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• 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). • Literature Review: Hardy and Romer (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. • Research Questions: The research questions that guide this study are as follows: 1. 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? • 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). • 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. • 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. • 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).

We used free association tasks to investigate second language (L2) verb-argument constructions (VACs) and the ways in which their access is sensitive to statistical patterns of usage (verb type-token frequency distribution, VAC-verb contingency, verb-VAC semantic prototypicality). 131 German, 131 Spanish, and 131 Czech advanced L2 learners of English generated the first word that came to mind to fill the V slot in 40 sparse VAC frames such as ‘he __ across the …’, ‘it __ of the …’, etc. For each VAC, we compared these results with corpus analyses of verb selection preferences in 100 million words of usage and with the semantic network structure of the verbs in these VACs. For all language groups, multiple regression analyses predicting the frequencies of verb types generated for each VAC show independent contributions of (i) verb frequency in the VAC, (ii) VAC-verb contingency, and (iii) verb prototypicality in terms of centrality within the VAC semantic network. L2 VAC processing involves rich associations, tuned by verb type and token frequencies and their contingencies of usage, which interface syntax, lexis, and semantics.

This paper combines data from learner corpora and psycholinguistic experiments in an attempt to find out what advanced learners of English (first language backgrounds German and Spanish) know about a range of common verbargument constructions (VACs), such as the ‘V about n’ construction (e.g. she thinks about chocolate a lot). Learners’ dominant verb-VAC associations are examined based on evidence retrieved from the German and Spanish subcomponents of ICLE and LINDSEI and collected in lexical production tasks in which participants complete VAC frames (e.g. ‘he ___ about the...’) with verbs that may fill the blank (e.g. talked, thought, wondered). The paper compares findings from the different data sets and highlights the value of linking corpus and experimental evidence in studying linguistic phenomena

Formulaic sequences are recognised as having important roles in language acquisition, processing, fluency, idiomaticity, and instruction. But there is little agreement over their definition and measurement, or on methods of corpus comparison. We argue that replicable research must be grounded upon operational definitions in statistical terms. We adopt an experimental design and apply four different corpus-analytic measures, variously based upon n-gram frequency (Frequency-grams), association (MI-grams), phrase-frames (P-frames), and native norm (items in the Academic Formulas List – AFL-grams), to samples of first and second language writing in order to examine and compare knowledge of formulas in first and second language acquisition as a function of proficiency and language background. We find that these different operationalizations produce different patterns of effect of expertise and L1/L2 status. We consider the implications for corpus design and methods of analysis.

This paper continues the detailed account of the central steps involved in compiling and distributing the Michigan Corpus of Upper-level Student Papers (MICUSP). In this paper, we discuss the annotation process used to encode MICUSP files in TEI-compliant XML, and the development of MICUSP Simple, the online application through which the corpus is now freely available online. We also describe how MICUSP Simple can be used to carry out simple word/phrase searches and to browse papers within different categories.

In this paper, we provide a detailed account of the steps that were central to designing and compiling the Michigan Corpus of Upper-level Student Papers (MICUSP). MICUSP is a new collection of 829 papers (around 2.6 million words) written by University of Michigan students in their final undergraduate year or in their first three years of graduate education. The papers come from sixteen disciplines, ranging from Humanities and Arts to Physical Sciences, and represent a range of different text types. In this paper, we offer an overview of the design of MICUSP, the online submission process used to collect papers, and the text-type classification of the papers.

Over the past few decades, corpora have not only revolutionized linguistic research but have also had an impact on second language learning and teaching. In the field of applied linguistics, more and more researchers and practitioners treasure what corpus linguistics has to offer to language pedagogy. Still, corpora and corpus tools have yet to be widely implemented in pedagogical contexts. The aim of this article is to provide an overview of pedagogical corpus applications and to review recent publications in the area of corpus linguistics and language teaching. It covers indirect corpus applications, such as in syllabus or materials design, as well as direct applications of corpora in the second language classroom. The article aims to illustrate how both general and specialized language corpora can be used in these applications and discusses directions for future research in applied corpus linguistics.

Evaluation is a pervasive element in spoken and written language but its identification poses serious problems to linguistic researchers, especially when they are dealing with larger amounts of text which require the application of computer-assisted analytic techniques. This article explores ways of identifying items of evaluative meaning in a three million word corpus of linguistic book reviews, a text type that is particularly rich in expressions of positive and negative evaluation. It discusses whether it is at all possible to capture evaluation in a corpus in a systematic way and which analytic strategies may be most promising in the search for a larger set of meaningful patterns. The paper ends with a discussion of some unresolved issues in the area of evaluation research and sketches tasks for future activities in the field.

Based on a large set of data from one of the biggest available corpora of spoken British English (the 10-million word spoken component of the BNC), this article explores central lexical-grammatical aspects of progressive forms with future time reference. Among the phenomena investigated are verb preferences, adverbial co-selection, subject types, and negation. It is demonstrated that future time progressives in spoken British English are patterned to a considerable extent (for example that it is individual verbs, rather than semantic groups of verbs, that preferably occur in such constructions) and that actual language use often runs counter to claims that can be found in traditional grammatical descriptions of the construction. A number of general and often neglected issues in the analysis of lexical-grammatical patterns are also addressed, in particular the notion of pattern frequency.

1. Introduction: Patterns, meaningful units and specialized discourses (by Schulze, Rainer) 2. Starting with the small words: Patterns, lexis and semantic sequences (by Hunston, Susan) 3. Emphasizers in spoken and written academic discourse: The case of really (by Diani, Giuliana) 4. The 'terroridiom' principle between spoken and written discourse (by Milizia, Denise) 5. 4-grams in comparable specialized corpora: Perspectives on phraseology, translation, and pedagogy (by Forchini, Pierfranca) 6. From phraseology to culture: Qualifying adjectives in the language of tourism (by Manca, Elena) 7. Index

1. Introduction: Zooming in (by Schulze, Rainer) 2. Part I. Setting the scene 3. Technology and phraseology: With notes on the history of corpus linguistics (by Stubbs, Michael) 4. Corpus-driven approaches to grammar: The search for common ground (by Hoey, Michael) 5. Valency - item-specificity and idiom principle (by Herbst, Thomas) 6. Fowler's Modern English Usage at the interface of lexis and grammar (by Busse, Ulrich) 7. The psycholinguistic reality of collocation and semantic prosody (1): Lexical access (by Ellis, Nick C.) 8. Part II. Considering the particulars 9. The lexicogrammar of present-day Indian English: Corpus-based perspectives on structural nativisation (by Mukherjee, Joybrato) 10. The semantic and grammatical overlap of as and that: Evidence from non-standard English (by Kolbe-Hanna, Daniela) 11. The historical development of the verb doubt and its various patterns of complementation (by Iyeiri, Yoko) 12. The grammatical properties of recurrent phrases with body-part nouns: The N1 to N1 pattern (by Lindquist, Hans) 13. A corpus-based investigation of cognate object constructions (by Hoche, Silke) 14. Revisiting the evidence for objects in English (by Meyer, Matthias L.G.) 15. Lexico-functional categories and complex collocations: The case of intensifiers (by Cacchiani, Silvia) 16. Polysemy and lexical priming: The case of drive (by Tsiamita, Fanie) 17. Local textual functions of move in newspaper story patterns (by Mahlberg, Michaela) 18. Loud signatures: Comparing evaluative discourse styles - patterns in rants and riffs (by Duguid, Alison) 19. Index