Published on August 19, 2024

Currently working at Carnegie Mellon University, Ben Markey’s award-winning paper titled “Presenting and Making Relevant: A Semantic Frame Analysis of Teaching Assistant Perceptions of Writing in Statistics” brings frame semantics to the task relevant to teaching assistants. Markey is a PhD candidate with interests in computational text analysis, LLMs, Writing in the Disciplines, and formative assessment at scale. His dissertation explores the use of computational methods to help teaching assistants assess writing in STEM courses taught at scale.

We are happy for the opportunity to learn more about the background to the work, how it started, and how it’s going.

Interviewer, Traci Nathans-Kelly (TNK): Your paper was selected for the 2024 Hayhoe Award at IEEE ProComm. Tell us a bit about how you landed on this article’s topic, which is rich with insights and fresh perspectives.

Ben Markey: As I imagine with most topics, it’s got a bit of a history. Through conversations with my advisor, we landed on working with TAs in Spring of 2023, with a particular focus on quantitatively driven fields that have taken an interest helping students become better professional and technical communicators. Especially in classes taught at scale, designing effective writing tasks and implementing helpful assessment is a problem yet to be solved. Since I was still in coursework, we had to start small, and since digging didn’t turn up much in the way of research into TA perceptions of writing, we figured we should start by interviewing a few TAs. The work got a bit sidetracked in Fall ’23 as we ended up devoting a lot of attention to a Written Comm piece analyzing ChatGPT generated text at scale, but towards the end of the semester I had to write a term paper for a Discourse Analysis seminar and figured I’d get some mileage out of the transcripts. That’s how I landed on frame semantics.

Portrait of Benjamin Markey, IEEE ProComm 2024 Hayhoe Fellow Award.

TNK: IEEE ProComm 2024 was fortunate to receive your research article for this year’s conference, acknowledged so beautifully by Dr. George Hayhoe during our awards ceremony. How did you come to decide that this venue was the right fit for your work?

Markey: I’m new at all of this and so I kind of just look at what the people around me are doing. Michael Laudenbach (who has since graduated and got a job at NJIT – woot!) in particular is someone I use as a model for my academic choices. We had discussed ProComm in the past. I know he has submitted and presented previously. When the news came out that CMU was to host this past conference, he and I chatted about potential projects. I threw out the Discourse Analysis paper about TA perceptions of writing and he encouraged me to submit. After that, I tinkered with the framing a bit and sent it on in.

TNK: What are the next steps related to this topic? 

Markey: Well, I’m currently in the process of revising it further for journal publication. I hope to have it submitted by the beginning of this semester. Right now, I’m ahead of schedule, so I’m optimistic it’ll get done.

As for the topic itself, I’m not sure what is next. Realistically, this push for journal publication is probably the end. That said, work over the next couple years will involve TAs, it will involve writing in statistics, and it will involve writing assessment.

TNK: What is the “next big thing” in sight for your future research and writing?

Markey: Topically, the work will involve leveraging computational means – machine learning, LLMs, corpus linguistics – to help bring TA perceptions into alignment. I’m personally interested in working with the verbs we commonly see on writing rubrics: present, account for, describe, analyze, demonstrate, summarize, etc. Each discipline has specific ways of doing those verbs in written communication. The hope is we might leverage technology to help TAs accurately identify and reliably assess those moments in the student writing.

IEEE ProComm thanks Ben for taking time with this interview.