An analysis of the relationship between 4 automated writing evaluation software and the outcomes in the writing program administrator's "WPA outcomes for first year composition

My study examined Automated Writing Evaluation tools (AWE) and their role within writing instruction. This examination was framed as a comparison of 4 AWE tools and the different outcomes in the Writing Program Administrators “Outcomes Statement for First Year Composition” (the OS). I also reviewed studies that identify feedback as an effective tool within composition instruction as well as literature related to the growth of AWE and the 2 different ways that these programs are being utilized: to provide scoring and to generate feedback. My research focused on the feedback generating component of AWE and their relationship with helping students to meet the outcomes outlined in the OS. To complete this analysis, I coded the OS, using its outcomes as a reliable indicator of the perspectives of the academic community regarding First Year Composition (FYC). This coding was applied to text associated with two different kinds of feedback related AWEs. Two of the AWE used in this study facilitated human feedback using analytical properties: Writerkey and Eli Review. While the other 2 generated automated feedback: WriteLab and PEG Writing Scholar. I also reviewed instructional documents associated with each AWE and used the coding to compare the features described in each text with the different outcomes in the OS. The most frequently occurring coding from the feedback was related to Rhetorical Knowledge and other outcomes associated with revision, while the most common codes from the instructional documents were associated with feedback and collaboration. My research also revealed none of these AWE were capable of addressing certain outcomes, these were mostly related to activities outside of the actual process of composing, like the act of reading and the various writing mediums.