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Students exhibit heterogeneity in writing motivation and ability. Profiles based on measures of motivation and ability might help to describe this heterogeneity and better understand the effects of interventions aimed at improving students’ writing outcomes. We aimed to identify writing motivation and ability profiles in U.S. middle-school students participating in an automated writing evaluation (AWE) intervention using MI Write, and to identify transition paths between profiles as a result of the intervention. We identified profiles and transition paths of 2,487 students using latent profile and latent transition analysis. Four motivation and ability profiles emerged from a latent transition analysis with self-reported writing self-efficacy, attitudes toward writing, and a measure of writing writing: Low, Low/Mid, Mid/High, and High. Most students started the school year in the Low/Mid (38%) and Mid/High (30%) profiles. Only 11% of students started the school year in the High profile. Between 50 and 70% of students maintained the same profile in the Spring. Approximately 30% of students were likely to move one profile higher in the Spring. Fewer than 1% of students exhibited steeper transitions (e.g., from High to Low profile). Random assignment to treatment did not significantly influence transition paths. Likewise, gender, being a member of a priority population, or receiving special education services did not significantly influence transition paths. Results provide a promising profiling strategy focused on students’ attitudes, motivations, and ability and show students’ likeliness to belong to each profile based on their demographic characteristics. Finally, despite previous research indicating positive effects of AWE on writing motivation, results indicate that simply providing access to AWE in schools serving priority populations is insufficient to produce meaningful changes in students’ writing motivation profiles or writing outcomes. Therefore, interventions targeting writing motivation, in conjunction with AWE, could improve results.

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