Icon for: A Daniel Johnson


Wake Forest University

Accelerating Student Scientific Writing Mastery Using Electronic Support and ...

NSF Awards: 1712423

2019 (see original presentation & discussion)

Undergraduate, Graduate

How can we provide students with more opportunities to practice meaningful scientific writing? How do we move beyond copy editing, and provide students with tailored, meaningful feedback that builds deep transferable communication skills? Are these goals even possible in classes with dozens or hundreds of enrolled students? Yes, we can, and yes, it is possible. Our process for teaching scientific writing brings together student annotation exercises, automated analysis of draft texts, and holistic grading and feedback with text analytics methods from data science. Our approach is designed so multiple instructors can implement them simultaneously, simplifying scale-up to large courses. The exercises and text analytics provide us with two important kinds of data. First we get benchmark data and actionable formative assessments of students' development as writers. Second, we get data that lets us monitor instructor performance, compare performance of instructors (either individually or as a cohort) to program guidelines, and make adjustments to instructor training in real time.

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