Journal ArticleDOI
What Is Successful Writing? An Investigation into the Multiple Ways Writers Can Write Successful Essays.
TLDR
This article identified multiple profiles of successful essays via a cluster analysis approach using linguistic features reported by a variety of natural language processing tools, and provided empirical evidence that successful writing cannot be defined simply through a single set of predefined features, but rather, successful writing has multiple profiles.Abstract:
This study identifies multiple profiles of successful essays via a cluster analysis approach using linguistic features reported by a variety of natural language processing tools. The findings from the study indicate that there are four profiles of successful writers for the samples analyzed. These four profiles are linguistically distinct from one another and demonstrate that expert human raters examine a number of different linguistic features in a variety of combinations when assessing writing proficiency and assigning high scores to independent essays (regardless of the scoring rubric considered). The writing styles in the four clusters can be described as action and depiction style, academic style, accessible style, and lexical style. The study provides empirical evidence that successful writing cannot be defined simply through a single set of predefined features, but that, rather, successful writing has multiple profiles. While these profiles may overlap, each profile is distinct.read more
Citations
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Journal ArticleDOI
Syntactic complexity in L2 writing: Progress and expansion
TL;DR: This commentary to the Special Issue identifies four themes that arise from the contributions that each study makes to the study of syntactic complexity in L2 writing and several other themes that stem from the collective findings from the five studies and which connect with the general landscape of the research domain.
Natural Language Processing in an Intelligent Writing Strategy Tutoring System.
TL;DR: The present study extends prior work by including a larger data sample and an expanded set of indices to assess new lexical, syntactic, cohesion, rhetorical, and reading ease indices and finds that the new indices increased accuracy but, more importantly, afford the means to provide more meaningful feedback in the context of a writing tutoring system.
Journal ArticleDOI
Linguistic features in writing quality and development: An overview
TL;DR: The authors provide an overview of how analyses of linguistic features in writing samples provide a greater understanding of predictions of both text quality and writer development and links between language features within texts, focusing on three main linguistic construct (lexical sophistication, syntactic complexity, and text cohesion).
Proceedings ArticleDOI
Understand students' self-reflections through learning analytics
Vitomir Kovanović,Srećko Joksimović,Negin Mirriahi,Ellen Blaine,Dragan Gašević,George Siemens,Shane Dawson +6 more
TL;DR: A random-forest classification system using linguistic indicators provided by the LIWC and Coh-Metrix tools is developed, which examines what particular indicators are representative of the different types of student reflective writings.
Journal ArticleDOI
Argumentative writing: theory, assessment, and instruction
Ralph P. Ferretti,Steve Graham +1 more
TL;DR: Despite the early emergence of oral argumentation, written argumentation is slow to develop, insensitive to alternative perspectives, and generally of poor quality as mentioned in this paper, which is unsettling because high quality argumentative writing is expected throughout the curriculum and needed in an increasingly competitive workplace that requires advanced communication skills.
References
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Book
Variation across Speech and Writing
TL;DR: The model applied in this study addressed textual dimensions and relations in speech and writing, as well as situations and functions, and its application to linguistic research on speech andWriting.
ReportDOI
Derivation of New Readability Formulas (Automated Readability Index, Fog Count and Flesch Reading Ease Formula) for Navy Enlisted Personnel
TL;DR: In this paper, three readability formulas were recalculated to be more suitable for Navy use: Automated Readability Index (ARI), Fog Count, and Flesch Reading Ease Formula.
BookDOI
The Cambridge handbook of expertise and expert performance
TL;DR: In this article, K. Anders Ericsson and K.H. Chi introduce the Cambridge handbook of expertise and expert performance, its development, organization, and content, and two approaches to the study of experts' characteristics.
Journal ArticleDOI
Are Good Texts Always Better? Interactions of Text Coherence, Background Knowledge, and Levels of Understanding in Learning From Text
TL;DR: This paper investigated the role of text coherence in the comprehension of science texts and found that readers who know little about the domain of the text benefit from a coherent text, whereas high-knowledge readers benefit from minimally coherent text.