Let me set a few things straight. For one, this site embodies an interactive space in which I have visualized and annotated datasets from my computational research on student composition from SUNY Geneseo’s online writing course, The Conventions of College Writing (INTD 106). Now in its first semester as part of Geneseo’s formal curriculum, INTD 106’s core learning outcome involves reinforcing our first-year writing seminar, INTD 105, by prompting students to independently reflect on what key factors drive the motor of successful academic writing.
Also important to note here is that INTD 106 represents SUNY Geneseo’s first large-scale OER course. For those unfamiliar with the acronym, OER stands for “open educational resources”; or, educational materials residing inside of the public domain, and which are freely accessible for all instructors to retain, reuse, revise, remix and redistribute. The OER Initiative is, I believe, a key step forward for every level of education, as its aims involve not only empowering educators, but also democratizing knowledge for the students and learners of tomorrow. With an enrollment of over 500 semesterly students, INTD 106 has emerged as one of the largest and most innovative of its kind in the SUNY System, which is why I’m here today, writing to you now.
In analyzing a handful of writing assignments between Spring 2018 and Fall 2018, I took it upon myself to text-mine student prose from Spring 2018 and Fall 2018, concatenating every round of submissions into a body of text ranging from 100,000 to 150,000 words each. It wasn’t long after doing so that I realized these corpora were fertile ground for comparative discourse analysis, with numerous metadiscursive trends resulting from our diverse range of guided prompts and writing assignments. Each corpus finds students exhibiting a full spectrum of analytic thought in regard to the scale at which they conceptualize the writing process — some speak to the myriad conventions of usage and punctuation, as others juggle the academic acrobats of higher-level argumentation, with even a select few hearkening back to their perilous memories of 8th-grade grammar instruction. Ultimately, these students have so many smart insights to offer that we at Geneseo believe it is necessary to consider their self-represented concerns during our iterative redesign of INTD 106, if only to better tailor the course to the students who are yet to come. Such a goal is no cozy afternoon of work, however, at least not since these corpora surpassed half a million words of total text.
As I took to computationally analyzing their self-reflections, moreover, I hoped to understand the deep-seated patterns of their writing as well as their metacognitive views on academic discourse, which is to say, their varied perspectives on what constitutes the analytic nomenclature of college composition. Striving to achieve a more sustainable student-centered bridge to learner success, I also aim to set a precedent for those who choose to pursue projects not unlike my own in the nearby future. Entering the analytical stage of my educational design research, I have in turn chosen to share the ongoing results of my longitudinal case study with you in the form of this website.
As all open educational practices should be, this project was born and raised in dialogue and compromise — and so I urge my readers to leave comments and queries at even the slightest inkling. As there are no writers without readers, or readers without writers, my work is for naught without the contributions of others. What I’m trying to say, then, is that I thank you for reading, for writing, for contributing to this course in process. If you gain from it but a fraction of what I have, I know it will have been well worth your time.
All my best,
For those unfamiliar with programming, the title of my site uses the same print() design as Python, whose function is to export a command to its corresponding output window; too, the pound symbol (#) in the red subtitle mimics the tool allowing for one to comment on code without contraindicating the internal functions of its script. I’ve also used Python’s standard font in Baskerville, which happens to be the preferred font of the course’s indefatigable instructor, Dr. Gillian Paku, for whom I am always thankful.