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Direct linkRanalli, Jim; Yamashita, Taichi – Language Learning & Technology, 2022
To the extent automated written corrective feedback (AWCF) tools such as Grammarly are based on sophisticated error-correction technologies, such as machine-learning techniques, they have the potential to find and correct more common L2 error types than simpler spelling and grammar checkers such as the one included in Microsoft Word (technically…
Descriptors: Error Correction, Feedback (Response), Computer Software, Second Language Learning
Download full textGenon, Lynrose Jane Dumandan; Torres, Chezka Bianca P. – English Language Teaching Educational Journal, 2020
This qualitative study identified the language assessment practices in terms of purpose, type, and timing in four elementary language classes in the Philippines. It then evaluated the constructive alignment and content validity of the assessment and described how the constructive alignment reflects the quality of teaching and learning in these…
Descriptors: Alignment (Education), Second Language Learning, Second Language Instruction, Teaching Methods
Smaill, Esther; Darr, Charles – New Zealand Council for Educational Research, 2020
In February 2020, the Ministry of Education asked the New Zealand Council for Educational Research (NZCER) to examine the curriculum-levelling construct that sits at the heart of The New Zealand Curriculum (Ministry of Education, 2007). A key goal of the research was to investigate, whether-- and if so, how--the construct helps (or hinders)…
Descriptors: Curriculum Development, Decision Making, Educational Planning, Program Development
