Automated, content-focused feedback for a writing-to-learn assignment in an undergraduate organic chemistry course-Reference-Cited by-同舟云学术

Automated, content-focused feedback for a writing-to-learn assignment in an undergraduate organic chemistry course

Published:2023-03-13 Issue: Volume: Page:
ISSN:
Container-title:LAK23: 13th International Learning Analytics and Knowledge Conference
language:
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Author:

Watts Field M.¹^ORCID,Dood Amber J.¹^ORCID,Shultz Ginger V.¹^ORCID

Affiliation:

1. University of Michigan, United States

Funder

NSF (National Science Foundation)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3576050.3576053

Reference34 articles.

1. The contributions of writing to learning and development: Results from a large-scale multi-institutional study;Anderson Paul;Research in the Teaching of English,2015

2. Organic Chemistry Students’ Written Descriptions and Explanations of Resonance and Its Influence on Reactivity

3. François Chollet and Others. 2015. Keras. https://keras.io. https://keras.io François Chollet and Others. 2015. Keras. https://keras.io. https://keras.io

4. A review of automated feedback systems for learners: Classification framework, challenges and opportunities

5. Analyzing explanations of substitution reactions using lexical analysis and logistic regression techniques

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