Article "Machine learning based feedback on textual student answers in large courses" 

The pre-proof version of my article "Machine learning based feedback on textual student answers in large courses" with S. Krusche and B. Bruegge is now published with the Journal "Computers and Education: Artificial Intelligence". DOI: doi.org/10.1016/j.caeai.2022.1

@oneabstractaday

Paper "A Machine Learning Approach for Suggesting Feedback in Textual Exercises in Large Courses" 

The third and last paper I want to toot about is titled "A Machine Learning Approach for Suggesting Feedback in Textual Exercises in Large Courses" and was presented at the 8th ACM Conference on Learning @ Scale (L@S) in 2021. DOI: doi.org/10.1145/3430895.346013 Preprint: brn.is/las21

This paper presents two things: (1) CoFee (approach) and (2) Athene (reference implementation). 🧵

Paper "Towards the Automation of Grading Textual Student Submissions to Open-ended Questions" 

The second paper I want to share today is titled “Towards the Automation of Grading Textual Student Submissions to Open-ended Questions” and was published at the European Conference on Software Engineering Education (ECSEE) in 2020. DOI : doi.org/10.1145/3396802.339680 Preprint: brn.is/ecsee20
In this paper we present an algorithm using topic modeling for segmenting the submissions into smaller blocks.

Paper "Toward the Automatic Assessment of Text Exercises" 

I published my first short paper titled “Toward the Automatic Assessment of Text Exercises” for the 2nd Workshop on Innovative Software Engineering Education (ISEE) in 2019.

The paper argues that automated assessment provides more individual feedback for students, combined with quicker feedback and grading cycles. We introduce a concept for automatic assessment of text exercises using machine learning techniques.

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