Large language models (LLMs) are increasingly used to support automated writing evaluation (AWE), both for purposes of scoring and feedback. However, LLMs present challenges to interpretability, making it hard to evaluate the construct validity of scoring and feedback models. BIOT (best interpretable orthogonal transformations) is a new method of analysis that makes dimensions of an embedding interpretable by aligning them with external predictors. It was originally developed to improve the interpretability of multidimensional scaling models. However, This paper shows that BIOT can be used to align LLM embeddings with an interpretable writing trait model developed using multidimensional analysis of classical NLP features to measure latent dimensions of writing style and writing quality. This makes it possible to determine whether an AWE model built using an LLM is aligned with known (and construct-relevant) dimensions of textual variation, supporting construct validity. Specifically, we examine the alignment between the hidden layers of deBERTA, a small LLM that has been shown to be useful for a variety of natural language processing applications, and a writing trait model developed through factor analysis of classical features used in existing AWE models. Specific dimensions of transformed deBERTA layers are strongly correlated with these classical factors. When the transformation matrix derived using BIOT is applied to token vectors, it is also possible to visualize which tokens in the original text contributed to high or low scores on a specific dimension. • Large language models (LLMs) are increasingly used to support automated writing evaluate (AWE). • LLMs present challenges to interpretability, making it hard to evaluate construct validity of scoring and feedback models. • BIOT is a new interpretation method that aligns embedding dimensions with external predictors. • Specifically, BIOT can be used to align LLM embeddings with classical NLP measures of aspects of style and writing quality. • This demonstrates a general method to determine whether an LLM latently represents construct-relevant dimensions.

Heeding previous scholars' calls for a critical investigation of the role of reflection in the professional development of tutors, this article examines reflections written by tutors in the context of conference records. More specifically, the authors investigate the consequences of incorporating a prompt to reflect on tutoring strategies into our online conference-records database. The authors first present the results of their opening coding of nearly 300 conference records, offering a taxonomy of specific types of reflections found in the conference records. The authors then identify three shifts in the content of conference records written after the introduction of the reflection prompt. Finally, the authors draw on analysis of tutor interviews to illuminate how the positive influence of the reflection prompt is inextricably linked to a larger culture of reflection that is often collaborative and leads to transfer of learning within and beyond the writing center.

This article argues that teaching Asian American literature should include immeasurable and nontangible factors that accompany racial grief, such as cultural betrayal, the trauma of belonging interstitially, and the sensation of displacement. I propose that these be introduced via a gothic motif, such as the double, haunting, and possession by ghosts. Such motifs have the advantage of familiarity (or, if not, are quite easy to explain) and being psychoanalytically informed.

Andrew Hoberek, John Burt, David Kadlec, Jamie Owen Daniel, Shelly Eversley, Catherine Jurca, Aparajita Sagar, , Twentieth-Century Literature in the New Century: A Symposium, College English, Vol. 64, No. 1 (Sep., 2001), pp. 9-33

Confronts the problem of applicants for admittance to graduate programs in the Humanities failing to have been told what would be wanted on their applications. Discusses helping students learn to explain their specialties to nonspecialists. Assumes that learning to summarize and “enter the conversations around one” is excellent rhetorical training regardless of the student’s profession.