I conclude by suggesting that directors consider the read-ahead method as yet another tool in their vast arsenal of pedagogical techniques, particularly when tutors must work with advanced writers from unfamiliar disciplines.

Being an African American woman for almost 40 years, a secondary education teacher for three years, and a three-time college student, I am well versed in the micro aggressions that plague students in education, which is why I feel it's important to always be aware of new information meant to combat the systems of oppression found in learning environments. Through my research, I realize what is needed is a way to help individuals see and acknowledge discriminatory practices in the educational field, especially when it comes to writing and the writing process. Culture, nationality, beliefs, biases, and stereotypes are not like layers of clothing that one can check at the door and pick up later. We have all been exposed to the unfair dynamics that form the race relations in society, and we carry those understandings with us everywhere we go, even if we are not completely aware of them. However, awakening this awareness is prevalent to promote a beneficial learning environment for students both in the classroom and in the writing center.

Working in writing centers is a great gig. We get to lead units committed to making collaborative learning happen in a host of ways: students gaining access to or refining disciplinary literacies, faculty and administration discovering more effective ways for writing to demonstrate learning and transfer, and tutors becoming conscious of their voices as mentors of communities of practice, both disciplinary and sociocultural. Many of us "graduate" from being students who have been tutored in writing centers to serving as writing tutors ourselves; some of us inspired by all of that labor decide to pursue graduate education in and become directors of these amazing units, charged with sustaining and growing these amazing units and all those who teach and learn within While our field has plenty of resources for educating tutors, for coaching faculty across the disciplines on using writing for teaching

Since the 2016 release of the Modern Language Association’s new style guidelines, scholars and teachers—along with writing centers, libraries, and editorial staffs--have been familiarizing themselves with the changes. Based on a standardized approach to citation, the eighth edition of the MLA Handbook asks us to adjust some long-entrenched habits. Perhaps more pressingly, the new MLA format reminds us of enduring pedagogical challenges regarding students’ information literacy, habits of source citation, and understanding of knowledge-making. With this issue of Composition Forum marking the journal’s progression to the new guidelines, we asked two scholars to explore the MLA Handbook ’s significance for our field’s scholarly and teacherly work.

Research problem: Although labor statistics document a steady rise in contract, contingent, and entrepreneurial labor, knowledge about the professional communication practices that build and sustain independent careers in the field of technical communication (TC) largely emerges from broad survey analysis, cultural/social critiques, or individual anecdotes. From these statistics and stories, we already know that independent technical communicators face challenges ranging from legal issues to establishing marketing visibility when they start and maintain businesses. Drawing on thick qualitative description from semistructured interviews, this article responds to the need for more systematic research tracing the networking practices, technologies, and relationships that enable entrepreneurial work. Research question: How do established individual entrepreneurs in TC describe the social relationships, networking practices, and networking technologies that shape their careers over time? Literature review: This project extends prior research at the intersections of entrepreneurship, technical communication, and social networks. Entrepreneurial studies research indicates that strong social ties and embeddedness influence venture performance; however, systematic scholarship on the networks or networking practices of independent or entrepreneurial technical communication practice has been limited. Methodology: The project used semistructured interviews to analyze the professional communication practices of eight technical communicators with considerable experience working independently as consultants or small-business owners. We used an online search to identify experienced entrepreneurs in the interdisciplinary field of technical communication. After recruiting participants via email, we conducted semistructured interviews to gather employment narratives, while prompting participants to share information about career-relevant ties, networking practices, and networking technologies. We then analyzed data through two iterative qualitative coding passes. Results and conclusions: Our participants, made up of experienced TC entrepreneurs, have used networking over at least two decades to advance personal business outcomes and evolve technical communication as a field and profession. Findings detail how networking is central to professional social knowledge construction, as TC entrepreneurs establish transactional contact with others, practice learning, and enact exponential reputation-building that addresses the isolation of working outside traditional organizations. Since this is a qualitative study based on self-report, the results are not generalizable but provide a foundation for future larger-scale research building from these qualitative themes.

Research problem: Entrepreneurial passion has been shown to play an important role in venture success and, therefore, in investors' funding decisions. However, it is unknown whether the passion entrepreneurs personally feel or experience can be accurately assessed by investors during a venture pitch. Research questions: (1) To what extent does entrepreneurs' personal passion align with investors' perceived passion? (2) To what cues do investors attend when assessing entrepreneurs' passion? Literature review: Integrating theory and research in entrepreneurship communication and entrepreneurial passion within the context of venture pitching, we explain that during venture pitches, investors make judgments about entrepreneurs' passion that have consequences for their investment decisions. However, they can attend to only those cues that entrepreneurs outwardly display. As a result, they may not be assessing the passion entrepreneurs personally feel or experience. Methodology: We used a sequential explanatory mixed methods research design. For our data collection, we surveyed 40 student entrepreneurs, videorecorded their venture pitches, and facilitated focus groups with 16 investors who viewed the videos and ranked, rated, and discussed their perceptions of entrepreneurs' passion. We conducted statistical analyses to assess the extent to which entrepreneurs' personal passion and investors' perceived passion aligned. We then performed an inductive analysis of critical cases to identify specific cues that investors attributed to passion or lack thereof. Results and conclusions: We revealed a large misalignment between entrepreneurs' personal passion and investors' perceived passion. Our critical case analysis demonstrated that entrepreneurs' weak or strong presentation skills led investors either to underestimate or overestimate, respectively, perceptions of entrepreneurs' passion. We suggest that entrepreneurs should develop specific presentation skills and rhetorical strategies for displaying their passion; at the same time, investors should be wary of attending too closely to presentation skills when assessing passion.

Research problem: Studies how one entrepreneur acquired, applied, and fit frames to her startup venture and stakeholders over one year. Research questions: How do pitchers acquire frames for pitches? How do pitchers apply frames to existing pitches? How do pitchers gauge the fit between the innovation, frames, and stakeholders? Literature review: The literature examined-framing professional communication, developing pitches, and framing pitches-stresses the relationship between framing, agency, and deliberation. However, few studies approach data from the perspective of the pitcher and few frames outside of the problem-solution frame are considered. Methodology: This autoethnography analyzes data from more than 500 pages of field notes, 60 minutes of video-recorded pitch sessions, 25 interviews with pitch stakeholders, and various textual artifacts that pertained to Author 1's nonprofit startup organization, Hacker Gals. Themes in the data were identified and analyzed through the composition of analytic memos. Frames were identified and analyzed through close reading and holistic interpretation. Results and conclusions: The entrepreneur acquired the most influential frames through stakeholder discussion, applied these frames in a way that stacked and made salient multiple frames beyond the problem-solution frame, and judged frame fit by considering the degree to which catchers took up the frames. The study's results suggest that the practice of frame stacking might increase pitch effectiveness by mitigating troubled identifications.

Research problem: This study investigates entrepreneurship as a rhetorical practice and seeks to illustrate how narratives of individuals from different cultures create a discourse of entrepreneurship. We offer theoretical and methodological considerations for comparative international analyses in entrepreneurship research. Research questions: (1) How do the stories that are told by entrepreneurs from different cultures reveal their values? (2) What can those stories tell us about entrepreneurship in different cultures? Literature review: An emerging stream of authors proposes to study entrepreneurship from individual narratives, but studies on entrepreneurship rhetorics are scarce, seldom use an international approach, and rarely cover the cultural aspects. Methodology: We collected entrepreneurial narratives in the US, Spain, and China, and deployed a novel two-fold method to retain cultural nuances and validate translation accuracy. Narrative data were studied based upon the coding, constant comparison, and memo writing used in grounded theory. Results and conclusions: We identify three core metaphorical devices used by participants to structure their entrepreneurial journeys (action and learning, autonomy and money, and exceptionalism and networks), and we suggest that the use of these metaphorical pairs varies both within and across cultures. These findings offer preliminary evidence, for the first time in the literature, that building a rhetorical understanding of entrepreneurship requires that we consider two axes: the individual and the cultural.

Applied Pedagogies: Strategies for Online Writing Instruction, edited by Daniel Ruefman and Abigail G. Scheg. Boulder: UP of Colorado for Utah State UP, 2016. Print. Foundational Practices of Online Writing Instruction, edited by Beth L. Hewett and Kevin Eric DePew. Fort Collins: WAC Clearinghouse and Parlor Press, 2015. Print. A Position Statement of Principles and Example Effective Practices for Online Writing Instruction (OWI) by the CCCC Committee on Best Practices for Online Writing Instruction. Conference on College Composition and Communication. Mar. 2013. Web.