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Dan Song; Alexander F. Tang – Language Learning & Technology, 2025
While many studies have addressed the benefits of technology-assisted L2 writing, limited research has delved into how generative artificial intelligence (GAI) supports students in completing their writing tasks in Mandarin Chinese. In this study, 26 university-level Mandarin Chinese foreign language students completed two writing tasks on two…
Descriptors: Artificial Intelligence, Second Language Learning, Standardized Tests, Writing Tests
Sarah R. Cohodes; Astrid Pineda – Blueprint Labs, 2025
The charter school movement encompasses many school models. In Massachusetts in the 2010's, the site of our study, urban charter schools primarily used "No Excuses" practices, whereas nonurban charters had greater model variety. Using randomized admissions lotteries, we estimate the impact of charter schools by locality on college…
Descriptors: Charter Schools, College Enrollment, Graduation, Urban Schools
Sarah Cohodes; Astrid Pineda; Amanda Schmidt – Blueprint Labs, 2025
Most of the literature on lottery-based charter school research focuses on charters in large urban centers, primarily finding that they raise standardized test scores. In contrast, the limited rigorous research on rural and suburban charters suggests that they reduce or do not affect test scores. However, this evidence is limited, and almost no…
Descriptors: Charter Schools, College Enrollment, Graduation, Urban Schools
Steve Hood; Cynthia Grua – Utah System of Higher Education, 2025
Prior learning refers to knowledge, skills, or competencies acquired through formal and informal education outside a traditional academic environment. This can include a student acquiring knowledge or skills through employee-sponsored training or military training, earning an industry certification, or taking national standardized exams. In the…
Descriptors: Prior Learning, Public Colleges, College Students, College Credits

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