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Using the educational social media platform Edmodo, teachers at multiple sites developed and implemented instruction that gave their high school students a chance to talk to students across the nation about the texts they were reading and to work collaboratively to develop writing related to their understanding.

Current quantitative methods in second language (L2) acquisition have proven useful in examining how phraseological unit production changes over time. However, these methods are limited in that they do not allow for the analysis of individual differences in those changes. This study demonstrates the potential for Latent Curve Modeling, a type of Structural Equation Modeling, to address questions about productive phraseological knowledge development. It examines growth in multiple indices of bigram and trigram use (frequency, association strength, proportion) in the spoken output of L2 speakers over the course of a 4-month study. Results for unconditional latent curve models indicate that spoken bigram and trigram proportions increased for the entire group over the study period. Conditional latent curve models showed that growth in bigram frequency and bigram proportion was predicted by proficiency, with less proficient writers experiencing greater growth. These models also demonstrated that conversation dyad predicted growth in spoken bigram frequency in that L2 speakers with L2 conversation partners, as compared to first language (L1) partners, produced more high-frequency bigrams over time. These results have implications for research on L2 productive phraseological knowledge development specifically and longitudinal L2 research in general.

In this article, we describe a two-day, intensive STEM training that we piloted in summer of 2022 to prepare newly hired professional staff to support STEM writers. The training was created by the director and associate director and was offered to two professional consultants and two graduate assistant consultants in-person over a two-day period before the start of the fall semester. Staff training should always be responsive to local contexts, and we are aware our model may not transfer to other university settings. However, we do hope that our pilot offers a model that other universities can adapt to meet local needs and implement when training professional and graduate staff. Although we focus on professional staff, our model may also be useful for supplementing a generalist approach to training graduate and undergraduate peer tutors who work closely with STEM writers or as a primary form of training for embedded consultants working within STEM courses. As we discuss our model, we turn to writing in the disciplines scholarship to explain our choices and ground our pedagogy. We also turn to research on tutor training and writing center staff professional development. As we describe our training activities, we also identify areas for improvement based on our own perspective and that of our professional and graduate staff attendees. [ABSTRACT FROM AUTHOR]