Despite the growing interest in the dynamics of the writing process in writing research, publicly available large-scale corpora of keystroke logs have been rare. We introduce KLiCKe, a freely available collection of keystroke logs for around 5,000 argumentative texts written by adults in the United States. The KLiCKe corpus also includes human-rated holistic scores for the essays as well as writers' demographic details, their typing skills, and vocabulary knowledge. We describe our methods for constructing the corpus and present descriptives for different components of the corpus. To illustrate the use of the KLiCKe corpus, we report a study using a subset of the corpus to investigate whether keystroke features are associated with holistic writing quality for L1 and L2 writers. The study shows that higher writing scores are related to shorter pauses in general, shorter between-word pauses, lower proportion of deletions, higher proportion of insertions, and less process variance. The KLiCKe corpus provides a robust resource for researchers to study the dynamics of text production and revision that will help spur the development of process-oriented tools and methodologies in writing assessment and instruction.

This study examines associations between writing behaviors manifested by keystroke analytics and the formulation of argument elements in L2 undergraduate writers' writing processes. Ninety-nine persuasive essays written by L2 undergraduate writers were human annotated for Toulmin argument elements. The corresponding keystroke logs were segmented and analyzed to characterize the dynamics of writing processes for different categories of the elements. A multinomial mixed-effects logistic regression model was built to predict argument categories using the keystroke analytics. The study reported that L2 undergraduate writers' text production for final claims and primary claims featured P-bursts (execution processes delimited by pauses exceeding 2 seconds) of longer spans but lower production fluency compared to that for data. In addition, fewer revisions were observed when L2 writers were constructing final claims than when they were formulating data. These findings shed light on the varying cognitive loads and activities L2 undergraduate writers may experience when building different argument elements in written argumentation.

This paper introduces the Persuasive Essays for Rating, Selecting, and Understanding Argumentative and Discourse Elements (PERSUADE) corpus.The PERSUADE corpus is large-scale corpus of writing with annotated discourse elements. The goal of the corpus is to spur the development of new, open-source scoring algorithms that identify discourse elements in argumentative writing to open new avenues for the development of automatic writing evaluation systems that focus more specifically on the semantic and organizational elements of student writing.

This study examines links between human ratings of writing quality and the incidence of argumentative features (e.g., claims, data) in persuasive essays along with relationships among these features and their distance from one another within an essay. The goal is to better understand how argumentation elements in persuasive essays combine to model human ratings of essay quality. The study finds that, in most cases, it is not the presence of argumentation features that is predictive of writing quality but rather the relationships between superordinate and subordinate features, parallel features, and the distances between features. This finding has not only theoretical value but also practical value in terms of pedagogical approaches and automated writing feedback.