Actionable Data for Teaching and Learning Writing
The production of and access to large amounts of data is the most significant recent change in writing research. This makes new questions, techniques of inquiry and quests for actionable data both possible and necessary.
Theorists and researchers from Writing Studies, Corpus and Computational Linguistics, Intercultural Rhetoric, and Pedagogy will explore the emergence of writing analytics and data mining as a primary concern for academe and as a method to develop teaching and learning practices.
Featured speakers will report on new educational data and text mining methods, advances in intelligent tutorial systems and artificial intelligence, pioneering research on machine feedback for formative as opposed to summative assessment, and research on ways to provide effective feedback on student work.