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The Post'Em Tool is a way for instructors to provide detailed text feedback to students by uploading a single CSV file.
Nearly all prominent marketplaces use R&R systems, which typically allow the two sides of the market to rate and review each other by awarding stars (1 to 5), providing text feedback, or both.
We are now curious about which themes (both strengths and areas for improvement) in the text feedback can be added to our current models of predicting work outcomes from references.
Teachers can provide both voice and text feedback comments on specific phrases or entire assignments and allows assessment with standards-aligned rubrics to show students how specific parts of their work affect their grade.
Quantitative analysis of preferences and free text feedback were used.
It also employs natural language processing for inferring the quality of text feedback between students.
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Mapping of the free-text feedback comments may assist in assessing milestones.
Comments received in the free-text feedback were encouraging, that generally, students found the session useful.
Free-text feedback was reviewed and summarised by two researchers (AP and MA).
Free-text feedback was positive overall with students commenting that it was "helpful", "enjoyable" and "boosted confidence".
Free-text feedback emphasized the multi-dimensional nature of ethnicity and highlighted the importance of identifying underlying causal processes linking particular ethnic identities to health outcomes.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com